From 87e8fe92c9328f971044389ed768ea3cc5c6b3d5 Mon Sep 17 00:00:00 2001 From: Olaoluwa Osuntokun Date: Thu, 18 Nov 2021 18:25:56 -0800 Subject: [PATCH] btcec: convert package into go module, alias to dcrec In this commit, we turn the package into a new Go module (version 2), and then port over the current set of types and functions to mainly alias to the more optimized and maintained dcrec variant. Taking a look at the benchmarks, most operations other than normalization (which IIRC is a bit slower now due to constant time fixes) enjoy some nice speeds up: ``` benchcmp is deprecated in favor of benchstat: https://pkg.go.dev/golang.org/x/perf/cmd/benchstat benchmark old ns/op new ns/op delta BenchmarkAddJacobian-8 464 328 -29.20% BenchmarkAddJacobianNotZOne-8 1138 372 -67.27% BenchmarkScalarBaseMult-8 47336 31531 -33.39% BenchmarkScalarBaseMultLarge-8 42465 32057 -24.51% BenchmarkScalarMult-8 123355 117579 -4.68% BenchmarkNAF-8 582 168 -71.12% BenchmarkSigVerify-8 175414 120794 -31.14% BenchmarkFieldNormalize-8 23.8 24.4 +2.39% BenchmarkParseCompressedPubKey-8 24282 10907 -55.08% ``` --- btcec/README.md | 36 +- btcec/bench_test.go | 162 +++-- btcec/btcec.go | 963 +-------------------------- btcec/btcec_test.go | 243 +++---- btcec/ciphering.go | 204 +----- btcec/ciphering_test.go | 147 +---- btcec/curve.go | 60 ++ btcec/error.go | 16 + btcec/example_test.go | 94 +-- btcec/field.go | 1385 +-------------------------------------- btcec/field_test.go | 1054 +++++++++++++---------------- btcec/genprecomps.go | 63 -- btcec/gensecp256k1.go | 203 ------ btcec/go.mod | 9 + btcec/go.sum | 49 ++ btcec/modnscalar.go | 42 ++ btcec/precompute.go | 67 -- btcec/privkey.go | 56 +- btcec/privkey_test.go | 10 +- btcec/pubkey.go | 171 +---- btcec/pubkey_test.go | 6 +- btcec/secp256k1.go | 10 - btcec/signature.go | 493 +++----------- btcec/signature_test.go | 130 ++-- 24 files changed, 1122 insertions(+), 4551 deletions(-) create mode 100644 btcec/curve.go create mode 100644 btcec/error.go delete mode 100644 btcec/genprecomps.go delete mode 100644 btcec/gensecp256k1.go create mode 100644 btcec/go.mod create mode 100644 btcec/go.sum create mode 100644 btcec/modnscalar.go delete mode 100644 btcec/precompute.go delete mode 100644 btcec/secp256k1.go diff --git a/btcec/README.md b/btcec/README.md index a6dd2cf2..cbf63dd0 100644 --- a/btcec/README.md +++ b/btcec/README.md @@ -3,7 +3,7 @@ btcec [![Build Status](https://github.com/btcsuite/btcd/workflows/Build%20and%20Test/badge.svg)](https://github.com/btcsuite/btcd/actions) [![ISC License](http://img.shields.io/badge/license-ISC-blue.svg)](http://copyfree.org) -[![GoDoc](https://pkg.go.dev/github.com/btcsuite/btcd/btcec?status.png)](https://pkg.go.dev/github.com/btcsuite/btcd/btcec) +[![GoDoc](https://pkg.go.dev/github.com/btcsuite/btcd/btcec/v2?status.png)](https://pkg.go.dev/github.com/btcsuite/btcd/btcec/v2) Package btcec implements elliptic curve cryptography needed for working with Bitcoin (secp256k1 only for now). It is designed so that it may be used with the @@ -20,47 +20,19 @@ use secp256k1 elliptic curve cryptography. ## Installation and Updating ```bash -$ go get -u github.com/btcsuite/btcd/btcec +$ go install -u -v github.com/btcsuite/btcd/btcec/v2 ``` ## Examples -* [Sign Message](https://pkg.go.dev/github.com/btcsuite/btcd/btcec#example-package--SignMessage) +* [Sign Message](https://pkg.go.dev/github.com/btcsuite/btcd/btcec/v2#example-package--SignMessage) Demonstrates signing a message with a secp256k1 private key that is first parsed form raw bytes and serializing the generated signature. -* [Verify Signature](https://pkg.go.dev/github.com/btcsuite/btcd/btcec#example-package--VerifySignature) +* [Verify Signature](https://pkg.go.dev/github.com/btcsuite/btcd/btcec/v2#example-package--VerifySignature) Demonstrates verifying a secp256k1 signature against a public key that is first parsed from raw bytes. The signature is also parsed from raw bytes. -* [Encryption](https://pkg.go.dev/github.com/btcsuite/btcd/btcec#example-package--EncryptMessage) - Demonstrates encrypting a message for a public key that is first parsed from - raw bytes, then decrypting it using the corresponding private key. - -* [Decryption](https://pkg.go.dev/github.com/btcsuite/btcd/btcec#example-package--DecryptMessage) - Demonstrates decrypting a message using a private key that is first parsed - from raw bytes. - -## GPG Verification Key - -All official release tags are signed by Conformal so users can ensure the code -has not been tampered with and is coming from the btcsuite developers. To -verify the signature perform the following: - -- Download the public key from the Conformal website at - https://opensource.conformal.com/GIT-GPG-KEY-conformal.txt - -- Import the public key into your GPG keyring: - ```bash - gpg --import GIT-GPG-KEY-conformal.txt - ``` - -- Verify the release tag with the following command where `TAG_NAME` is a - placeholder for the specific tag: - ```bash - git tag -v TAG_NAME - ``` - ## License Package btcec is licensed under the [copyfree](http://copyfree.org) ISC License diff --git a/btcec/bench_test.go b/btcec/bench_test.go index 7ccd78cf..475a4afd 100644 --- a/btcec/bench_test.go +++ b/btcec/bench_test.go @@ -6,43 +6,114 @@ package btcec import ( "encoding/hex" + "math/big" "testing" + + secp "github.com/decred/dcrd/dcrec/secp256k1/v4" ) -// BenchmarkAddJacobian benchmarks the secp256k1 curve addJacobian function with +// setHex decodes the passed big-endian hex string into the internal field value +// representation. Only the first 32-bytes are used. +// +// This is NOT constant time. +// +// The field value is returned to support chaining. This enables syntax like: +// f := new(FieldVal).SetHex("0abc").Add(1) so that f = 0x0abc + 1 +func setHex(hexString string) *FieldVal { + if len(hexString)%2 != 0 { + hexString = "0" + hexString + } + bytes, _ := hex.DecodeString(hexString) + + var f FieldVal + f.SetByteSlice(bytes) + + return &f +} + +// hexToFieldVal converts the passed hex string into a FieldVal and will panic +// if there is an error. This is only provided for the hard-coded constants so +// errors in the source code can be detected. It will only (and must only) be +// called with hard-coded values. +func hexToFieldVal(s string) *FieldVal { + b, err := hex.DecodeString(s) + if err != nil { + panic("invalid hex in source file: " + s) + } + var f FieldVal + if overflow := f.SetByteSlice(b); overflow { + panic("hex in source file overflows mod P: " + s) + } + return &f +} + +// fromHex converts the passed hex string into a big integer pointer and will +// panic is there is an error. This is only provided for the hard-coded +// constants so errors in the source code can bet detected. It will only (and +// must only) be called for initialization purposes. +func fromHex(s string) *big.Int { + if s == "" { + return big.NewInt(0) + } + r, ok := new(big.Int).SetString(s, 16) + if !ok { + panic("invalid hex in source file: " + s) + } + return r +} + +// jacobianPointFromHex decodes the passed big-endian hex strings into a +// Jacobian point with its internal fields set to the resulting values. Only +// the first 32-bytes are used. +func jacobianPointFromHex(x, y, z string) JacobianPoint { + var p JacobianPoint + p.X = *setHex(x) + p.Y = *setHex(y) + p.Z = *setHex(z) + + return p +} + +// BenchmarkAddNonConst benchmarks the secp256k1 curve AddNonConst function with // Z values of 1 so that the associated optimizations are used. func BenchmarkAddJacobian(b *testing.B) { - b.StopTimer() - x1 := new(fieldVal).SetHex("34f9460f0e4f08393d192b3c5133a6ba099aa0ad9fd54ebccfacdfa239ff49c6") - y1 := new(fieldVal).SetHex("0b71ea9bd730fd8923f6d25a7a91e7dd7728a960686cb5a901bb419e0f2ca232") - z1 := new(fieldVal).SetHex("1") - x2 := new(fieldVal).SetHex("34f9460f0e4f08393d192b3c5133a6ba099aa0ad9fd54ebccfacdfa239ff49c6") - y2 := new(fieldVal).SetHex("0b71ea9bd730fd8923f6d25a7a91e7dd7728a960686cb5a901bb419e0f2ca232") - z2 := new(fieldVal).SetHex("1") - x3, y3, z3 := new(fieldVal), new(fieldVal), new(fieldVal) - curve := S256() - b.StartTimer() + p1 := jacobianPointFromHex( + "34f9460f0e4f08393d192b3c5133a6ba099aa0ad9fd54ebccfacdfa239ff49c6", + "0b71ea9bd730fd8923f6d25a7a91e7dd7728a960686cb5a901bb419e0f2ca232", + "1", + ) + p2 := jacobianPointFromHex( + "34f9460f0e4f08393d192b3c5133a6ba099aa0ad9fd54ebccfacdfa239ff49c6", + "0b71ea9bd730fd8923f6d25a7a91e7dd7728a960686cb5a901bb419e0f2ca232", + "1", + ) + + b.ReportAllocs() + b.ResetTimer() + var result JacobianPoint for i := 0; i < b.N; i++ { - curve.addJacobian(x1, y1, z1, x2, y2, z2, x3, y3, z3) + secp.AddNonConst(&p1, &p2, &result) } } -// BenchmarkAddJacobianNotZOne benchmarks the secp256k1 curve addJacobian +// BenchmarkAddNonConstNotZOne benchmarks the secp256k1 curve AddNonConst // function with Z values other than one so the optimizations associated with // Z=1 aren't used. func BenchmarkAddJacobianNotZOne(b *testing.B) { - b.StopTimer() - x1 := new(fieldVal).SetHex("d3e5183c393c20e4f464acf144ce9ae8266a82b67f553af33eb37e88e7fd2718") - y1 := new(fieldVal).SetHex("5b8f54deb987ec491fb692d3d48f3eebb9454b034365ad480dda0cf079651190") - z1 := new(fieldVal).SetHex("2") - x2 := new(fieldVal).SetHex("91abba6a34b7481d922a4bd6a04899d5a686f6cf6da4e66a0cb427fb25c04bd4") - y2 := new(fieldVal).SetHex("03fede65e30b4e7576a2abefc963ddbf9fdccbf791b77c29beadefe49951f7d1") - z2 := new(fieldVal).SetHex("3") - x3, y3, z3 := new(fieldVal), new(fieldVal), new(fieldVal) - curve := S256() - b.StartTimer() + x1 := setHex("d3e5183c393c20e4f464acf144ce9ae8266a82b67f553af33eb37e88e7fd2718") + y1 := setHex("5b8f54deb987ec491fb692d3d48f3eebb9454b034365ad480dda0cf079651190") + z1 := setHex("2") + x2 := setHex("91abba6a34b7481d922a4bd6a04899d5a686f6cf6da4e66a0cb427fb25c04bd4") + y2 := setHex("03fede65e30b4e7576a2abefc963ddbf9fdccbf791b77c29beadefe49951f7d1") + z2 := setHex("3") + p1 := MakeJacobianPoint(x1, y1, z1) + p2 := MakeJacobianPoint(x2, y2, z2) + + b.ReportAllocs() + b.ResetTimer() + var result JacobianPoint for i := 0; i < b.N; i++ { - curve.addJacobian(x1, y1, z1, x2, y2, z2, x3, y3, z3) + AddNonConst(&p1, &p2, &result) } } @@ -77,12 +148,20 @@ func BenchmarkScalarMult(b *testing.B) { } } -// BenchmarkNAF benchmarks the NAF function. -func BenchmarkNAF(b *testing.B) { - k := fromHex("d74bf844b0862475103d96a611cf2d898447e288d34b360bc885cb8ce7c00575") - for i := 0; i < b.N; i++ { - NAF(k.Bytes()) +// hexToModNScalar converts the passed hex string into a ModNScalar and will +// panic if there is an error. This is only provided for the hard-coded +// constants so errors in the source code can be detected. It will only (and +// must only) be called with hard-coded values. +func hexToModNScalar(s string) *ModNScalar { + b, err := hex.DecodeString(s) + if err != nil { + panic("invalid hex in source file: " + s) } + var scalar ModNScalar + if overflow := scalar.SetByteSlice(b); overflow { + panic("hex in source file overflows mod N scalar: " + s) + } + return &scalar } // BenchmarkSigVerify benchmarks how long it takes the secp256k1 curve to @@ -91,27 +170,26 @@ func BenchmarkSigVerify(b *testing.B) { b.StopTimer() // Randomly generated keypair. // Private key: 9e0699c91ca1e3b7e3c9ba71eb71c89890872be97576010fe593fbf3fd57e66d - pubKey := PublicKey{ - Curve: S256(), - X: fromHex("d2e670a19c6d753d1a6d8b20bd045df8a08fb162cf508956c31268c6d81ffdab"), - Y: fromHex("ab65528eefbb8057aa85d597258a3fbd481a24633bc9b47a9aa045c91371de52"), - } + pubKey := NewPublicKey( + hexToFieldVal("d2e670a19c6d753d1a6d8b20bd045df8a08fb162cf508956c31268c6d81ffdab"), + hexToFieldVal("ab65528eefbb8057aa85d597258a3fbd481a24633bc9b47a9aa045c91371de52"), + ) // Double sha256 of []byte{0x01, 0x02, 0x03, 0x04} msgHash := fromHex("8de472e2399610baaa7f84840547cd409434e31f5d3bd71e4d947f283874f9c0") - sig := Signature{ - R: fromHex("fef45d2892953aa5bbcdb057b5e98b208f1617a7498af7eb765574e29b5d9c2c"), - S: fromHex("d47563f52aac6b04b55de236b7c515eb9311757db01e02cff079c3ca6efb063f"), - } + sig := NewSignature( + hexToModNScalar("fef45d2892953aa5bbcdb057b5e98b208f1617a7498af7eb765574e29b5d9c2c"), + hexToModNScalar("d47563f52aac6b04b55de236b7c515eb9311757db01e02cff079c3ca6efb063f"), + ) - if !sig.Verify(msgHash.Bytes(), &pubKey) { + if !sig.Verify(msgHash.Bytes(), pubKey) { b.Errorf("Signature failed to verify") return } b.StartTimer() for i := 0; i < b.N; i++ { - sig.Verify(msgHash.Bytes(), &pubKey) + sig.Verify(msgHash.Bytes(), pubKey) } } @@ -119,7 +197,7 @@ func BenchmarkSigVerify(b *testing.B) { // to perform normalization (which includes modular reduction). func BenchmarkFieldNormalize(b *testing.B) { // The normalize function is constant time so default value is fine. - f := new(fieldVal) + var f FieldVal for i := 0; i < b.N; i++ { f.Normalize() } @@ -138,7 +216,7 @@ func BenchmarkParseCompressedPubKey(b *testing.B) { b.ReportAllocs() b.ResetTimer() for i := 0; i < b.N; i++ { - pk, err = ParsePubKey(rawPk, S256()) + pk, err = ParsePubKey(rawPk) } _ = pk _ = err diff --git a/btcec/btcec.go b/btcec/btcec.go index a2e20f4b..efde8d6a 100644 --- a/btcec/btcec.go +++ b/btcec/btcec.go @@ -20,959 +20,22 @@ package btcec // reverse the transform than to operate in affine coordinates. import ( - "crypto/elliptic" - "math/big" - "sync" + secp "github.com/decred/dcrd/dcrec/secp256k1/v4" ) -var ( - // fieldOne is simply the integer 1 in field representation. It is - // used to avoid needing to create it multiple times during the internal - // arithmetic. - fieldOne = new(fieldVal).SetInt(1) -) - -// KoblitzCurve supports a koblitz curve implementation that fits the ECC Curve -// interface from crypto/elliptic. -type KoblitzCurve struct { - *elliptic.CurveParams - - // q is the value (P+1)/4 used to compute the square root of field - // elements. - q *big.Int - - H int // cofactor of the curve. - halfOrder *big.Int // half the order N - - // fieldB is the constant B of the curve as a fieldVal. - fieldB *fieldVal - - // byteSize is simply the bit size / 8 and is provided for convenience - // since it is calculated repeatedly. - byteSize int - - // bytePoints - bytePoints *[32][256][3]fieldVal - - // The next 6 values are used specifically for endomorphism - // optimizations in ScalarMult. - - // lambda must fulfill lambda^3 = 1 mod N where N is the order of G. - lambda *big.Int - - // beta must fulfill beta^3 = 1 mod P where P is the prime field of the - // curve. - beta *fieldVal - - // See the EndomorphismVectors in gensecp256k1.go to see how these are - // derived. - a1 *big.Int - b1 *big.Int - a2 *big.Int - b2 *big.Int -} - -// Params returns the parameters for the curve. -func (curve *KoblitzCurve) Params() *elliptic.CurveParams { - return curve.CurveParams -} - -// bigAffineToField takes an affine point (x, y) as big integers and converts -// it to an affine point as field values. -func (curve *KoblitzCurve) bigAffineToField(x, y *big.Int) (*fieldVal, *fieldVal) { - x3, y3 := new(fieldVal), new(fieldVal) - x3.SetByteSlice(x.Bytes()) - y3.SetByteSlice(y.Bytes()) - - return x3, y3 -} - -// fieldJacobianToBigAffine takes a Jacobian point (x, y, z) as field values and -// converts it to an affine point as big integers. -func (curve *KoblitzCurve) fieldJacobianToBigAffine(x, y, z *fieldVal) (*big.Int, *big.Int) { - // Inversions are expensive and both point addition and point doubling - // are faster when working with points that have a z value of one. So, - // if the point needs to be converted to affine, go ahead and normalize - // the point itself at the same time as the calculation is the same. - var zInv, tempZ fieldVal - zInv.Set(z).Inverse() // zInv = Z^-1 - tempZ.SquareVal(&zInv) // tempZ = Z^-2 - x.Mul(&tempZ) // X = X/Z^2 (mag: 1) - y.Mul(tempZ.Mul(&zInv)) // Y = Y/Z^3 (mag: 1) - z.SetInt(1) // Z = 1 (mag: 1) - - // Normalize the x and y values. - x.Normalize() - y.Normalize() - - // Convert the field values for the now affine point to big.Ints. - x3, y3 := new(big.Int), new(big.Int) - x3.SetBytes(x.Bytes()[:]) - y3.SetBytes(y.Bytes()[:]) - return x3, y3 -} - -// IsOnCurve returns boolean if the point (x,y) is on the curve. -// Part of the elliptic.Curve interface. This function differs from the -// crypto/elliptic algorithm since a = 0 not -3. -func (curve *KoblitzCurve) IsOnCurve(x, y *big.Int) bool { - // Convert big ints to field values for faster arithmetic. - fx, fy := curve.bigAffineToField(x, y) - - // Elliptic curve equation for secp256k1 is: y^2 = x^3 + 7 - y2 := new(fieldVal).SquareVal(fy).Normalize() - result := new(fieldVal).SquareVal(fx).Mul(fx).AddInt(7).Normalize() - return y2.Equals(result) -} - -// addZ1AndZ2EqualsOne adds two Jacobian points that are already known to have -// z values of 1 and stores the result in (x3, y3, z3). That is to say -// (x1, y1, 1) + (x2, y2, 1) = (x3, y3, z3). It performs faster addition than -// the generic add routine since less arithmetic is needed due to the ability to -// avoid the z value multiplications. -func (curve *KoblitzCurve) addZ1AndZ2EqualsOne(x1, y1, z1, x2, y2, x3, y3, z3 *fieldVal) { - // To compute the point addition efficiently, this implementation splits - // the equation into intermediate elements which are used to minimize - // the number of field multiplications using the method shown at: - // http://hyperelliptic.org/EFD/g1p/auto-shortw-jacobian-0.html#addition-mmadd-2007-bl - // - // In particular it performs the calculations using the following: - // H = X2-X1, HH = H^2, I = 4*HH, J = H*I, r = 2*(Y2-Y1), V = X1*I - // X3 = r^2-J-2*V, Y3 = r*(V-X3)-2*Y1*J, Z3 = 2*H - // - // This results in a cost of 4 field multiplications, 2 field squarings, - // 6 field additions, and 5 integer multiplications. - - // When the x coordinates are the same for two points on the curve, the - // y coordinates either must be the same, in which case it is point - // doubling, or they are opposite and the result is the point at - // infinity per the group law for elliptic curve cryptography. - x1.Normalize() - y1.Normalize() - x2.Normalize() - y2.Normalize() - if x1.Equals(x2) { - if y1.Equals(y2) { - // Since x1 == x2 and y1 == y2, point doubling must be - // done, otherwise the addition would end up dividing - // by zero. - curve.doubleJacobian(x1, y1, z1, x3, y3, z3) - return - } - - // Since x1 == x2 and y1 == -y2, the sum is the point at - // infinity per the group law. - x3.SetInt(0) - y3.SetInt(0) - z3.SetInt(0) - return - } - - // Calculate X3, Y3, and Z3 according to the intermediate elements - // breakdown above. - var h, i, j, r, v fieldVal - var negJ, neg2V, negX3 fieldVal - h.Set(x1).Negate(1).Add(x2) // H = X2-X1 (mag: 3) - i.SquareVal(&h).MulInt(4) // I = 4*H^2 (mag: 4) - j.Mul2(&h, &i) // J = H*I (mag: 1) - r.Set(y1).Negate(1).Add(y2).MulInt(2) // r = 2*(Y2-Y1) (mag: 6) - v.Mul2(x1, &i) // V = X1*I (mag: 1) - negJ.Set(&j).Negate(1) // negJ = -J (mag: 2) - neg2V.Set(&v).MulInt(2).Negate(2) // neg2V = -(2*V) (mag: 3) - x3.Set(&r).Square().Add(&negJ).Add(&neg2V) // X3 = r^2-J-2*V (mag: 6) - negX3.Set(x3).Negate(6) // negX3 = -X3 (mag: 7) - j.Mul(y1).MulInt(2).Negate(2) // J = -(2*Y1*J) (mag: 3) - y3.Set(&v).Add(&negX3).Mul(&r).Add(&j) // Y3 = r*(V-X3)-2*Y1*J (mag: 4) - z3.Set(&h).MulInt(2) // Z3 = 2*H (mag: 6) - - // Normalize the resulting field values to a magnitude of 1 as needed. - x3.Normalize() - y3.Normalize() - z3.Normalize() -} - -// addZ1EqualsZ2 adds two Jacobian points that are already known to have the -// same z value and stores the result in (x3, y3, z3). That is to say -// (x1, y1, z1) + (x2, y2, z1) = (x3, y3, z3). It performs faster addition than -// the generic add routine since less arithmetic is needed due to the known -// equivalence. -func (curve *KoblitzCurve) addZ1EqualsZ2(x1, y1, z1, x2, y2, x3, y3, z3 *fieldVal) { - // To compute the point addition efficiently, this implementation splits - // the equation into intermediate elements which are used to minimize - // the number of field multiplications using a slightly modified version - // of the method shown at: - // http://hyperelliptic.org/EFD/g1p/auto-shortw-jacobian-0.html#addition-mmadd-2007-bl - // - // In particular it performs the calculations using the following: - // A = X2-X1, B = A^2, C=Y2-Y1, D = C^2, E = X1*B, F = X2*B - // X3 = D-E-F, Y3 = C*(E-X3)-Y1*(F-E), Z3 = Z1*A - // - // This results in a cost of 5 field multiplications, 2 field squarings, - // 9 field additions, and 0 integer multiplications. - - // When the x coordinates are the same for two points on the curve, the - // y coordinates either must be the same, in which case it is point - // doubling, or they are opposite and the result is the point at - // infinity per the group law for elliptic curve cryptography. - x1.Normalize() - y1.Normalize() - x2.Normalize() - y2.Normalize() - if x1.Equals(x2) { - if y1.Equals(y2) { - // Since x1 == x2 and y1 == y2, point doubling must be - // done, otherwise the addition would end up dividing - // by zero. - curve.doubleJacobian(x1, y1, z1, x3, y3, z3) - return - } - - // Since x1 == x2 and y1 == -y2, the sum is the point at - // infinity per the group law. - x3.SetInt(0) - y3.SetInt(0) - z3.SetInt(0) - return - } - - // Calculate X3, Y3, and Z3 according to the intermediate elements - // breakdown above. - var a, b, c, d, e, f fieldVal - var negX1, negY1, negE, negX3 fieldVal - negX1.Set(x1).Negate(1) // negX1 = -X1 (mag: 2) - negY1.Set(y1).Negate(1) // negY1 = -Y1 (mag: 2) - a.Set(&negX1).Add(x2) // A = X2-X1 (mag: 3) - b.SquareVal(&a) // B = A^2 (mag: 1) - c.Set(&negY1).Add(y2) // C = Y2-Y1 (mag: 3) - d.SquareVal(&c) // D = C^2 (mag: 1) - e.Mul2(x1, &b) // E = X1*B (mag: 1) - negE.Set(&e).Negate(1) // negE = -E (mag: 2) - f.Mul2(x2, &b) // F = X2*B (mag: 1) - x3.Add2(&e, &f).Negate(3).Add(&d) // X3 = D-E-F (mag: 5) - negX3.Set(x3).Negate(5).Normalize() // negX3 = -X3 (mag: 1) - y3.Set(y1).Mul(f.Add(&negE)).Negate(3) // Y3 = -(Y1*(F-E)) (mag: 4) - y3.Add(e.Add(&negX3).Mul(&c)) // Y3 = C*(E-X3)+Y3 (mag: 5) - z3.Mul2(z1, &a) // Z3 = Z1*A (mag: 1) - - // Normalize the resulting field values to a magnitude of 1 as needed. - x3.Normalize() - y3.Normalize() -} - -// addZ2EqualsOne adds two Jacobian points when the second point is already -// known to have a z value of 1 (and the z value for the first point is not 1) -// and stores the result in (x3, y3, z3). That is to say (x1, y1, z1) + -// (x2, y2, 1) = (x3, y3, z3). It performs faster addition than the generic -// add routine since less arithmetic is needed due to the ability to avoid -// multiplications by the second point's z value. -func (curve *KoblitzCurve) addZ2EqualsOne(x1, y1, z1, x2, y2, x3, y3, z3 *fieldVal) { - // To compute the point addition efficiently, this implementation splits - // the equation into intermediate elements which are used to minimize - // the number of field multiplications using the method shown at: - // http://hyperelliptic.org/EFD/g1p/auto-shortw-jacobian-0.html#addition-madd-2007-bl - // - // In particular it performs the calculations using the following: - // Z1Z1 = Z1^2, U2 = X2*Z1Z1, S2 = Y2*Z1*Z1Z1, H = U2-X1, HH = H^2, - // I = 4*HH, J = H*I, r = 2*(S2-Y1), V = X1*I - // X3 = r^2-J-2*V, Y3 = r*(V-X3)-2*Y1*J, Z3 = (Z1+H)^2-Z1Z1-HH - // - // This results in a cost of 7 field multiplications, 4 field squarings, - // 9 field additions, and 4 integer multiplications. - - // When the x coordinates are the same for two points on the curve, the - // y coordinates either must be the same, in which case it is point - // doubling, or they are opposite and the result is the point at - // infinity per the group law for elliptic curve cryptography. Since - // any number of Jacobian coordinates can represent the same affine - // point, the x and y values need to be converted to like terms. Due to - // the assumption made for this function that the second point has a z - // value of 1 (z2=1), the first point is already "converted". - var z1z1, u2, s2 fieldVal - x1.Normalize() - y1.Normalize() - z1z1.SquareVal(z1) // Z1Z1 = Z1^2 (mag: 1) - u2.Set(x2).Mul(&z1z1).Normalize() // U2 = X2*Z1Z1 (mag: 1) - s2.Set(y2).Mul(&z1z1).Mul(z1).Normalize() // S2 = Y2*Z1*Z1Z1 (mag: 1) - if x1.Equals(&u2) { - if y1.Equals(&s2) { - // Since x1 == x2 and y1 == y2, point doubling must be - // done, otherwise the addition would end up dividing - // by zero. - curve.doubleJacobian(x1, y1, z1, x3, y3, z3) - return - } - - // Since x1 == x2 and y1 == -y2, the sum is the point at - // infinity per the group law. - x3.SetInt(0) - y3.SetInt(0) - z3.SetInt(0) - return - } - - // Calculate X3, Y3, and Z3 according to the intermediate elements - // breakdown above. - var h, hh, i, j, r, rr, v fieldVal - var negX1, negY1, negX3 fieldVal - negX1.Set(x1).Negate(1) // negX1 = -X1 (mag: 2) - h.Add2(&u2, &negX1) // H = U2-X1 (mag: 3) - hh.SquareVal(&h) // HH = H^2 (mag: 1) - i.Set(&hh).MulInt(4) // I = 4 * HH (mag: 4) - j.Mul2(&h, &i) // J = H*I (mag: 1) - negY1.Set(y1).Negate(1) // negY1 = -Y1 (mag: 2) - r.Set(&s2).Add(&negY1).MulInt(2) // r = 2*(S2-Y1) (mag: 6) - rr.SquareVal(&r) // rr = r^2 (mag: 1) - v.Mul2(x1, &i) // V = X1*I (mag: 1) - x3.Set(&v).MulInt(2).Add(&j).Negate(3) // X3 = -(J+2*V) (mag: 4) - x3.Add(&rr) // X3 = r^2+X3 (mag: 5) - negX3.Set(x3).Negate(5) // negX3 = -X3 (mag: 6) - y3.Set(y1).Mul(&j).MulInt(2).Negate(2) // Y3 = -(2*Y1*J) (mag: 3) - y3.Add(v.Add(&negX3).Mul(&r)) // Y3 = r*(V-X3)+Y3 (mag: 4) - z3.Add2(z1, &h).Square() // Z3 = (Z1+H)^2 (mag: 1) - z3.Add(z1z1.Add(&hh).Negate(2)) // Z3 = Z3-(Z1Z1+HH) (mag: 4) - - // Normalize the resulting field values to a magnitude of 1 as needed. - x3.Normalize() - y3.Normalize() - z3.Normalize() -} - -// addGeneric adds two Jacobian points (x1, y1, z1) and (x2, y2, z2) without any -// assumptions about the z values of the two points and stores the result in -// (x3, y3, z3). That is to say (x1, y1, z1) + (x2, y2, z2) = (x3, y3, z3). It -// is the slowest of the add routines due to requiring the most arithmetic. -func (curve *KoblitzCurve) addGeneric(x1, y1, z1, x2, y2, z2, x3, y3, z3 *fieldVal) { - // To compute the point addition efficiently, this implementation splits - // the equation into intermediate elements which are used to minimize - // the number of field multiplications using the method shown at: - // http://hyperelliptic.org/EFD/g1p/auto-shortw-jacobian-0.html#addition-add-2007-bl - // - // In particular it performs the calculations using the following: - // Z1Z1 = Z1^2, Z2Z2 = Z2^2, U1 = X1*Z2Z2, U2 = X2*Z1Z1, S1 = Y1*Z2*Z2Z2 - // S2 = Y2*Z1*Z1Z1, H = U2-U1, I = (2*H)^2, J = H*I, r = 2*(S2-S1) - // V = U1*I - // X3 = r^2-J-2*V, Y3 = r*(V-X3)-2*S1*J, Z3 = ((Z1+Z2)^2-Z1Z1-Z2Z2)*H - // - // This results in a cost of 11 field multiplications, 5 field squarings, - // 9 field additions, and 4 integer multiplications. - - // When the x coordinates are the same for two points on the curve, the - // y coordinates either must be the same, in which case it is point - // doubling, or they are opposite and the result is the point at - // infinity. Since any number of Jacobian coordinates can represent the - // same affine point, the x and y values need to be converted to like - // terms. - var z1z1, z2z2, u1, u2, s1, s2 fieldVal - z1z1.SquareVal(z1) // Z1Z1 = Z1^2 (mag: 1) - z2z2.SquareVal(z2) // Z2Z2 = Z2^2 (mag: 1) - u1.Set(x1).Mul(&z2z2).Normalize() // U1 = X1*Z2Z2 (mag: 1) - u2.Set(x2).Mul(&z1z1).Normalize() // U2 = X2*Z1Z1 (mag: 1) - s1.Set(y1).Mul(&z2z2).Mul(z2).Normalize() // S1 = Y1*Z2*Z2Z2 (mag: 1) - s2.Set(y2).Mul(&z1z1).Mul(z1).Normalize() // S2 = Y2*Z1*Z1Z1 (mag: 1) - if u1.Equals(&u2) { - if s1.Equals(&s2) { - // Since x1 == x2 and y1 == y2, point doubling must be - // done, otherwise the addition would end up dividing - // by zero. - curve.doubleJacobian(x1, y1, z1, x3, y3, z3) - return - } - - // Since x1 == x2 and y1 == -y2, the sum is the point at - // infinity per the group law. - x3.SetInt(0) - y3.SetInt(0) - z3.SetInt(0) - return - } - - // Calculate X3, Y3, and Z3 according to the intermediate elements - // breakdown above. - var h, i, j, r, rr, v fieldVal - var negU1, negS1, negX3 fieldVal - negU1.Set(&u1).Negate(1) // negU1 = -U1 (mag: 2) - h.Add2(&u2, &negU1) // H = U2-U1 (mag: 3) - i.Set(&h).MulInt(2).Square() // I = (2*H)^2 (mag: 2) - j.Mul2(&h, &i) // J = H*I (mag: 1) - negS1.Set(&s1).Negate(1) // negS1 = -S1 (mag: 2) - r.Set(&s2).Add(&negS1).MulInt(2) // r = 2*(S2-S1) (mag: 6) - rr.SquareVal(&r) // rr = r^2 (mag: 1) - v.Mul2(&u1, &i) // V = U1*I (mag: 1) - x3.Set(&v).MulInt(2).Add(&j).Negate(3) // X3 = -(J+2*V) (mag: 4) - x3.Add(&rr) // X3 = r^2+X3 (mag: 5) - negX3.Set(x3).Negate(5) // negX3 = -X3 (mag: 6) - y3.Mul2(&s1, &j).MulInt(2).Negate(2) // Y3 = -(2*S1*J) (mag: 3) - y3.Add(v.Add(&negX3).Mul(&r)) // Y3 = r*(V-X3)+Y3 (mag: 4) - z3.Add2(z1, z2).Square() // Z3 = (Z1+Z2)^2 (mag: 1) - z3.Add(z1z1.Add(&z2z2).Negate(2)) // Z3 = Z3-(Z1Z1+Z2Z2) (mag: 4) - z3.Mul(&h) // Z3 = Z3*H (mag: 1) - - // Normalize the resulting field values to a magnitude of 1 as needed. - x3.Normalize() - y3.Normalize() -} - -// addJacobian adds the passed Jacobian points (x1, y1, z1) and (x2, y2, z2) -// together and stores the result in (x3, y3, z3). -func (curve *KoblitzCurve) addJacobian(x1, y1, z1, x2, y2, z2, x3, y3, z3 *fieldVal) { - // A point at infinity is the identity according to the group law for - // elliptic curve cryptography. Thus, ∞ + P = P and P + ∞ = P. - if (x1.IsZero() && y1.IsZero()) || z1.IsZero() { - x3.Set(x2) - y3.Set(y2) - z3.Set(z2) - return - } - if (x2.IsZero() && y2.IsZero()) || z2.IsZero() { - x3.Set(x1) - y3.Set(y1) - z3.Set(z1) - return - } - - // Faster point addition can be achieved when certain assumptions are - // met. For example, when both points have the same z value, arithmetic - // on the z values can be avoided. This section thus checks for these - // conditions and calls an appropriate add function which is accelerated - // by using those assumptions. - z1.Normalize() - z2.Normalize() - isZ1One := z1.Equals(fieldOne) - isZ2One := z2.Equals(fieldOne) - switch { - case isZ1One && isZ2One: - curve.addZ1AndZ2EqualsOne(x1, y1, z1, x2, y2, x3, y3, z3) - return - case z1.Equals(z2): - curve.addZ1EqualsZ2(x1, y1, z1, x2, y2, x3, y3, z3) - return - case isZ2One: - curve.addZ2EqualsOne(x1, y1, z1, x2, y2, x3, y3, z3) - return - } - - // None of the above assumptions are true, so fall back to generic - // point addition. - curve.addGeneric(x1, y1, z1, x2, y2, z2, x3, y3, z3) -} - -// Add returns the sum of (x1,y1) and (x2,y2). Part of the elliptic.Curve -// interface. -func (curve *KoblitzCurve) Add(x1, y1, x2, y2 *big.Int) (*big.Int, *big.Int) { - // A point at infinity is the identity according to the group law for - // elliptic curve cryptography. Thus, ∞ + P = P and P + ∞ = P. - if x1.Sign() == 0 && y1.Sign() == 0 { - return x2, y2 - } - if x2.Sign() == 0 && y2.Sign() == 0 { - return x1, y1 - } - - // Convert the affine coordinates from big integers to field values - // and do the point addition in Jacobian projective space. - fx1, fy1 := curve.bigAffineToField(x1, y1) - fx2, fy2 := curve.bigAffineToField(x2, y2) - fx3, fy3, fz3 := new(fieldVal), new(fieldVal), new(fieldVal) - fOne := new(fieldVal).SetInt(1) - curve.addJacobian(fx1, fy1, fOne, fx2, fy2, fOne, fx3, fy3, fz3) - - // Convert the Jacobian coordinate field values back to affine big - // integers. - return curve.fieldJacobianToBigAffine(fx3, fy3, fz3) -} - -// doubleZ1EqualsOne performs point doubling on the passed Jacobian point -// when the point is already known to have a z value of 1 and stores -// the result in (x3, y3, z3). That is to say (x3, y3, z3) = 2*(x1, y1, 1). It -// performs faster point doubling than the generic routine since less arithmetic -// is needed due to the ability to avoid multiplication by the z value. -func (curve *KoblitzCurve) doubleZ1EqualsOne(x1, y1, x3, y3, z3 *fieldVal) { - // This function uses the assumptions that z1 is 1, thus the point - // doubling formulas reduce to: - // - // X3 = (3*X1^2)^2 - 8*X1*Y1^2 - // Y3 = (3*X1^2)*(4*X1*Y1^2 - X3) - 8*Y1^4 - // Z3 = 2*Y1 - // - // To compute the above efficiently, this implementation splits the - // equation into intermediate elements which are used to minimize the - // number of field multiplications in favor of field squarings which - // are roughly 35% faster than field multiplications with the current - // implementation at the time this was written. - // - // This uses a slightly modified version of the method shown at: - // http://hyperelliptic.org/EFD/g1p/auto-shortw-jacobian-0.html#doubling-mdbl-2007-bl - // - // In particular it performs the calculations using the following: - // A = X1^2, B = Y1^2, C = B^2, D = 2*((X1+B)^2-A-C) - // E = 3*A, F = E^2, X3 = F-2*D, Y3 = E*(D-X3)-8*C - // Z3 = 2*Y1 - // - // This results in a cost of 1 field multiplication, 5 field squarings, - // 6 field additions, and 5 integer multiplications. - var a, b, c, d, e, f fieldVal - z3.Set(y1).MulInt(2) // Z3 = 2*Y1 (mag: 2) - a.SquareVal(x1) // A = X1^2 (mag: 1) - b.SquareVal(y1) // B = Y1^2 (mag: 1) - c.SquareVal(&b) // C = B^2 (mag: 1) - b.Add(x1).Square() // B = (X1+B)^2 (mag: 1) - d.Set(&a).Add(&c).Negate(2) // D = -(A+C) (mag: 3) - d.Add(&b).MulInt(2) // D = 2*(B+D)(mag: 8) - e.Set(&a).MulInt(3) // E = 3*A (mag: 3) - f.SquareVal(&e) // F = E^2 (mag: 1) - x3.Set(&d).MulInt(2).Negate(16) // X3 = -(2*D) (mag: 17) - x3.Add(&f) // X3 = F+X3 (mag: 18) - f.Set(x3).Negate(18).Add(&d).Normalize() // F = D-X3 (mag: 1) - y3.Set(&c).MulInt(8).Negate(8) // Y3 = -(8*C) (mag: 9) - y3.Add(f.Mul(&e)) // Y3 = E*F+Y3 (mag: 10) - - // Normalize the field values back to a magnitude of 1. - x3.Normalize() - y3.Normalize() - z3.Normalize() -} - -// doubleGeneric performs point doubling on the passed Jacobian point without -// any assumptions about the z value and stores the result in (x3, y3, z3). -// That is to say (x3, y3, z3) = 2*(x1, y1, z1). It is the slowest of the point -// doubling routines due to requiring the most arithmetic. -func (curve *KoblitzCurve) doubleGeneric(x1, y1, z1, x3, y3, z3 *fieldVal) { - // Point doubling formula for Jacobian coordinates for the secp256k1 - // curve: - // X3 = (3*X1^2)^2 - 8*X1*Y1^2 - // Y3 = (3*X1^2)*(4*X1*Y1^2 - X3) - 8*Y1^4 - // Z3 = 2*Y1*Z1 - // - // To compute the above efficiently, this implementation splits the - // equation into intermediate elements which are used to minimize the - // number of field multiplications in favor of field squarings which - // are roughly 35% faster than field multiplications with the current - // implementation at the time this was written. - // - // This uses a slightly modified version of the method shown at: - // http://hyperelliptic.org/EFD/g1p/auto-shortw-jacobian-0.html#doubling-dbl-2009-l - // - // In particular it performs the calculations using the following: - // A = X1^2, B = Y1^2, C = B^2, D = 2*((X1+B)^2-A-C) - // E = 3*A, F = E^2, X3 = F-2*D, Y3 = E*(D-X3)-8*C - // Z3 = 2*Y1*Z1 - // - // This results in a cost of 1 field multiplication, 5 field squarings, - // 6 field additions, and 5 integer multiplications. - var a, b, c, d, e, f fieldVal - z3.Mul2(y1, z1).MulInt(2) // Z3 = 2*Y1*Z1 (mag: 2) - a.SquareVal(x1) // A = X1^2 (mag: 1) - b.SquareVal(y1) // B = Y1^2 (mag: 1) - c.SquareVal(&b) // C = B^2 (mag: 1) - b.Add(x1).Square() // B = (X1+B)^2 (mag: 1) - d.Set(&a).Add(&c).Negate(2) // D = -(A+C) (mag: 3) - d.Add(&b).MulInt(2) // D = 2*(B+D)(mag: 8) - e.Set(&a).MulInt(3) // E = 3*A (mag: 3) - f.SquareVal(&e) // F = E^2 (mag: 1) - x3.Set(&d).MulInt(2).Negate(16) // X3 = -(2*D) (mag: 17) - x3.Add(&f) // X3 = F+X3 (mag: 18) - f.Set(x3).Negate(18).Add(&d).Normalize() // F = D-X3 (mag: 1) - y3.Set(&c).MulInt(8).Negate(8) // Y3 = -(8*C) (mag: 9) - y3.Add(f.Mul(&e)) // Y3 = E*F+Y3 (mag: 10) - - // Normalize the field values back to a magnitude of 1. - x3.Normalize() - y3.Normalize() - z3.Normalize() -} - -// doubleJacobian doubles the passed Jacobian point (x1, y1, z1) and stores the -// result in (x3, y3, z3). -func (curve *KoblitzCurve) doubleJacobian(x1, y1, z1, x3, y3, z3 *fieldVal) { - // Doubling a point at infinity is still infinity. - if y1.IsZero() || z1.IsZero() { - x3.SetInt(0) - y3.SetInt(0) - z3.SetInt(0) - return - } - - // Slightly faster point doubling can be achieved when the z value is 1 - // by avoiding the multiplication on the z value. This section calls - // a point doubling function which is accelerated by using that - // assumption when possible. - if z1.Normalize().Equals(fieldOne) { - curve.doubleZ1EqualsOne(x1, y1, x3, y3, z3) - return - } - - // Fall back to generic point doubling which works with arbitrary z - // values. - curve.doubleGeneric(x1, y1, z1, x3, y3, z3) -} - -// Double returns 2*(x1,y1). Part of the elliptic.Curve interface. -func (curve *KoblitzCurve) Double(x1, y1 *big.Int) (*big.Int, *big.Int) { - if y1.Sign() == 0 { - return new(big.Int), new(big.Int) - } - - // Convert the affine coordinates from big integers to field values - // and do the point doubling in Jacobian projective space. - fx1, fy1 := curve.bigAffineToField(x1, y1) - fx3, fy3, fz3 := new(fieldVal), new(fieldVal), new(fieldVal) - fOne := new(fieldVal).SetInt(1) - curve.doubleJacobian(fx1, fy1, fOne, fx3, fy3, fz3) - - // Convert the Jacobian coordinate field values back to affine big - // integers. - return curve.fieldJacobianToBigAffine(fx3, fy3, fz3) -} - -// splitK returns a balanced length-two representation of k and their signs. -// This is algorithm 3.74 from [GECC]. -// -// One thing of note about this algorithm is that no matter what c1 and c2 are, -// the final equation of k = k1 + k2 * lambda (mod n) will hold. This is -// provable mathematically due to how a1/b1/a2/b2 are computed. -// -// c1 and c2 are chosen to minimize the max(k1,k2). -func (curve *KoblitzCurve) splitK(k []byte) ([]byte, []byte, int, int) { - // All math here is done with big.Int, which is slow. - // At some point, it might be useful to write something similar to - // fieldVal but for N instead of P as the prime field if this ends up - // being a bottleneck. - bigIntK := new(big.Int) - c1, c2 := new(big.Int), new(big.Int) - tmp1, tmp2 := new(big.Int), new(big.Int) - k1, k2 := new(big.Int), new(big.Int) - - bigIntK.SetBytes(k) - // c1 = round(b2 * k / n) from step 4. - // Rounding isn't really necessary and costs too much, hence skipped - c1.Mul(curve.b2, bigIntK) - c1.Div(c1, curve.N) - // c2 = round(b1 * k / n) from step 4 (sign reversed to optimize one step) - // Rounding isn't really necessary and costs too much, hence skipped - c2.Mul(curve.b1, bigIntK) - c2.Div(c2, curve.N) - // k1 = k - c1 * a1 - c2 * a2 from step 5 (note c2's sign is reversed) - tmp1.Mul(c1, curve.a1) - tmp2.Mul(c2, curve.a2) - k1.Sub(bigIntK, tmp1) - k1.Add(k1, tmp2) - // k2 = - c1 * b1 - c2 * b2 from step 5 (note c2's sign is reversed) - tmp1.Mul(c1, curve.b1) - tmp2.Mul(c2, curve.b2) - k2.Sub(tmp2, tmp1) - - // Note Bytes() throws out the sign of k1 and k2. This matters - // since k1 and/or k2 can be negative. Hence, we pass that - // back separately. - return k1.Bytes(), k2.Bytes(), k1.Sign(), k2.Sign() -} - -// moduloReduce reduces k from more than 32 bytes to 32 bytes and under. This -// is done by doing a simple modulo curve.N. We can do this since G^N = 1 and -// thus any other valid point on the elliptic curve has the same order. -func (curve *KoblitzCurve) moduloReduce(k []byte) []byte { - // Since the order of G is curve.N, we can use a much smaller number - // by doing modulo curve.N - if len(k) > curve.byteSize { - // Reduce k by performing modulo curve.N. - tmpK := new(big.Int).SetBytes(k) - tmpK.Mod(tmpK, curve.N) - return tmpK.Bytes() - } - - return k -} - -// NAF takes a positive integer k and returns the Non-Adjacent Form (NAF) as two -// byte slices. The first is where 1s will be. The second is where -1s will -// be. NAF is convenient in that on average, only 1/3rd of its values are -// non-zero. This is algorithm 3.30 from [GECC]. -// -// Essentially, this makes it possible to minimize the number of operations -// since the resulting ints returned will be at least 50% 0s. -func NAF(k []byte) ([]byte, []byte) { - // The essence of this algorithm is that whenever we have consecutive 1s - // in the binary, we want to put a -1 in the lowest bit and get a bunch - // of 0s up to the highest bit of consecutive 1s. This is due to this - // identity: - // 2^n + 2^(n-1) + 2^(n-2) + ... + 2^(n-k) = 2^(n+1) - 2^(n-k) - // - // The algorithm thus may need to go 1 more bit than the length of the - // bits we actually have, hence bits being 1 bit longer than was - // necessary. Since we need to know whether adding will cause a carry, - // we go from right-to-left in this addition. - var carry, curIsOne, nextIsOne bool - // these default to zero - retPos := make([]byte, len(k)+1) - retNeg := make([]byte, len(k)+1) - for i := len(k) - 1; i >= 0; i-- { - curByte := k[i] - for j := uint(0); j < 8; j++ { - curIsOne = curByte&1 == 1 - if j == 7 { - if i == 0 { - nextIsOne = false - } else { - nextIsOne = k[i-1]&1 == 1 - } - } else { - nextIsOne = curByte&2 == 2 - } - if carry { - if curIsOne { - // This bit is 1, so continue to carry - // and don't need to do anything. - } else { - // We've hit a 0 after some number of - // 1s. - if nextIsOne { - // Start carrying again since - // a new sequence of 1s is - // starting. - retNeg[i+1] += 1 << j - } else { - // Stop carrying since 1s have - // stopped. - carry = false - retPos[i+1] += 1 << j - } - } - } else if curIsOne { - if nextIsOne { - // If this is the start of at least 2 - // consecutive 1s, set the current one - // to -1 and start carrying. - retNeg[i+1] += 1 << j - carry = true - } else { - // This is a singleton, not consecutive - // 1s. - retPos[i+1] += 1 << j - } - } - curByte >>= 1 - } - } - if carry { - retPos[0] = 1 - return retPos, retNeg - } - return retPos[1:], retNeg[1:] -} - -// ScalarMult returns k*(Bx, By) where k is a big endian integer. -// Part of the elliptic.Curve interface. -func (curve *KoblitzCurve) ScalarMult(Bx, By *big.Int, k []byte) (*big.Int, *big.Int) { - // Point Q = ∞ (point at infinity). - qx, qy, qz := new(fieldVal), new(fieldVal), new(fieldVal) - - // Decompose K into k1 and k2 in order to halve the number of EC ops. - // See Algorithm 3.74 in [GECC]. - k1, k2, signK1, signK2 := curve.splitK(curve.moduloReduce(k)) - - // The main equation here to remember is: - // k * P = k1 * P + k2 * ϕ(P) - // - // P1 below is P in the equation, P2 below is ϕ(P) in the equation - p1x, p1y := curve.bigAffineToField(Bx, By) - p1yNeg := new(fieldVal).NegateVal(p1y, 1) - p1z := new(fieldVal).SetInt(1) - - // NOTE: ϕ(x,y) = (βx,y). The Jacobian z coordinate is 1, so this math - // goes through. - p2x := new(fieldVal).Mul2(p1x, curve.beta) - p2y := new(fieldVal).Set(p1y) - p2yNeg := new(fieldVal).NegateVal(p2y, 1) - p2z := new(fieldVal).SetInt(1) - - // Flip the positive and negative values of the points as needed - // depending on the signs of k1 and k2. As mentioned in the equation - // above, each of k1 and k2 are multiplied by the respective point. - // Since -k * P is the same thing as k * -P, and the group law for - // elliptic curves states that P(x, y) = -P(x, -y), it's faster and - // simplifies the code to just make the point negative. - if signK1 == -1 { - p1y, p1yNeg = p1yNeg, p1y - } - if signK2 == -1 { - p2y, p2yNeg = p2yNeg, p2y - } - - // NAF versions of k1 and k2 should have a lot more zeros. - // - // The Pos version of the bytes contain the +1s and the Neg versions - // contain the -1s. - k1PosNAF, k1NegNAF := NAF(k1) - k2PosNAF, k2NegNAF := NAF(k2) - k1Len := len(k1PosNAF) - k2Len := len(k2PosNAF) - - m := k1Len - if m < k2Len { - m = k2Len - } - - // Add left-to-right using the NAF optimization. See algorithm 3.77 - // from [GECC]. This should be faster overall since there will be a lot - // more instances of 0, hence reducing the number of Jacobian additions - // at the cost of 1 possible extra doubling. - var k1BytePos, k1ByteNeg, k2BytePos, k2ByteNeg byte - for i := 0; i < m; i++ { - // Since we're going left-to-right, pad the front with 0s. - if i < m-k1Len { - k1BytePos = 0 - k1ByteNeg = 0 - } else { - k1BytePos = k1PosNAF[i-(m-k1Len)] - k1ByteNeg = k1NegNAF[i-(m-k1Len)] - } - if i < m-k2Len { - k2BytePos = 0 - k2ByteNeg = 0 - } else { - k2BytePos = k2PosNAF[i-(m-k2Len)] - k2ByteNeg = k2NegNAF[i-(m-k2Len)] - } - - for j := 7; j >= 0; j-- { - // Q = 2 * Q - curve.doubleJacobian(qx, qy, qz, qx, qy, qz) - - if k1BytePos&0x80 == 0x80 { - curve.addJacobian(qx, qy, qz, p1x, p1y, p1z, - qx, qy, qz) - } else if k1ByteNeg&0x80 == 0x80 { - curve.addJacobian(qx, qy, qz, p1x, p1yNeg, p1z, - qx, qy, qz) - } - - if k2BytePos&0x80 == 0x80 { - curve.addJacobian(qx, qy, qz, p2x, p2y, p2z, - qx, qy, qz) - } else if k2ByteNeg&0x80 == 0x80 { - curve.addJacobian(qx, qy, qz, p2x, p2yNeg, p2z, - qx, qy, qz) - } - k1BytePos <<= 1 - k1ByteNeg <<= 1 - k2BytePos <<= 1 - k2ByteNeg <<= 1 - } - } - - // Convert the Jacobian coordinate field values back to affine big.Ints. - return curve.fieldJacobianToBigAffine(qx, qy, qz) -} - -// ScalarBaseMult returns k*G where G is the base point of the group and k is a -// big endian integer. -// Part of the elliptic.Curve interface. -func (curve *KoblitzCurve) ScalarBaseMult(k []byte) (*big.Int, *big.Int) { - newK := curve.moduloReduce(k) - diff := len(curve.bytePoints) - len(newK) - - // Point Q = ∞ (point at infinity). - qx, qy, qz := new(fieldVal), new(fieldVal), new(fieldVal) - - // curve.bytePoints has all 256 byte points for each 8-bit window. The - // strategy is to add up the byte points. This is best understood by - // expressing k in base-256 which it already sort of is. - // Each "digit" in the 8-bit window can be looked up using bytePoints - // and added together. - for i, byteVal := range newK { - p := curve.bytePoints[diff+i][byteVal] - curve.addJacobian(qx, qy, qz, &p[0], &p[1], &p[2], qx, qy, qz) - } - return curve.fieldJacobianToBigAffine(qx, qy, qz) -} - -// QPlus1Div4 returns the (P+1)/4 constant for the curve for use in calculating -// square roots via exponentiation. -// -// DEPRECATED: The actual value returned is (P+1)/4, where as the original -// method name implies that this value is (((P+1)/4)+1)/4. This method is kept -// to maintain backwards compatibility of the API. Use Q() instead. -func (curve *KoblitzCurve) QPlus1Div4() *big.Int { - return curve.q -} - -// Q returns the (P+1)/4 constant for the curve for use in calculating square -// roots via exponentiation. -func (curve *KoblitzCurve) Q() *big.Int { - return curve.q -} - -var initonce sync.Once -var secp256k1 KoblitzCurve - -func initAll() { - initS256() -} - -// fromHex converts the passed hex string into a big integer pointer and will -// panic is there is an error. This is only provided for the hard-coded -// constants so errors in the source code can bet detected. It will only (and -// must only) be called for initialization purposes. -func fromHex(s string) *big.Int { - r, ok := new(big.Int).SetString(s, 16) - if !ok { - panic("invalid hex in source file: " + s) - } - return r -} - -func initS256() { - // Curve parameters taken from [SECG] section 2.4.1. - secp256k1.CurveParams = new(elliptic.CurveParams) - secp256k1.P = fromHex("FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFEFFFFFC2F") - secp256k1.N = fromHex("FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFEBAAEDCE6AF48A03BBFD25E8CD0364141") - secp256k1.B = fromHex("0000000000000000000000000000000000000000000000000000000000000007") - secp256k1.Gx = fromHex("79BE667EF9DCBBAC55A06295CE870B07029BFCDB2DCE28D959F2815B16F81798") - secp256k1.Gy = fromHex("483ADA7726A3C4655DA4FBFC0E1108A8FD17B448A68554199C47D08FFB10D4B8") - secp256k1.BitSize = 256 - // Curve name taken from https://safecurves.cr.yp.to/. - secp256k1.Name = "secp256k1" - secp256k1.q = new(big.Int).Div(new(big.Int).Add(secp256k1.P, - big.NewInt(1)), big.NewInt(4)) - secp256k1.H = 1 - secp256k1.halfOrder = new(big.Int).Rsh(secp256k1.N, 1) - secp256k1.fieldB = new(fieldVal).SetByteSlice(secp256k1.B.Bytes()) - - // Provided for convenience since this gets computed repeatedly. - secp256k1.byteSize = secp256k1.BitSize / 8 - - // Deserialize and set the pre-computed table used to accelerate scalar - // base multiplication. This is hard-coded data, so any errors are - // panics because it means something is wrong in the source code. - if err := loadS256BytePoints(); err != nil { - panic(err) - } - - // Next 6 constants are from Hal Finney's bitcointalk.org post: - // https://bitcointalk.org/index.php?topic=3238.msg45565#msg45565 - // May he rest in peace. - // - // They have also been independently derived from the code in the - // EndomorphismVectors function in gensecp256k1.go. - secp256k1.lambda = fromHex("5363AD4CC05C30E0A5261C028812645A122E22EA20816678DF02967C1B23BD72") - secp256k1.beta = new(fieldVal).SetHex("7AE96A2B657C07106E64479EAC3434E99CF0497512F58995C1396C28719501EE") - secp256k1.a1 = fromHex("3086D221A7D46BCDE86C90E49284EB15") - secp256k1.b1 = fromHex("-E4437ED6010E88286F547FA90ABFE4C3") - secp256k1.a2 = fromHex("114CA50F7A8E2F3F657C1108D9D44CFD8") - secp256k1.b2 = fromHex("3086D221A7D46BCDE86C90E49284EB15") - - // Alternatively, we can use the parameters below, however, they seem - // to be about 8% slower. - // secp256k1.lambda = fromHex("AC9C52B33FA3CF1F5AD9E3FD77ED9BA4A880B9FC8EC739C2E0CFC810B51283CE") - // secp256k1.beta = new(fieldVal).SetHex("851695D49A83F8EF919BB86153CBCB16630FB68AED0A766A3EC693D68E6AFA40") - // secp256k1.a1 = fromHex("E4437ED6010E88286F547FA90ABFE4C3") - // secp256k1.b1 = fromHex("-3086D221A7D46BCDE86C90E49284EB15") - // secp256k1.a2 = fromHex("3086D221A7D46BCDE86C90E49284EB15") - // secp256k1.b2 = fromHex("114CA50F7A8E2F3F657C1108D9D44CFD8") -} +// KoblitzCurve provides an implementation for secp256k1 that fits the ECC +// Curve interface from crypto/elliptic. +type KoblitzCurve = secp.KoblitzCurve // S256 returns a Curve which implements secp256k1. func S256() *KoblitzCurve { - initonce.Do(initAll) - return &secp256k1 + return secp.S256() +} + +// CurveParams contains the parameters for the secp256k1 curve. +type CurveParams = secp.CurveParams + +// Params returns the secp256k1 curve parameters for convenience. +func Params() *CurveParams { + return secp.Params() } diff --git a/btcec/btcec_test.go b/btcec/btcec_test.go index 42a69037..5fdd638f 100644 --- a/btcec/btcec_test.go +++ b/btcec/btcec_test.go @@ -15,17 +15,17 @@ import ( // isJacobianOnS256Curve returns boolean if the point (x,y,z) is on the // secp256k1 curve. -func isJacobianOnS256Curve(x, y, z *fieldVal) bool { +func isJacobianOnS256Curve(point *JacobianPoint) bool { // Elliptic curve equation for secp256k1 is: y^2 = x^3 + 7 // In Jacobian coordinates, Y = y/z^3 and X = x/z^2 // Thus: // (y/z^3)^2 = (x/z^2)^3 + 7 // y^2/z^6 = x^3/z^6 + 7 // y^2 = x^3 + 7*z^6 - var y2, z2, x3, result fieldVal - y2.SquareVal(y).Normalize() - z2.SquareVal(z) - x3.SquareVal(x).Mul(x) + var y2, z2, x3, result FieldVal + y2.SquareVal(&point.Y).Normalize() + z2.SquareVal(&point.Z) + x3.SquareVal(&point.X).Mul(&point.X) result.SquareVal(&z2).Mul(&z2).MulInt(7).Add(&x3).Normalize() return y2.Equals(&result) } @@ -222,43 +222,37 @@ func TestAddJacobian(t *testing.T) { t.Logf("Running %d tests", len(tests)) for i, test := range tests { - // Convert hex to field values. - x1 := new(fieldVal).SetHex(test.x1) - y1 := new(fieldVal).SetHex(test.y1) - z1 := new(fieldVal).SetHex(test.z1) - x2 := new(fieldVal).SetHex(test.x2) - y2 := new(fieldVal).SetHex(test.y2) - z2 := new(fieldVal).SetHex(test.z2) - x3 := new(fieldVal).SetHex(test.x3) - y3 := new(fieldVal).SetHex(test.y3) - z3 := new(fieldVal).SetHex(test.z3) + // Convert hex to Jacobian points. + p1 := jacobianPointFromHex(test.x1, test.y1, test.z1) + p2 := jacobianPointFromHex(test.x2, test.y2, test.z2) + want := jacobianPointFromHex(test.x3, test.y3, test.z3) // Ensure the test data is using points that are actually on // the curve (or the point at infinity). - if !z1.IsZero() && !isJacobianOnS256Curve(x1, y1, z1) { + if !p1.Z.IsZero() && !isJacobianOnS256Curve(&p1) { t.Errorf("#%d first point is not on the curve -- "+ "invalid test data", i) continue } - if !z2.IsZero() && !isJacobianOnS256Curve(x2, y2, z2) { + if !p2.Z.IsZero() && !isJacobianOnS256Curve(&p2) { t.Errorf("#%d second point is not on the curve -- "+ "invalid test data", i) continue } - if !z3.IsZero() && !isJacobianOnS256Curve(x3, y3, z3) { + if !want.Z.IsZero() && !isJacobianOnS256Curve(&want) { t.Errorf("#%d expected point is not on the curve -- "+ "invalid test data", i) continue } // Add the two points. - rx, ry, rz := new(fieldVal), new(fieldVal), new(fieldVal) - S256().addJacobian(x1, y1, z1, x2, y2, z2, rx, ry, rz) + var r JacobianPoint + AddNonConst(&p1, &p2, &r) // Ensure result matches expected. - if !rx.Equals(x3) || !ry.Equals(y3) || !rz.Equals(z3) { + if !r.X.Equals(&want.X) || !r.Y.Equals(&want.Y) || !r.Z.Equals(&want.Z) { t.Errorf("#%d wrong result\ngot: (%v, %v, %v)\n"+ - "want: (%v, %v, %v)", i, rx, ry, rz, x3, y3, z3) + "want: (%v, %v, %v)", i, r.X, r.Y, r.Z, want.X, want.Y, want.Z) continue } } @@ -360,6 +354,15 @@ func TestAddAffine(t *testing.T) { } } +// isStrictlyEqual returns whether or not the two Jacobian points are strictly +// equal for use in the tests. Recall that several Jacobian points can be +// equal in affine coordinates, while not having the same coordinates in +// projective space, so the two points not being equal doesn't necessarily mean +// they aren't actually the same affine point. +func isStrictlyEqual(p, other *JacobianPoint) bool { + return p.X.Equals(&other.X) && p.Y.Equals(&other.Y) && p.Z.Equals(&other.Z) +} + // TestDoubleJacobian tests doubling of points projected in Jacobian // coordinates. func TestDoubleJacobian(t *testing.T) { @@ -408,34 +411,31 @@ func TestDoubleJacobian(t *testing.T) { t.Logf("Running %d tests", len(tests)) for i, test := range tests { // Convert hex to field values. - x1 := new(fieldVal).SetHex(test.x1) - y1 := new(fieldVal).SetHex(test.y1) - z1 := new(fieldVal).SetHex(test.z1) - x3 := new(fieldVal).SetHex(test.x3) - y3 := new(fieldVal).SetHex(test.y3) - z3 := new(fieldVal).SetHex(test.z3) + p1 := jacobianPointFromHex(test.x1, test.y1, test.z1) + want := jacobianPointFromHex(test.x3, test.y3, test.z3) // Ensure the test data is using points that are actually on // the curve (or the point at infinity). - if !z1.IsZero() && !isJacobianOnS256Curve(x1, y1, z1) { + if !p1.Z.IsZero() && !isJacobianOnS256Curve(&p1) { t.Errorf("#%d first point is not on the curve -- "+ "invalid test data", i) continue } - if !z3.IsZero() && !isJacobianOnS256Curve(x3, y3, z3) { + if !want.Z.IsZero() && !isJacobianOnS256Curve(&want) { t.Errorf("#%d expected point is not on the curve -- "+ "invalid test data", i) continue } // Double the point. - rx, ry, rz := new(fieldVal), new(fieldVal), new(fieldVal) - S256().doubleJacobian(x1, y1, z1, rx, ry, rz) + var result JacobianPoint + DoubleNonConst(&p1, &result) // Ensure result matches expected. - if !rx.Equals(x3) || !ry.Equals(y3) || !rz.Equals(z3) { + if !isStrictlyEqual(&result, &want) { t.Errorf("#%d wrong result\ngot: (%v, %v, %v)\n"+ - "want: (%v, %v, %v)", i, rx, ry, rz, x3, y3, z3) + "want: (%v, %v, %v)", i, result.X, result.Y, result.Z, + want.X, want.Y, want.Z) continue } } @@ -663,6 +663,64 @@ func TestScalarMultRand(t *testing.T) { } } +var ( + // Next 6 constants are from Hal Finney's bitcointalk.org post: + // https://bitcointalk.org/index.php?topic=3238.msg45565#msg45565 + // May he rest in peace. + // + // They have also been independently derived from the code in the + // EndomorphismVectors function in genstatics.go. + endomorphismLambda = fromHex("5363ad4cc05c30e0a5261c028812645a122e22ea20816678df02967c1b23bd72") + endomorphismBeta = hexToFieldVal("7ae96a2b657c07106e64479eac3434e99cf0497512f58995c1396c28719501ee") + endomorphismA1 = fromHex("3086d221a7d46bcde86c90e49284eb15") + endomorphismB1 = fromHex("-e4437ed6010e88286f547fa90abfe4c3") + endomorphismA2 = fromHex("114ca50f7a8e2f3f657c1108d9d44cfd8") + endomorphismB2 = fromHex("3086d221a7d46bcde86c90e49284eb15") +) + +// splitK returns a balanced length-two representation of k and their signs. +// This is algorithm 3.74 from [GECC]. +// +// One thing of note about this algorithm is that no matter what c1 and c2 are, +// the final equation of k = k1 + k2 * lambda (mod n) will hold. This is +// provable mathematically due to how a1/b1/a2/b2 are computed. +// +// c1 and c2 are chosen to minimize the max(k1,k2). +func splitK(k []byte) ([]byte, []byte, int, int) { + // All math here is done with big.Int, which is slow. + // At some point, it might be useful to write something similar to + // FieldVal but for N instead of P as the prime field if this ends up + // being a bottleneck. + bigIntK := new(big.Int) + c1, c2 := new(big.Int), new(big.Int) + tmp1, tmp2 := new(big.Int), new(big.Int) + k1, k2 := new(big.Int), new(big.Int) + + bigIntK.SetBytes(k) + // c1 = round(b2 * k / n) from step 4. + // Rounding isn't really necessary and costs too much, hence skipped + c1.Mul(endomorphismB2, bigIntK) + c1.Div(c1, Params().N) + // c2 = round(b1 * k / n) from step 4 (sign reversed to optimize one step) + // Rounding isn't really necessary and costs too much, hence skipped + c2.Mul(endomorphismB1, bigIntK) + c2.Div(c2, Params().N) + // k1 = k - c1 * a1 - c2 * a2 from step 5 (note c2's sign is reversed) + tmp1.Mul(c1, endomorphismA1) + tmp2.Mul(c2, endomorphismA2) + k1.Sub(bigIntK, tmp1) + k1.Add(k1, tmp2) + // k2 = - c1 * b1 - c2 * b2 from step 5 (note c2's sign is reversed) + tmp1.Mul(c1, endomorphismB1) + tmp2.Mul(c2, endomorphismB2) + k2.Sub(tmp2, tmp1) + + // Note Bytes() throws out the sign of k1 and k2. This matters + // since k1 and/or k2 can be negative. Hence, we pass that + // back separately. + return k1.Bytes(), k2.Bytes(), k1.Sign(), k2.Sign() +} + func TestSplitK(t *testing.T) { tests := []struct { k string @@ -719,7 +777,7 @@ func TestSplitK(t *testing.T) { if !ok { t.Errorf("%d: bad value for k: %s", i, test.k) } - k1, k2, k1Sign, k2Sign := s256.splitK(k.Bytes()) + k1, k2, k1Sign, k2Sign := splitK(k.Bytes()) k1str := fmt.Sprintf("%064x", k1) if test.k1 != k1str { t.Errorf("%d: bad k1: got %v, want %v", i, k1str, test.k1) @@ -740,7 +798,7 @@ func TestSplitK(t *testing.T) { k2Int := new(big.Int).SetBytes(k2) k2SignInt := new(big.Int).SetInt64(int64(k2Sign)) k2Int.Mul(k2Int, k2SignInt) - gotK := new(big.Int).Mul(k2Int, s256.lambda) + gotK := new(big.Int).Mul(k2Int, endomorphismLambda) gotK.Add(k1Int, gotK) gotK.Mod(gotK, s256.N) if k.Cmp(gotK) != 0 { @@ -759,14 +817,14 @@ func TestSplitKRand(t *testing.T) { break } k := new(big.Int).SetBytes(bytesK) - k1, k2, k1Sign, k2Sign := s256.splitK(bytesK) + k1, k2, k1Sign, k2Sign := splitK(bytesK) k1Int := new(big.Int).SetBytes(k1) k1SignInt := new(big.Int).SetInt64(int64(k1Sign)) k1Int.Mul(k1Int, k1SignInt) k2Int := new(big.Int).SetBytes(k2) k2SignInt := new(big.Int).SetInt64(int64(k2Sign)) k2Int.Mul(k2Int, k2SignInt) - gotK := new(big.Int).Mul(k2Int, s256.lambda) + gotK := new(big.Int).Mul(k2Int, endomorphismLambda) gotK.Add(k1Int, gotK) gotK.Mod(gotK, s256.N) if k.Cmp(gotK) != 0 { @@ -778,12 +836,13 @@ func TestSplitKRand(t *testing.T) { // Test this curve's usage with the ecdsa package. func testKeyGeneration(t *testing.T, c *KoblitzCurve, tag string) { - priv, err := NewPrivateKey(c) + priv, err := NewPrivateKey() if err != nil { t.Errorf("%s: error: %s", tag, err) return } - if !c.IsOnCurve(priv.PublicKey.X, priv.PublicKey.Y) { + pub := priv.PubKey() + if !c.IsOnCurve(pub.X(), pub.Y()) { t.Errorf("%s: public key invalid: %s", tag, err) } } @@ -793,15 +852,11 @@ func TestKeyGeneration(t *testing.T) { } func testSignAndVerify(t *testing.T, c *KoblitzCurve, tag string) { - priv, _ := NewPrivateKey(c) + priv, _ := NewPrivateKey() pub := priv.PubKey() hashed := []byte("testing") - sig, err := priv.Sign(hashed) - if err != nil { - t.Errorf("%s: error signing: %s", tag, err) - return - } + sig := Sign(priv, hashed) if !sig.Verify(hashed, pub) { t.Errorf("%s: Verify failed", tag) @@ -817,73 +872,41 @@ func TestSignAndVerify(t *testing.T) { testSignAndVerify(t, S256(), "S256") } -func TestNAF(t *testing.T) { - tests := []string{ - "6df2b5d30854069ccdec40ae022f5c948936324a4e9ebed8eb82cfd5a6b6d766", - "b776e53fb55f6b006a270d42d64ec2b1", - "d6cc32c857f1174b604eefc544f0c7f7", - "45c53aa1bb56fcd68c011e2dad6758e4", - "a2e79d200f27f2360fba57619936159b", +// checkNAFEncoding returns an error if the provided positive and negative +// portions of an overall NAF encoding do not adhere to the requirements or they +// do not sum back to the provided original value. +func checkNAFEncoding(pos, neg []byte, origValue *big.Int) error { + // NAF must not have a leading zero byte and the number of negative + // bytes must not exceed the positive portion. + if len(pos) > 0 && pos[0] == 0 { + return fmt.Errorf("positive has leading zero -- got %x", pos) } - negOne := big.NewInt(-1) - one := big.NewInt(1) - two := big.NewInt(2) - for i, test := range tests { - want, _ := new(big.Int).SetString(test, 16) - nafPos, nafNeg := NAF(want.Bytes()) - got := big.NewInt(0) - // Check that the NAF representation comes up with the right number - for i := 0; i < len(nafPos); i++ { - bytePos := nafPos[i] - byteNeg := nafNeg[i] - for j := 7; j >= 0; j-- { - got.Mul(got, two) - if bytePos&0x80 == 0x80 { - got.Add(got, one) - } else if byteNeg&0x80 == 0x80 { - got.Add(got, negOne) - } - bytePos <<= 1 - byteNeg <<= 1 - } - } - if got.Cmp(want) != 0 { - t.Errorf("%d: Failed NAF got %X want %X", i, got, want) - } + if len(neg) > len(pos) { + return fmt.Errorf("negative has len %d > pos len %d", len(neg), + len(pos)) } -} -func TestNAFRand(t *testing.T) { - negOne := big.NewInt(-1) - one := big.NewInt(1) - two := big.NewInt(2) - for i := 0; i < 1024; i++ { - data := make([]byte, 32) - _, err := rand.Read(data) - if err != nil { - t.Fatalf("failed to read random data at %d", i) - break - } - nafPos, nafNeg := NAF(data) - want := new(big.Int).SetBytes(data) - got := big.NewInt(0) - // Check that the NAF representation comes up with the right number - for i := 0; i < len(nafPos); i++ { - bytePos := nafPos[i] - byteNeg := nafNeg[i] - for j := 7; j >= 0; j-- { - got.Mul(got, two) - if bytePos&0x80 == 0x80 { - got.Add(got, one) - } else if byteNeg&0x80 == 0x80 { - got.Add(got, negOne) - } - bytePos <<= 1 - byteNeg <<= 1 - } - } - if got.Cmp(want) != 0 { - t.Errorf("%d: Failed NAF got %X want %X", i, got, want) + // Ensure the result doesn't have any adjacent non-zero digits. + gotPos := new(big.Int).SetBytes(pos) + gotNeg := new(big.Int).SetBytes(neg) + posOrNeg := new(big.Int).Or(gotPos, gotNeg) + prevBit := posOrNeg.Bit(0) + for bit := 1; bit < posOrNeg.BitLen(); bit++ { + thisBit := posOrNeg.Bit(bit) + if prevBit == 1 && thisBit == 1 { + return fmt.Errorf("adjacent non-zero digits found at bit pos %d", + bit-1) } + prevBit = thisBit } + + // Ensure the resulting positive and negative portions of the overall + // NAF representation sum back to the original value. + gotValue := new(big.Int).Sub(gotPos, gotNeg) + if origValue.Cmp(gotValue) != 0 { + return fmt.Errorf("pos-neg is not original value: got %x, want %x", + gotValue, origValue) + } + + return nil } diff --git a/btcec/ciphering.go b/btcec/ciphering.go index b18c9b7a..88d93e27 100644 --- a/btcec/ciphering.go +++ b/btcec/ciphering.go @@ -5,212 +5,12 @@ package btcec import ( - "bytes" - "crypto/aes" - "crypto/cipher" - "crypto/hmac" - "crypto/rand" - "crypto/sha256" - "crypto/sha512" - "errors" - "io" -) - -var ( - // ErrInvalidMAC occurs when Message Authentication Check (MAC) fails - // during decryption. This happens because of either invalid private key or - // corrupt ciphertext. - ErrInvalidMAC = errors.New("invalid mac hash") - - // errInputTooShort occurs when the input ciphertext to the Decrypt - // function is less than 134 bytes long. - errInputTooShort = errors.New("ciphertext too short") - - // errUnsupportedCurve occurs when the first two bytes of the encrypted - // text aren't 0x02CA (= 712 = secp256k1, from OpenSSL). - errUnsupportedCurve = errors.New("unsupported curve") - - errInvalidXLength = errors.New("invalid X length, must be 32") - errInvalidYLength = errors.New("invalid Y length, must be 32") - errInvalidPadding = errors.New("invalid PKCS#7 padding") - - // 0x02CA = 714 - ciphCurveBytes = [2]byte{0x02, 0xCA} - // 0x20 = 32 - ciphCoordLength = [2]byte{0x00, 0x20} + secp "github.com/decred/dcrd/dcrec/secp256k1/v4" ) // GenerateSharedSecret generates a shared secret based on a private key and a // public key using Diffie-Hellman key exchange (ECDH) (RFC 4753). // RFC5903 Section 9 states we should only return x. func GenerateSharedSecret(privkey *PrivateKey, pubkey *PublicKey) []byte { - x, _ := pubkey.Curve.ScalarMult(pubkey.X, pubkey.Y, privkey.D.Bytes()) - return x.Bytes() -} - -// Encrypt encrypts data for the target public key using AES-256-CBC. It also -// generates a private key (the pubkey of which is also in the output). The only -// supported curve is secp256k1. The `structure' that it encodes everything into -// is: -// -// struct { -// // Initialization Vector used for AES-256-CBC -// IV [16]byte -// // Public Key: curve(2) + len_of_pubkeyX(2) + pubkeyX + -// // len_of_pubkeyY(2) + pubkeyY (curve = 714) -// PublicKey [70]byte -// // Cipher text -// Data []byte -// // HMAC-SHA-256 Message Authentication Code -// HMAC [32]byte -// } -// -// The primary aim is to ensure byte compatibility with Pyelliptic. Also, refer -// to section 5.8.1 of ANSI X9.63 for rationale on this format. -func Encrypt(pubkey *PublicKey, in []byte) ([]byte, error) { - ephemeral, err := NewPrivateKey(S256()) - if err != nil { - return nil, err - } - ecdhKey := GenerateSharedSecret(ephemeral, pubkey) - derivedKey := sha512.Sum512(ecdhKey) - keyE := derivedKey[:32] - keyM := derivedKey[32:] - - paddedIn := addPKCSPadding(in) - // IV + Curve params/X/Y + padded plaintext/ciphertext + HMAC-256 - out := make([]byte, aes.BlockSize+70+len(paddedIn)+sha256.Size) - iv := out[:aes.BlockSize] - if _, err = io.ReadFull(rand.Reader, iv); err != nil { - return nil, err - } - // start writing public key - pb := ephemeral.PubKey().SerializeUncompressed() - offset := aes.BlockSize - - // curve and X length - copy(out[offset:offset+4], append(ciphCurveBytes[:], ciphCoordLength[:]...)) - offset += 4 - // X - copy(out[offset:offset+32], pb[1:33]) - offset += 32 - // Y length - copy(out[offset:offset+2], ciphCoordLength[:]) - offset += 2 - // Y - copy(out[offset:offset+32], pb[33:]) - offset += 32 - - // start encryption - block, err := aes.NewCipher(keyE) - if err != nil { - return nil, err - } - mode := cipher.NewCBCEncrypter(block, iv) - mode.CryptBlocks(out[offset:len(out)-sha256.Size], paddedIn) - - // start HMAC-SHA-256 - hm := hmac.New(sha256.New, keyM) - hm.Write(out[:len(out)-sha256.Size]) // everything is hashed - copy(out[len(out)-sha256.Size:], hm.Sum(nil)) // write checksum - - return out, nil -} - -// Decrypt decrypts data that was encrypted using the Encrypt function. -func Decrypt(priv *PrivateKey, in []byte) ([]byte, error) { - // IV + Curve params/X/Y + 1 block + HMAC-256 - if len(in) < aes.BlockSize+70+aes.BlockSize+sha256.Size { - return nil, errInputTooShort - } - - // read iv - iv := in[:aes.BlockSize] - offset := aes.BlockSize - - // start reading pubkey - if !bytes.Equal(in[offset:offset+2], ciphCurveBytes[:]) { - return nil, errUnsupportedCurve - } - offset += 2 - - if !bytes.Equal(in[offset:offset+2], ciphCoordLength[:]) { - return nil, errInvalidXLength - } - offset += 2 - - xBytes := in[offset : offset+32] - offset += 32 - - if !bytes.Equal(in[offset:offset+2], ciphCoordLength[:]) { - return nil, errInvalidYLength - } - offset += 2 - - yBytes := in[offset : offset+32] - offset += 32 - - pb := make([]byte, 65) - pb[0] = byte(0x04) // uncompressed - copy(pb[1:33], xBytes) - copy(pb[33:], yBytes) - // check if (X, Y) lies on the curve and create a Pubkey if it does - pubkey, err := ParsePubKey(pb, S256()) - if err != nil { - return nil, err - } - - // check for cipher text length - if (len(in)-aes.BlockSize-offset-sha256.Size)%aes.BlockSize != 0 { - return nil, errInvalidPadding // not padded to 16 bytes - } - - // read hmac - messageMAC := in[len(in)-sha256.Size:] - - // generate shared secret - ecdhKey := GenerateSharedSecret(priv, pubkey) - derivedKey := sha512.Sum512(ecdhKey) - keyE := derivedKey[:32] - keyM := derivedKey[32:] - - // verify mac - hm := hmac.New(sha256.New, keyM) - hm.Write(in[:len(in)-sha256.Size]) // everything is hashed - expectedMAC := hm.Sum(nil) - if !hmac.Equal(messageMAC, expectedMAC) { - return nil, ErrInvalidMAC - } - - // start decryption - block, err := aes.NewCipher(keyE) - if err != nil { - return nil, err - } - mode := cipher.NewCBCDecrypter(block, iv) - // same length as ciphertext - plaintext := make([]byte, len(in)-offset-sha256.Size) - mode.CryptBlocks(plaintext, in[offset:len(in)-sha256.Size]) - - return removePKCSPadding(plaintext) -} - -// Implement PKCS#7 padding with block size of 16 (AES block size). - -// addPKCSPadding adds padding to a block of data -func addPKCSPadding(src []byte) []byte { - padding := aes.BlockSize - len(src)%aes.BlockSize - padtext := bytes.Repeat([]byte{byte(padding)}, padding) - return append(src, padtext...) -} - -// removePKCSPadding removes padding from data that was added with addPKCSPadding -func removePKCSPadding(src []byte) ([]byte, error) { - length := len(src) - padLength := int(src[length-1]) - if padLength > aes.BlockSize || length < aes.BlockSize { - return nil, errInvalidPadding - } - - return src[:length-padLength], nil + return secp.GenerateSharedSecret(privkey, pubkey) } diff --git a/btcec/ciphering_test.go b/btcec/ciphering_test.go index 819f1884..c6bea3da 100644 --- a/btcec/ciphering_test.go +++ b/btcec/ciphering_test.go @@ -6,17 +6,16 @@ package btcec import ( "bytes" - "encoding/hex" "testing" ) func TestGenerateSharedSecret(t *testing.T) { - privKey1, err := NewPrivateKey(S256()) + privKey1, err := NewPrivateKey() if err != nil { t.Errorf("private key generation error: %s", err) return } - privKey2, err := NewPrivateKey(S256()) + privKey2, err := NewPrivateKey() if err != nil { t.Errorf("private key generation error: %s", err) return @@ -30,145 +29,3 @@ func TestGenerateSharedSecret(t *testing.T) { secret1, secret2) } } - -// Test 1: Encryption and decryption -func TestCipheringBasic(t *testing.T) { - privkey, err := NewPrivateKey(S256()) - if err != nil { - t.Fatal("failed to generate private key") - } - - in := []byte("Hey there dude. How are you doing? This is a test.") - - out, err := Encrypt(privkey.PubKey(), in) - if err != nil { - t.Fatal("failed to encrypt:", err) - } - - dec, err := Decrypt(privkey, out) - if err != nil { - t.Fatal("failed to decrypt:", err) - } - - if !bytes.Equal(in, dec) { - t.Error("decrypted data doesn't match original") - } -} - -// Test 2: Byte compatibility with Pyelliptic -func TestCiphering(t *testing.T) { - pb, _ := hex.DecodeString("fe38240982f313ae5afb3e904fb8215fb11af1200592b" + - "fca26c96c4738e4bf8f") - privkey, _ := PrivKeyFromBytes(S256(), pb) - - in := []byte("This is just a test.") - out, _ := hex.DecodeString("b0d66e5adaa5ed4e2f0ca68e17b8f2fc02ca002009e3" + - "3487e7fa4ab505cf34d98f131be7bd258391588ca7804acb30251e71a04e0020ecf" + - "df0f84608f8add82d7353af780fbb28868c713b7813eb4d4e61f7b75d7534dd9856" + - "9b0ba77cf14348fcff80fee10e11981f1b4be372d93923e9178972f69937ec850ed" + - "6c3f11ff572ddd5b2bedf9f9c0b327c54da02a28fcdce1f8369ffec") - - dec, err := Decrypt(privkey, out) - if err != nil { - t.Fatal("failed to decrypt:", err) - } - - if !bytes.Equal(in, dec) { - t.Error("decrypted data doesn't match original") - } -} - -func TestCipheringErrors(t *testing.T) { - privkey, err := NewPrivateKey(S256()) - if err != nil { - t.Fatal("failed to generate private key") - } - - tests1 := []struct { - ciphertext []byte // input ciphertext - }{ - {bytes.Repeat([]byte{0x00}, 133)}, // errInputTooShort - {bytes.Repeat([]byte{0x00}, 134)}, // errUnsupportedCurve - {bytes.Repeat([]byte{0x02, 0xCA}, 134)}, // errInvalidXLength - {bytes.Repeat([]byte{0x02, 0xCA, 0x00, 0x20}, 134)}, // errInvalidYLength - {[]byte{0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, // IV - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x02, 0xCA, 0x00, 0x20, // curve and X length - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, // X - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x20, // Y length - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, // Y - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, // ciphertext - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, // MAC - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - }}, // invalid pubkey - {[]byte{0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, // IV - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x02, 0xCA, 0x00, 0x20, // curve and X length - 0x11, 0x5C, 0x42, 0xE7, 0x57, 0xB2, 0xEF, 0xB7, // X - 0x67, 0x1C, 0x57, 0x85, 0x30, 0xEC, 0x19, 0x1A, - 0x13, 0x59, 0x38, 0x1E, 0x6A, 0x71, 0x12, 0x7A, - 0x9D, 0x37, 0xC4, 0x86, 0xFD, 0x30, 0xDA, 0xE5, - 0x00, 0x20, // Y length - 0x7E, 0x76, 0xDC, 0x58, 0xF6, 0x93, 0xBD, 0x7E, // Y - 0x70, 0x10, 0x35, 0x8C, 0xE6, 0xB1, 0x65, 0xE4, - 0x83, 0xA2, 0x92, 0x10, 0x10, 0xDB, 0x67, 0xAC, - 0x11, 0xB1, 0xB5, 0x1B, 0x65, 0x19, 0x53, 0xD2, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, // ciphertext - // padding not aligned to 16 bytes - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, // MAC - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - }}, // errInvalidPadding - {[]byte{0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, // IV - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x02, 0xCA, 0x00, 0x20, // curve and X length - 0x11, 0x5C, 0x42, 0xE7, 0x57, 0xB2, 0xEF, 0xB7, // X - 0x67, 0x1C, 0x57, 0x85, 0x30, 0xEC, 0x19, 0x1A, - 0x13, 0x59, 0x38, 0x1E, 0x6A, 0x71, 0x12, 0x7A, - 0x9D, 0x37, 0xC4, 0x86, 0xFD, 0x30, 0xDA, 0xE5, - 0x00, 0x20, // Y length - 0x7E, 0x76, 0xDC, 0x58, 0xF6, 0x93, 0xBD, 0x7E, // Y - 0x70, 0x10, 0x35, 0x8C, 0xE6, 0xB1, 0x65, 0xE4, - 0x83, 0xA2, 0x92, 0x10, 0x10, 0xDB, 0x67, 0xAC, - 0x11, 0xB1, 0xB5, 0x1B, 0x65, 0x19, 0x53, 0xD2, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, // ciphertext - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, // MAC - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, - }}, // ErrInvalidMAC - } - - for i, test := range tests1 { - _, err = Decrypt(privkey, test.ciphertext) - if err == nil { - t.Errorf("Decrypt #%d did not get error", i) - } - } - - // test error from removePKCSPadding - tests2 := []struct { - in []byte // input data - }{ - {bytes.Repeat([]byte{0x11}, 17)}, - {bytes.Repeat([]byte{0x07}, 15)}, - } - for i, test := range tests2 { - _, err = removePKCSPadding(test.in) - if err == nil { - t.Errorf("removePKCSPadding #%d did not get error", i) - } - } -} diff --git a/btcec/curve.go b/btcec/curve.go new file mode 100644 index 00000000..b86c5913 --- /dev/null +++ b/btcec/curve.go @@ -0,0 +1,60 @@ +package btcec + +import ( + secp "github.com/decred/dcrd/dcrec/secp256k1/v4" +) + +// JacobianPoint is an element of the group formed by the secp256k1 curve in +// Jacobian projective coordinates and thus represents a point on the curve. +type JacobianPoint = secp.JacobianPoint + +// MakeJacobianPoint returns a Jacobian point with the provided X, Y, and Z +// coordinates. +func MakeJacobianPoint(x, y, z *FieldVal) JacobianPoint { + return secp.MakeJacobianPoint(x, y, z) +} + +// AddNonConst adds the passed Jacobian points together and stores the result +// in the provided result param in *non-constant* time. +func AddNonConst(p1, p2, result *JacobianPoint) { + secp.AddNonConst(p1, p2, result) +} + +// DecompressY attempts to calculate the Y coordinate for the given X +// coordinate such that the result pair is a point on the secp256k1 curve. It +// adjusts Y based on the desired oddness and returns whether or not it was +// successful since not all X coordinates are valid. +// +// The magnitude of the provided X coordinate field val must be a max of 8 for +// a correct result. The resulting Y field val will have a max magnitude of 2. +func DecompressY(x *FieldVal, odd bool, resultY *FieldVal) bool { + return secp.DecompressY(x, odd, resultY) +} + +// DoubleNonConst doubles the passed Jacobian point and stores the result in +// the provided result parameter in *non-constant* time. +// +// NOTE: The point must be normalized for this function to return the correct +// result. The resulting point will be normalized. +func DoubleNonConst(p, result *JacobianPoint) { + secp.DoubleNonConst(p, result) +} + +// ScalarBaseMultNonConst multiplies k*G where G is the base point of the group +// and k is a big endian integer. The result is stored in Jacobian coordinates +// (x1, y1, z1). +// +// NOTE: The resulting point will be normalized. +func ScalarBaseMultNonConst(k *ModNScalar, result *JacobianPoint) { + secp.ScalarBaseMultNonConst(k, result) +} + +// ScalarMultNonConst multiplies k*P where k is a big endian integer modulo the +// curve order and P is a point in Jacobian projective coordinates and stores +// the result in the provided Jacobian point. +// +// NOTE: The point must be normalized for this function to return the correct +// result. The resulting point will be normalized. +func ScalarMultNonConst(k *ModNScalar, point, result *JacobianPoint) { + secp.ScalarMultNonConst(k, point, result) +} diff --git a/btcec/error.go b/btcec/error.go new file mode 100644 index 00000000..39c9172b --- /dev/null +++ b/btcec/error.go @@ -0,0 +1,16 @@ +package btcec + +import ( + secp "github.com/decred/dcrd/dcrec/secp256k1/v4" +) + +// Error identifies an error related to public key cryptography using a +// sec256k1 curve. It has full support for errors.Is and errors.As, so the +// caller can ascertain the specific reason for the error by checking the +// underlying error. +type Error = secp.Error + +// ErrorKind identifies a kind of error. It has full support for errors.Is and +// errors.As, so the caller can directly check against an error kind when +// determining the reason for an error. +type ErrorKind = secp.ErrorKind diff --git a/btcec/example_test.go b/btcec/example_test.go index ca51ee87..b73f102c 100644 --- a/btcec/example_test.go +++ b/btcec/example_test.go @@ -8,7 +8,7 @@ import ( "encoding/hex" "fmt" - "github.com/btcsuite/btcd/btcec" + "github.com/btcsuite/btcd/btcec/v2" "github.com/btcsuite/btcd/chaincfg/chainhash" ) @@ -22,16 +22,12 @@ func Example_signMessage() { fmt.Println(err) return } - privKey, pubKey := btcec.PrivKeyFromBytes(btcec.S256(), pkBytes) + privKey, pubKey := btcec.PrivKeyFromBytes(pkBytes) // Sign a message using the private key. message := "test message" messageHash := chainhash.DoubleHashB([]byte(message)) - signature, err := privKey.Sign(messageHash) - if err != nil { - fmt.Println(err) - return - } + signature := btcec.Sign(privKey, messageHash) // Serialize and display the signature. fmt.Printf("Serialized Signature: %x\n", signature.Serialize()) @@ -56,7 +52,7 @@ func Example_verifySignature() { fmt.Println(err) return } - pubKey, err := btcec.ParsePubKey(pubKeyBytes, btcec.S256()) + pubKey, err := btcec.ParsePubKey(pubKeyBytes) if err != nil { fmt.Println(err) return @@ -71,7 +67,7 @@ func Example_verifySignature() { fmt.Println(err) return } - signature, err := btcec.ParseSignature(sigBytes, btcec.S256()) + signature, err := btcec.ParseSignature(sigBytes) if err != nil { fmt.Println(err) return @@ -86,83 +82,3 @@ func Example_verifySignature() { // Output: // Signature Verified? true } - -// This example demonstrates encrypting a message for a public key that is first -// parsed from raw bytes, then decrypting it using the corresponding private key. -func Example_encryptMessage() { - // Decode the hex-encoded pubkey of the recipient. - pubKeyBytes, err := hex.DecodeString("04115c42e757b2efb7671c578530ec191a1" + - "359381e6a71127a9d37c486fd30dae57e76dc58f693bd7e7010358ce6b165e483a29" + - "21010db67ac11b1b51b651953d2") // uncompressed pubkey - if err != nil { - fmt.Println(err) - return - } - pubKey, err := btcec.ParsePubKey(pubKeyBytes, btcec.S256()) - if err != nil { - fmt.Println(err) - return - } - - // Encrypt a message decryptable by the private key corresponding to pubKey - message := "test message" - ciphertext, err := btcec.Encrypt(pubKey, []byte(message)) - if err != nil { - fmt.Println(err) - return - } - - // Decode the hex-encoded private key. - pkBytes, err := hex.DecodeString("a11b0a4e1a132305652ee7a8eb7848f6ad" + - "5ea381e3ce20a2c086a2e388230811") - if err != nil { - fmt.Println(err) - return - } - // note that we already have corresponding pubKey - privKey, _ := btcec.PrivKeyFromBytes(btcec.S256(), pkBytes) - - // Try decrypting and verify if it's the same message. - plaintext, err := btcec.Decrypt(privKey, ciphertext) - if err != nil { - fmt.Println(err) - return - } - - fmt.Println(string(plaintext)) - - // Output: - // test message -} - -// This example demonstrates decrypting a message using a private key that is -// first parsed from raw bytes. -func Example_decryptMessage() { - // Decode the hex-encoded private key. - pkBytes, err := hex.DecodeString("a11b0a4e1a132305652ee7a8eb7848f6ad" + - "5ea381e3ce20a2c086a2e388230811") - if err != nil { - fmt.Println(err) - return - } - - privKey, _ := btcec.PrivKeyFromBytes(btcec.S256(), pkBytes) - - ciphertext, err := hex.DecodeString("35f644fbfb208bc71e57684c3c8b437402ca" + - "002047a2f1b38aa1a8f1d5121778378414f708fe13ebf7b4a7bb74407288c1958969" + - "00207cf4ac6057406e40f79961c973309a892732ae7a74ee96cd89823913b8b8d650" + - "a44166dc61ea1c419d47077b748a9c06b8d57af72deb2819d98a9d503efc59fc8307" + - "d14174f8b83354fac3ff56075162") - - // Try decrypting the message. - plaintext, err := btcec.Decrypt(privKey, ciphertext) - if err != nil { - fmt.Println(err) - return - } - - fmt.Println(string(plaintext)) - - // Output: - // test message -} diff --git a/btcec/field.go b/btcec/field.go index 98105ed8..fef6f345 100644 --- a/btcec/field.go +++ b/btcec/field.go @@ -1,1356 +1,43 @@ -// Copyright (c) 2013-2016 The btcsuite developers -// Copyright (c) 2013-2016 Dave Collins -// Use of this source code is governed by an ISC -// license that can be found in the LICENSE file. - package btcec -// References: -// [HAC]: Handbook of Applied Cryptography Menezes, van Oorschot, Vanstone. -// http://cacr.uwaterloo.ca/hac/ +import secp "github.com/decred/dcrd/dcrec/secp256k1/v4" -// All elliptic curve operations for secp256k1 are done in a finite field -// characterized by a 256-bit prime. Given this precision is larger than the -// biggest available native type, obviously some form of bignum math is needed. -// This package implements specialized fixed-precision field arithmetic rather -// than relying on an arbitrary-precision arithmetic package such as math/big -// for dealing with the field math since the size is known. As a result, rather -// large performance gains are achieved by taking advantage of many -// optimizations not available to arbitrary-precision arithmetic and generic -// modular arithmetic algorithms. +// FieldVal implements optimized fixed-precision arithmetic over the secp256k1 +// finite field. This means all arithmetic is performed modulo +// '0xfffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f'. // -// There are various ways to internally represent each finite field element. -// For example, the most obvious representation would be to use an array of 4 -// uint64s (64 bits * 4 = 256 bits). However, that representation suffers from -// a couple of issues. First, there is no native Go type large enough to handle -// the intermediate results while adding or multiplying two 64-bit numbers, and -// second there is no space left for overflows when performing the intermediate -// arithmetic between each array element which would lead to expensive carry -// propagation. +// WARNING: Since it is so important for the field arithmetic to be extremely +// fast for high performance crypto, this type does not perform any validation +// of documented preconditions where it ordinarily would. As a result, it is +// IMPERATIVE for callers to understand some key concepts that are described +// below and ensure the methods are called with the necessary preconditions +// that each method is documented with. For example, some methods only give the +// correct result if the field value is normalized and others require the field +// values involved to have a maximum magnitude and THERE ARE NO EXPLICIT CHECKS +// TO ENSURE THOSE PRECONDITIONS ARE SATISFIED. This does, unfortunately, make +// the type more difficult to use correctly and while I typically prefer to +// ensure all state and input is valid for most code, this is a bit of an +// exception because those extra checks really add up in what ends up being +// critical hot paths. // -// Given the above, this implementation represents the the field elements as -// 10 uint32s with each word (array entry) treated as base 2^26. This was -// chosen for the following reasons: -// 1) Most systems at the current time are 64-bit (or at least have 64-bit -// registers available for specialized purposes such as MMX) so the -// intermediate results can typically be done using a native register (and -// using uint64s to avoid the need for additional half-word arithmetic) -// 2) In order to allow addition of the internal words without having to -// propagate the the carry, the max normalized value for each register must -// be less than the number of bits available in the register -// 3) Since we're dealing with 32-bit values, 64-bits of overflow is a -// reasonable choice for #2 -// 4) Given the need for 256-bits of precision and the properties stated in #1, -// #2, and #3, the representation which best accommodates this is 10 uint32s -// with base 2^26 (26 bits * 10 = 260 bits, so the final word only needs 22 -// bits) which leaves the desired 64 bits (32 * 10 = 320, 320 - 256 = 64) for -// overflow +// The first key concept when working with this type is normalization. In order +// to avoid the need to propagate a ton of carries, the internal representation +// provides additional overflow bits for each word of the overall 256-bit +// value. This means that there are multiple internal representations for the +// same value and, as a result, any methods that rely on comparison of the +// value, such as equality and oddness determination, require the caller to +// provide a normalized value. // -// Since it is so important that the field arithmetic is extremely fast for -// high performance crypto, this package does not perform any validation where -// it ordinarily would. For example, some functions only give the correct -// result is the field is normalized and there is no checking to ensure it is. -// While I typically prefer to ensure all state and input is valid for most -// packages, this code is really only used internally and every extra check -// counts. - -import ( - "encoding/hex" -) - -// Constants used to make the code more readable. -const ( - twoBitsMask = 0x3 - fourBitsMask = 0xf - sixBitsMask = 0x3f - eightBitsMask = 0xff -) - -// Constants related to the field representation. -const ( - // fieldWords is the number of words used to internally represent the - // 256-bit value. - fieldWords = 10 - - // fieldBase is the exponent used to form the numeric base of each word. - // 2^(fieldBase*i) where i is the word position. - fieldBase = 26 - - // fieldOverflowBits is the minimum number of "overflow" bits for each - // word in the field value. - fieldOverflowBits = 32 - fieldBase - - // fieldBaseMask is the mask for the bits in each word needed to - // represent the numeric base of each word (except the most significant - // word). - fieldBaseMask = (1 << fieldBase) - 1 - - // fieldMSBBits is the number of bits in the most significant word used - // to represent the value. - fieldMSBBits = 256 - (fieldBase * (fieldWords - 1)) - - // fieldMSBMask is the mask for the bits in the most significant word - // needed to represent the value. - fieldMSBMask = (1 << fieldMSBBits) - 1 - - // fieldPrimeWordZero is word zero of the secp256k1 prime in the - // internal field representation. It is used during negation. - fieldPrimeWordZero = 0x3fffc2f - - // fieldPrimeWordOne is word one of the secp256k1 prime in the - // internal field representation. It is used during negation. - fieldPrimeWordOne = 0x3ffffbf -) - -var ( - // fieldQBytes is the value Q = (P+1)/4 for the secp256k1 prime P. This - // value is used to efficiently compute the square root of values in the - // field via exponentiation. The value of Q in hex is: - // - // Q = 3fffffffffffffffffffffffffffffffffffffffffffffffffffffffbfffff0c - fieldQBytes = []byte{ - 0x3f, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, - 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, - 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, - 0xff, 0xff, 0xff, 0xff, 0xbf, 0xff, 0xff, 0x0c, - } -) - -// fieldVal implements optimized fixed-precision arithmetic over the -// secp256k1 finite field. This means all arithmetic is performed modulo -// 0xfffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f. It -// represents each 256-bit value as 10 32-bit integers in base 2^26. This -// provides 6 bits of overflow in each word (10 bits in the most significant -// word) for a total of 64 bits of overflow (9*6 + 10 = 64). It only implements -// the arithmetic needed for elliptic curve operations. +// The second key concept when working with this type is magnitude. As +// previously mentioned, the internal representation provides additional +// overflow bits which means that the more math operations that are performed +// on the field value between normalizations, the more those overflow bits +// accumulate. The magnitude is effectively that maximum possible number of +// those overflow bits that could possibly be required as a result of a given +// operation. Since there are only a limited number of overflow bits available, +// this implies that the max possible magnitude MUST be tracked by the caller +// and the caller MUST normalize the field value if a given operation would +// cause the magnitude of the result to exceed the max allowed value. // -// The following depicts the internal representation: -// ----------------------------------------------------------------- -// | n[9] | n[8] | ... | n[0] | -// | 32 bits available | 32 bits available | ... | 32 bits available | -// | 22 bits for value | 26 bits for value | ... | 26 bits for value | -// | 10 bits overflow | 6 bits overflow | ... | 6 bits overflow | -// | Mult: 2^(26*9) | Mult: 2^(26*8) | ... | Mult: 2^(26*0) | -// ----------------------------------------------------------------- -// -// For example, consider the number 2^49 + 1. It would be represented as: -// n[0] = 1 -// n[1] = 2^23 -// n[2..9] = 0 -// -// The full 256-bit value is then calculated by looping i from 9..0 and -// doing sum(n[i] * 2^(26i)) like so: -// n[9] * 2^(26*9) = 0 * 2^234 = 0 -// n[8] * 2^(26*8) = 0 * 2^208 = 0 -// ... -// n[1] * 2^(26*1) = 2^23 * 2^26 = 2^49 -// n[0] * 2^(26*0) = 1 * 2^0 = 1 -// Sum: 0 + 0 + ... + 2^49 + 1 = 2^49 + 1 -type fieldVal struct { - n [10]uint32 -} - -// String returns the field value as a human-readable hex string. -func (f fieldVal) String() string { - t := new(fieldVal).Set(&f).Normalize() - return hex.EncodeToString(t.Bytes()[:]) -} - -// Zero sets the field value to zero. A newly created field value is already -// set to zero. This function can be useful to clear an existing field value -// for reuse. -func (f *fieldVal) Zero() { - f.n[0] = 0 - f.n[1] = 0 - f.n[2] = 0 - f.n[3] = 0 - f.n[4] = 0 - f.n[5] = 0 - f.n[6] = 0 - f.n[7] = 0 - f.n[8] = 0 - f.n[9] = 0 -} - -// Set sets the field value equal to the passed value. -// -// The field value is returned to support chaining. This enables syntax like: -// f := new(fieldVal).Set(f2).Add(1) so that f = f2 + 1 where f2 is not -// modified. -func (f *fieldVal) Set(val *fieldVal) *fieldVal { - *f = *val - return f -} - -// SetInt sets the field value to the passed integer. This is a convenience -// function since it is fairly common to perform some arithemetic with small -// native integers. -// -// The field value is returned to support chaining. This enables syntax such -// as f := new(fieldVal).SetInt(2).Mul(f2) so that f = 2 * f2. -func (f *fieldVal) SetInt(ui uint) *fieldVal { - f.Zero() - f.n[0] = uint32(ui) - return f -} - -// SetBytes packs the passed 32-byte big-endian value into the internal field -// value representation. -// -// The field value is returned to support chaining. This enables syntax like: -// f := new(fieldVal).SetBytes(byteArray).Mul(f2) so that f = ba * f2. -func (f *fieldVal) SetBytes(b *[32]byte) *fieldVal { - // Pack the 256 total bits across the 10 uint32 words with a max of - // 26-bits per word. This could be done with a couple of for loops, - // but this unrolled version is significantly faster. Benchmarks show - // this is about 34 times faster than the variant which uses loops. - f.n[0] = uint32(b[31]) | uint32(b[30])<<8 | uint32(b[29])<<16 | - (uint32(b[28])&twoBitsMask)<<24 - f.n[1] = uint32(b[28])>>2 | uint32(b[27])<<6 | uint32(b[26])<<14 | - (uint32(b[25])&fourBitsMask)<<22 - f.n[2] = uint32(b[25])>>4 | uint32(b[24])<<4 | uint32(b[23])<<12 | - (uint32(b[22])&sixBitsMask)<<20 - f.n[3] = uint32(b[22])>>6 | uint32(b[21])<<2 | uint32(b[20])<<10 | - uint32(b[19])<<18 - f.n[4] = uint32(b[18]) | uint32(b[17])<<8 | uint32(b[16])<<16 | - (uint32(b[15])&twoBitsMask)<<24 - f.n[5] = uint32(b[15])>>2 | uint32(b[14])<<6 | uint32(b[13])<<14 | - (uint32(b[12])&fourBitsMask)<<22 - f.n[6] = uint32(b[12])>>4 | uint32(b[11])<<4 | uint32(b[10])<<12 | - (uint32(b[9])&sixBitsMask)<<20 - f.n[7] = uint32(b[9])>>6 | uint32(b[8])<<2 | uint32(b[7])<<10 | - uint32(b[6])<<18 - f.n[8] = uint32(b[5]) | uint32(b[4])<<8 | uint32(b[3])<<16 | - (uint32(b[2])&twoBitsMask)<<24 - f.n[9] = uint32(b[2])>>2 | uint32(b[1])<<6 | uint32(b[0])<<14 - return f -} - -// SetByteSlice interprets the provided slice as a 256-bit big-endian unsigned -// integer (meaning it is truncated to the first 32 bytes), packs it into the -// internal field value representation, and returns the updated field value. -// -// Note that since passing a slice with more than 32 bytes is truncated, it is -// possible that the truncated value is less than the field prime. It is up to -// the caller to decide whether it needs to provide numbers of the appropriate -// size or if it is acceptable to use this function with the described -// truncation behavior. -// -// The field value is returned to support chaining. This enables syntax like: -// f := new(fieldVal).SetByteSlice(byteSlice) -func (f *fieldVal) SetByteSlice(b []byte) *fieldVal { - var b32 [32]byte - if len(b) > 32 { - b = b[:32] - } - copy(b32[32-len(b):], b) - return f.SetBytes(&b32) -} - -// SetHex decodes the passed big-endian hex string into the internal field value -// representation. Only the first 32-bytes are used. -// -// The field value is returned to support chaining. This enables syntax like: -// f := new(fieldVal).SetHex("0abc").Add(1) so that f = 0x0abc + 1 -func (f *fieldVal) SetHex(hexString string) *fieldVal { - if len(hexString)%2 != 0 { - hexString = "0" + hexString - } - bytes, _ := hex.DecodeString(hexString) - return f.SetByteSlice(bytes) -} - -// Normalize normalizes the internal field words into the desired range and -// performs fast modular reduction over the secp256k1 prime by making use of the -// special form of the prime. -func (f *fieldVal) Normalize() *fieldVal { - // The field representation leaves 6 bits of overflow in each word so - // intermediate calculations can be performed without needing to - // propagate the carry to each higher word during the calculations. In - // order to normalize, we need to "compact" the full 256-bit value to - // the right while propagating any carries through to the high order - // word. - // - // Since this field is doing arithmetic modulo the secp256k1 prime, we - // also need to perform modular reduction over the prime. - // - // Per [HAC] section 14.3.4: Reduction method of moduli of special form, - // when the modulus is of the special form m = b^t - c, highly efficient - // reduction can be achieved. - // - // The secp256k1 prime is equivalent to 2^256 - 4294968273, so it fits - // this criteria. - // - // 4294968273 in field representation (base 2^26) is: - // n[0] = 977 - // n[1] = 64 - // That is to say (2^26 * 64) + 977 = 4294968273 - // - // The algorithm presented in the referenced section typically repeats - // until the quotient is zero. However, due to our field representation - // we already know to within one reduction how many times we would need - // to repeat as it's the uppermost bits of the high order word. Thus we - // can simply multiply the magnitude by the field representation of the - // prime and do a single iteration. After this step there might be an - // additional carry to bit 256 (bit 22 of the high order word). - t9 := f.n[9] - m := t9 >> fieldMSBBits - t9 = t9 & fieldMSBMask - t0 := f.n[0] + m*977 - t1 := (t0 >> fieldBase) + f.n[1] + (m << 6) - t0 = t0 & fieldBaseMask - t2 := (t1 >> fieldBase) + f.n[2] - t1 = t1 & fieldBaseMask - t3 := (t2 >> fieldBase) + f.n[3] - t2 = t2 & fieldBaseMask - t4 := (t3 >> fieldBase) + f.n[4] - t3 = t3 & fieldBaseMask - t5 := (t4 >> fieldBase) + f.n[5] - t4 = t4 & fieldBaseMask - t6 := (t5 >> fieldBase) + f.n[6] - t5 = t5 & fieldBaseMask - t7 := (t6 >> fieldBase) + f.n[7] - t6 = t6 & fieldBaseMask - t8 := (t7 >> fieldBase) + f.n[8] - t7 = t7 & fieldBaseMask - t9 = (t8 >> fieldBase) + t9 - t8 = t8 & fieldBaseMask - - // At this point, the magnitude is guaranteed to be one, however, the - // value could still be greater than the prime if there was either a - // carry through to bit 256 (bit 22 of the higher order word) or the - // value is greater than or equal to the field characteristic. The - // following determines if either or these conditions are true and does - // the final reduction in constant time. - // - // Note that the if/else statements here intentionally do the bitwise - // operators even when it won't change the value to ensure constant time - // between the branches. Also note that 'm' will be zero when neither - // of the aforementioned conditions are true and the value will not be - // changed when 'm' is zero. - m = 1 - if t9 == fieldMSBMask { - m &= 1 - } else { - m &= 0 - } - if t2&t3&t4&t5&t6&t7&t8 == fieldBaseMask { - m &= 1 - } else { - m &= 0 - } - if ((t0+977)>>fieldBase + t1 + 64) > fieldBaseMask { - m &= 1 - } else { - m &= 0 - } - if t9>>fieldMSBBits != 0 { - m |= 1 - } else { - m |= 0 - } - t0 = t0 + m*977 - t1 = (t0 >> fieldBase) + t1 + (m << 6) - t0 = t0 & fieldBaseMask - t2 = (t1 >> fieldBase) + t2 - t1 = t1 & fieldBaseMask - t3 = (t2 >> fieldBase) + t3 - t2 = t2 & fieldBaseMask - t4 = (t3 >> fieldBase) + t4 - t3 = t3 & fieldBaseMask - t5 = (t4 >> fieldBase) + t5 - t4 = t4 & fieldBaseMask - t6 = (t5 >> fieldBase) + t6 - t5 = t5 & fieldBaseMask - t7 = (t6 >> fieldBase) + t7 - t6 = t6 & fieldBaseMask - t8 = (t7 >> fieldBase) + t8 - t7 = t7 & fieldBaseMask - t9 = (t8 >> fieldBase) + t9 - t8 = t8 & fieldBaseMask - t9 = t9 & fieldMSBMask // Remove potential multiple of 2^256. - - // Finally, set the normalized and reduced words. - f.n[0] = t0 - f.n[1] = t1 - f.n[2] = t2 - f.n[3] = t3 - f.n[4] = t4 - f.n[5] = t5 - f.n[6] = t6 - f.n[7] = t7 - f.n[8] = t8 - f.n[9] = t9 - return f -} - -// PutBytes unpacks the field value to a 32-byte big-endian value using the -// passed byte array. There is a similar function, Bytes, which unpacks the -// field value into a new array and returns that. This version is provided -// since it can be useful to cut down on the number of allocations by allowing -// the caller to reuse a buffer. -// -// The field value must be normalized for this function to return the correct -// result. -func (f *fieldVal) PutBytes(b *[32]byte) { - // Unpack the 256 total bits from the 10 uint32 words with a max of - // 26-bits per word. This could be done with a couple of for loops, - // but this unrolled version is a bit faster. Benchmarks show this is - // about 10 times faster than the variant which uses loops. - b[31] = byte(f.n[0] & eightBitsMask) - b[30] = byte((f.n[0] >> 8) & eightBitsMask) - b[29] = byte((f.n[0] >> 16) & eightBitsMask) - b[28] = byte((f.n[0]>>24)&twoBitsMask | (f.n[1]&sixBitsMask)<<2) - b[27] = byte((f.n[1] >> 6) & eightBitsMask) - b[26] = byte((f.n[1] >> 14) & eightBitsMask) - b[25] = byte((f.n[1]>>22)&fourBitsMask | (f.n[2]&fourBitsMask)<<4) - b[24] = byte((f.n[2] >> 4) & eightBitsMask) - b[23] = byte((f.n[2] >> 12) & eightBitsMask) - b[22] = byte((f.n[2]>>20)&sixBitsMask | (f.n[3]&twoBitsMask)<<6) - b[21] = byte((f.n[3] >> 2) & eightBitsMask) - b[20] = byte((f.n[3] >> 10) & eightBitsMask) - b[19] = byte((f.n[3] >> 18) & eightBitsMask) - b[18] = byte(f.n[4] & eightBitsMask) - b[17] = byte((f.n[4] >> 8) & eightBitsMask) - b[16] = byte((f.n[4] >> 16) & eightBitsMask) - b[15] = byte((f.n[4]>>24)&twoBitsMask | (f.n[5]&sixBitsMask)<<2) - b[14] = byte((f.n[5] >> 6) & eightBitsMask) - b[13] = byte((f.n[5] >> 14) & eightBitsMask) - b[12] = byte((f.n[5]>>22)&fourBitsMask | (f.n[6]&fourBitsMask)<<4) - b[11] = byte((f.n[6] >> 4) & eightBitsMask) - b[10] = byte((f.n[6] >> 12) & eightBitsMask) - b[9] = byte((f.n[6]>>20)&sixBitsMask | (f.n[7]&twoBitsMask)<<6) - b[8] = byte((f.n[7] >> 2) & eightBitsMask) - b[7] = byte((f.n[7] >> 10) & eightBitsMask) - b[6] = byte((f.n[7] >> 18) & eightBitsMask) - b[5] = byte(f.n[8] & eightBitsMask) - b[4] = byte((f.n[8] >> 8) & eightBitsMask) - b[3] = byte((f.n[8] >> 16) & eightBitsMask) - b[2] = byte((f.n[8]>>24)&twoBitsMask | (f.n[9]&sixBitsMask)<<2) - b[1] = byte((f.n[9] >> 6) & eightBitsMask) - b[0] = byte((f.n[9] >> 14) & eightBitsMask) -} - -// Bytes unpacks the field value to a 32-byte big-endian value. See PutBytes -// for a variant that allows the a buffer to be passed which can be useful to -// to cut down on the number of allocations by allowing the caller to reuse a -// buffer. -// -// The field value must be normalized for this function to return correct -// result. -func (f *fieldVal) Bytes() *[32]byte { - b := new([32]byte) - f.PutBytes(b) - return b -} - -// IsZero returns whether or not the field value is equal to zero. -func (f *fieldVal) IsZero() bool { - // The value can only be zero if no bits are set in any of the words. - // This is a constant time implementation. - bits := f.n[0] | f.n[1] | f.n[2] | f.n[3] | f.n[4] | - f.n[5] | f.n[6] | f.n[7] | f.n[8] | f.n[9] - - return bits == 0 -} - -// IsOdd returns whether or not the field value is an odd number. -// -// The field value must be normalized for this function to return correct -// result. -func (f *fieldVal) IsOdd() bool { - // Only odd numbers have the bottom bit set. - return f.n[0]&1 == 1 -} - -// Equals returns whether or not the two field values are the same. Both -// field values being compared must be normalized for this function to return -// the correct result. -func (f *fieldVal) Equals(val *fieldVal) bool { - // Xor only sets bits when they are different, so the two field values - // can only be the same if no bits are set after xoring each word. - // This is a constant time implementation. - bits := (f.n[0] ^ val.n[0]) | (f.n[1] ^ val.n[1]) | (f.n[2] ^ val.n[2]) | - (f.n[3] ^ val.n[3]) | (f.n[4] ^ val.n[4]) | (f.n[5] ^ val.n[5]) | - (f.n[6] ^ val.n[6]) | (f.n[7] ^ val.n[7]) | (f.n[8] ^ val.n[8]) | - (f.n[9] ^ val.n[9]) - - return bits == 0 -} - -// NegateVal negates the passed value and stores the result in f. The caller -// must provide the magnitude of the passed value for a correct result. -// -// The field value is returned to support chaining. This enables syntax like: -// f.NegateVal(f2).AddInt(1) so that f = -f2 + 1. -func (f *fieldVal) NegateVal(val *fieldVal, magnitude uint32) *fieldVal { - // Negation in the field is just the prime minus the value. However, - // in order to allow negation against a field value without having to - // normalize/reduce it first, multiply by the magnitude (that is how - // "far" away it is from the normalized value) to adjust. Also, since - // negating a value pushes it one more order of magnitude away from the - // normalized range, add 1 to compensate. - // - // For some intuition here, imagine you're performing mod 12 arithmetic - // (picture a clock) and you are negating the number 7. So you start at - // 12 (which is of course 0 under mod 12) and count backwards (left on - // the clock) 7 times to arrive at 5. Notice this is just 12-7 = 5. - // Now, assume you're starting with 19, which is a number that is - // already larger than the modulus and congruent to 7 (mod 12). When a - // value is already in the desired range, its magnitude is 1. Since 19 - // is an additional "step", its magnitude (mod 12) is 2. Since any - // multiple of the modulus is conguent to zero (mod m), the answer can - // be shortcut by simply mulplying the magnitude by the modulus and - // subtracting. Keeping with the example, this would be (2*12)-19 = 5. - f.n[0] = (magnitude+1)*fieldPrimeWordZero - val.n[0] - f.n[1] = (magnitude+1)*fieldPrimeWordOne - val.n[1] - f.n[2] = (magnitude+1)*fieldBaseMask - val.n[2] - f.n[3] = (magnitude+1)*fieldBaseMask - val.n[3] - f.n[4] = (magnitude+1)*fieldBaseMask - val.n[4] - f.n[5] = (magnitude+1)*fieldBaseMask - val.n[5] - f.n[6] = (magnitude+1)*fieldBaseMask - val.n[6] - f.n[7] = (magnitude+1)*fieldBaseMask - val.n[7] - f.n[8] = (magnitude+1)*fieldBaseMask - val.n[8] - f.n[9] = (magnitude+1)*fieldMSBMask - val.n[9] - - return f -} - -// Negate negates the field value. The existing field value is modified. The -// caller must provide the magnitude of the field value for a correct result. -// -// The field value is returned to support chaining. This enables syntax like: -// f.Negate().AddInt(1) so that f = -f + 1. -func (f *fieldVal) Negate(magnitude uint32) *fieldVal { - return f.NegateVal(f, magnitude) -} - -// AddInt adds the passed integer to the existing field value and stores the -// result in f. This is a convenience function since it is fairly common to -// perform some arithemetic with small native integers. -// -// The field value is returned to support chaining. This enables syntax like: -// f.AddInt(1).Add(f2) so that f = f + 1 + f2. -func (f *fieldVal) AddInt(ui uint) *fieldVal { - // Since the field representation intentionally provides overflow bits, - // it's ok to use carryless addition as the carry bit is safely part of - // the word and will be normalized out. - f.n[0] += uint32(ui) - - return f -} - -// Add adds the passed value to the existing field value and stores the result -// in f. -// -// The field value is returned to support chaining. This enables syntax like: -// f.Add(f2).AddInt(1) so that f = f + f2 + 1. -func (f *fieldVal) Add(val *fieldVal) *fieldVal { - // Since the field representation intentionally provides overflow bits, - // it's ok to use carryless addition as the carry bit is safely part of - // each word and will be normalized out. This could obviously be done - // in a loop, but the unrolled version is faster. - f.n[0] += val.n[0] - f.n[1] += val.n[1] - f.n[2] += val.n[2] - f.n[3] += val.n[3] - f.n[4] += val.n[4] - f.n[5] += val.n[5] - f.n[6] += val.n[6] - f.n[7] += val.n[7] - f.n[8] += val.n[8] - f.n[9] += val.n[9] - - return f -} - -// Add2 adds the passed two field values together and stores the result in f. -// -// The field value is returned to support chaining. This enables syntax like: -// f3.Add2(f, f2).AddInt(1) so that f3 = f + f2 + 1. -func (f *fieldVal) Add2(val *fieldVal, val2 *fieldVal) *fieldVal { - // Since the field representation intentionally provides overflow bits, - // it's ok to use carryless addition as the carry bit is safely part of - // each word and will be normalized out. This could obviously be done - // in a loop, but the unrolled version is faster. - f.n[0] = val.n[0] + val2.n[0] - f.n[1] = val.n[1] + val2.n[1] - f.n[2] = val.n[2] + val2.n[2] - f.n[3] = val.n[3] + val2.n[3] - f.n[4] = val.n[4] + val2.n[4] - f.n[5] = val.n[5] + val2.n[5] - f.n[6] = val.n[6] + val2.n[6] - f.n[7] = val.n[7] + val2.n[7] - f.n[8] = val.n[8] + val2.n[8] - f.n[9] = val.n[9] + val2.n[9] - - return f -} - -// MulInt multiplies the field value by the passed int and stores the result in -// f. Note that this function can overflow if multiplying the value by any of -// the individual words exceeds a max uint32. Therefore it is important that -// the caller ensures no overflows will occur before using this function. -// -// The field value is returned to support chaining. This enables syntax like: -// f.MulInt(2).Add(f2) so that f = 2 * f + f2. -func (f *fieldVal) MulInt(val uint) *fieldVal { - // Since each word of the field representation can hold up to - // fieldOverflowBits extra bits which will be normalized out, it's safe - // to multiply each word without using a larger type or carry - // propagation so long as the values won't overflow a uint32. This - // could obviously be done in a loop, but the unrolled version is - // faster. - ui := uint32(val) - f.n[0] *= ui - f.n[1] *= ui - f.n[2] *= ui - f.n[3] *= ui - f.n[4] *= ui - f.n[5] *= ui - f.n[6] *= ui - f.n[7] *= ui - f.n[8] *= ui - f.n[9] *= ui - - return f -} - -// Mul multiplies the passed value to the existing field value and stores the -// result in f. Note that this function can overflow if multiplying any -// of the individual words exceeds a max uint32. In practice, this means the -// magnitude of either value involved in the multiplication must be a max of -// 8. -// -// The field value is returned to support chaining. This enables syntax like: -// f.Mul(f2).AddInt(1) so that f = (f * f2) + 1. -func (f *fieldVal) Mul(val *fieldVal) *fieldVal { - return f.Mul2(f, val) -} - -// Mul2 multiplies the passed two field values together and stores the result -// result in f. Note that this function can overflow if multiplying any of -// the individual words exceeds a max uint32. In practice, this means the -// magnitude of either value involved in the multiplication must be a max of -// 8. -// -// The field value is returned to support chaining. This enables syntax like: -// f3.Mul2(f, f2).AddInt(1) so that f3 = (f * f2) + 1. -func (f *fieldVal) Mul2(val *fieldVal, val2 *fieldVal) *fieldVal { - // This could be done with a couple of for loops and an array to store - // the intermediate terms, but this unrolled version is significantly - // faster. - - // Terms for 2^(fieldBase*0). - m := uint64(val.n[0]) * uint64(val2.n[0]) - t0 := m & fieldBaseMask - - // Terms for 2^(fieldBase*1). - m = (m >> fieldBase) + - uint64(val.n[0])*uint64(val2.n[1]) + - uint64(val.n[1])*uint64(val2.n[0]) - t1 := m & fieldBaseMask - - // Terms for 2^(fieldBase*2). - m = (m >> fieldBase) + - uint64(val.n[0])*uint64(val2.n[2]) + - uint64(val.n[1])*uint64(val2.n[1]) + - uint64(val.n[2])*uint64(val2.n[0]) - t2 := m & fieldBaseMask - - // Terms for 2^(fieldBase*3). - m = (m >> fieldBase) + - uint64(val.n[0])*uint64(val2.n[3]) + - uint64(val.n[1])*uint64(val2.n[2]) + - uint64(val.n[2])*uint64(val2.n[1]) + - uint64(val.n[3])*uint64(val2.n[0]) - t3 := m & fieldBaseMask - - // Terms for 2^(fieldBase*4). - m = (m >> fieldBase) + - uint64(val.n[0])*uint64(val2.n[4]) + - uint64(val.n[1])*uint64(val2.n[3]) + - uint64(val.n[2])*uint64(val2.n[2]) + - uint64(val.n[3])*uint64(val2.n[1]) + - uint64(val.n[4])*uint64(val2.n[0]) - t4 := m & fieldBaseMask - - // Terms for 2^(fieldBase*5). - m = (m >> fieldBase) + - uint64(val.n[0])*uint64(val2.n[5]) + - uint64(val.n[1])*uint64(val2.n[4]) + - uint64(val.n[2])*uint64(val2.n[3]) + - uint64(val.n[3])*uint64(val2.n[2]) + - uint64(val.n[4])*uint64(val2.n[1]) + - uint64(val.n[5])*uint64(val2.n[0]) - t5 := m & fieldBaseMask - - // Terms for 2^(fieldBase*6). - m = (m >> fieldBase) + - uint64(val.n[0])*uint64(val2.n[6]) + - uint64(val.n[1])*uint64(val2.n[5]) + - uint64(val.n[2])*uint64(val2.n[4]) + - uint64(val.n[3])*uint64(val2.n[3]) + - uint64(val.n[4])*uint64(val2.n[2]) + - uint64(val.n[5])*uint64(val2.n[1]) + - uint64(val.n[6])*uint64(val2.n[0]) - t6 := m & fieldBaseMask - - // Terms for 2^(fieldBase*7). - m = (m >> fieldBase) + - uint64(val.n[0])*uint64(val2.n[7]) + - uint64(val.n[1])*uint64(val2.n[6]) + - uint64(val.n[2])*uint64(val2.n[5]) + - uint64(val.n[3])*uint64(val2.n[4]) + - uint64(val.n[4])*uint64(val2.n[3]) + - uint64(val.n[5])*uint64(val2.n[2]) + - uint64(val.n[6])*uint64(val2.n[1]) + - uint64(val.n[7])*uint64(val2.n[0]) - t7 := m & fieldBaseMask - - // Terms for 2^(fieldBase*8). - m = (m >> fieldBase) + - uint64(val.n[0])*uint64(val2.n[8]) + - uint64(val.n[1])*uint64(val2.n[7]) + - uint64(val.n[2])*uint64(val2.n[6]) + - uint64(val.n[3])*uint64(val2.n[5]) + - uint64(val.n[4])*uint64(val2.n[4]) + - uint64(val.n[5])*uint64(val2.n[3]) + - uint64(val.n[6])*uint64(val2.n[2]) + - uint64(val.n[7])*uint64(val2.n[1]) + - uint64(val.n[8])*uint64(val2.n[0]) - t8 := m & fieldBaseMask - - // Terms for 2^(fieldBase*9). - m = (m >> fieldBase) + - uint64(val.n[0])*uint64(val2.n[9]) + - uint64(val.n[1])*uint64(val2.n[8]) + - uint64(val.n[2])*uint64(val2.n[7]) + - uint64(val.n[3])*uint64(val2.n[6]) + - uint64(val.n[4])*uint64(val2.n[5]) + - uint64(val.n[5])*uint64(val2.n[4]) + - uint64(val.n[6])*uint64(val2.n[3]) + - uint64(val.n[7])*uint64(val2.n[2]) + - uint64(val.n[8])*uint64(val2.n[1]) + - uint64(val.n[9])*uint64(val2.n[0]) - t9 := m & fieldBaseMask - - // Terms for 2^(fieldBase*10). - m = (m >> fieldBase) + - uint64(val.n[1])*uint64(val2.n[9]) + - uint64(val.n[2])*uint64(val2.n[8]) + - uint64(val.n[3])*uint64(val2.n[7]) + - uint64(val.n[4])*uint64(val2.n[6]) + - uint64(val.n[5])*uint64(val2.n[5]) + - uint64(val.n[6])*uint64(val2.n[4]) + - uint64(val.n[7])*uint64(val2.n[3]) + - uint64(val.n[8])*uint64(val2.n[2]) + - uint64(val.n[9])*uint64(val2.n[1]) - t10 := m & fieldBaseMask - - // Terms for 2^(fieldBase*11). - m = (m >> fieldBase) + - uint64(val.n[2])*uint64(val2.n[9]) + - uint64(val.n[3])*uint64(val2.n[8]) + - uint64(val.n[4])*uint64(val2.n[7]) + - uint64(val.n[5])*uint64(val2.n[6]) + - uint64(val.n[6])*uint64(val2.n[5]) + - uint64(val.n[7])*uint64(val2.n[4]) + - uint64(val.n[8])*uint64(val2.n[3]) + - uint64(val.n[9])*uint64(val2.n[2]) - t11 := m & fieldBaseMask - - // Terms for 2^(fieldBase*12). - m = (m >> fieldBase) + - uint64(val.n[3])*uint64(val2.n[9]) + - uint64(val.n[4])*uint64(val2.n[8]) + - uint64(val.n[5])*uint64(val2.n[7]) + - uint64(val.n[6])*uint64(val2.n[6]) + - uint64(val.n[7])*uint64(val2.n[5]) + - uint64(val.n[8])*uint64(val2.n[4]) + - uint64(val.n[9])*uint64(val2.n[3]) - t12 := m & fieldBaseMask - - // Terms for 2^(fieldBase*13). - m = (m >> fieldBase) + - uint64(val.n[4])*uint64(val2.n[9]) + - uint64(val.n[5])*uint64(val2.n[8]) + - uint64(val.n[6])*uint64(val2.n[7]) + - uint64(val.n[7])*uint64(val2.n[6]) + - uint64(val.n[8])*uint64(val2.n[5]) + - uint64(val.n[9])*uint64(val2.n[4]) - t13 := m & fieldBaseMask - - // Terms for 2^(fieldBase*14). - m = (m >> fieldBase) + - uint64(val.n[5])*uint64(val2.n[9]) + - uint64(val.n[6])*uint64(val2.n[8]) + - uint64(val.n[7])*uint64(val2.n[7]) + - uint64(val.n[8])*uint64(val2.n[6]) + - uint64(val.n[9])*uint64(val2.n[5]) - t14 := m & fieldBaseMask - - // Terms for 2^(fieldBase*15). - m = (m >> fieldBase) + - uint64(val.n[6])*uint64(val2.n[9]) + - uint64(val.n[7])*uint64(val2.n[8]) + - uint64(val.n[8])*uint64(val2.n[7]) + - uint64(val.n[9])*uint64(val2.n[6]) - t15 := m & fieldBaseMask - - // Terms for 2^(fieldBase*16). - m = (m >> fieldBase) + - uint64(val.n[7])*uint64(val2.n[9]) + - uint64(val.n[8])*uint64(val2.n[8]) + - uint64(val.n[9])*uint64(val2.n[7]) - t16 := m & fieldBaseMask - - // Terms for 2^(fieldBase*17). - m = (m >> fieldBase) + - uint64(val.n[8])*uint64(val2.n[9]) + - uint64(val.n[9])*uint64(val2.n[8]) - t17 := m & fieldBaseMask - - // Terms for 2^(fieldBase*18). - m = (m >> fieldBase) + uint64(val.n[9])*uint64(val2.n[9]) - t18 := m & fieldBaseMask - - // What's left is for 2^(fieldBase*19). - t19 := m >> fieldBase - - // At this point, all of the terms are grouped into their respective - // base. - // - // Per [HAC] section 14.3.4: Reduction method of moduli of special form, - // when the modulus is of the special form m = b^t - c, highly efficient - // reduction can be achieved per the provided algorithm. - // - // The secp256k1 prime is equivalent to 2^256 - 4294968273, so it fits - // this criteria. - // - // 4294968273 in field representation (base 2^26) is: - // n[0] = 977 - // n[1] = 64 - // That is to say (2^26 * 64) + 977 = 4294968273 - // - // Since each word is in base 26, the upper terms (t10 and up) start - // at 260 bits (versus the final desired range of 256 bits), so the - // field representation of 'c' from above needs to be adjusted for the - // extra 4 bits by multiplying it by 2^4 = 16. 4294968273 * 16 = - // 68719492368. Thus, the adjusted field representation of 'c' is: - // n[0] = 977 * 16 = 15632 - // n[1] = 64 * 16 = 1024 - // That is to say (2^26 * 1024) + 15632 = 68719492368 - // - // To reduce the final term, t19, the entire 'c' value is needed instead - // of only n[0] because there are no more terms left to handle n[1]. - // This means there might be some magnitude left in the upper bits that - // is handled below. - m = t0 + t10*15632 - t0 = m & fieldBaseMask - m = (m >> fieldBase) + t1 + t10*1024 + t11*15632 - t1 = m & fieldBaseMask - m = (m >> fieldBase) + t2 + t11*1024 + t12*15632 - t2 = m & fieldBaseMask - m = (m >> fieldBase) + t3 + t12*1024 + t13*15632 - t3 = m & fieldBaseMask - m = (m >> fieldBase) + t4 + t13*1024 + t14*15632 - t4 = m & fieldBaseMask - m = (m >> fieldBase) + t5 + t14*1024 + t15*15632 - t5 = m & fieldBaseMask - m = (m >> fieldBase) + t6 + t15*1024 + t16*15632 - t6 = m & fieldBaseMask - m = (m >> fieldBase) + t7 + t16*1024 + t17*15632 - t7 = m & fieldBaseMask - m = (m >> fieldBase) + t8 + t17*1024 + t18*15632 - t8 = m & fieldBaseMask - m = (m >> fieldBase) + t9 + t18*1024 + t19*68719492368 - t9 = m & fieldMSBMask - m = m >> fieldMSBBits - - // At this point, if the magnitude is greater than 0, the overall value - // is greater than the max possible 256-bit value. In particular, it is - // "how many times larger" than the max value it is. - // - // The algorithm presented in [HAC] section 14.3.4 repeats until the - // quotient is zero. However, due to the above, we already know at - // least how many times we would need to repeat as it's the value - // currently in m. Thus we can simply multiply the magnitude by the - // field representation of the prime and do a single iteration. Notice - // that nothing will be changed when the magnitude is zero, so we could - // skip this in that case, however always running regardless allows it - // to run in constant time. The final result will be in the range - // 0 <= result <= prime + (2^64 - c), so it is guaranteed to have a - // magnitude of 1, but it is denormalized. - d := t0 + m*977 - f.n[0] = uint32(d & fieldBaseMask) - d = (d >> fieldBase) + t1 + m*64 - f.n[1] = uint32(d & fieldBaseMask) - f.n[2] = uint32((d >> fieldBase) + t2) - f.n[3] = uint32(t3) - f.n[4] = uint32(t4) - f.n[5] = uint32(t5) - f.n[6] = uint32(t6) - f.n[7] = uint32(t7) - f.n[8] = uint32(t8) - f.n[9] = uint32(t9) - - return f -} - -// Square squares the field value. The existing field value is modified. Note -// that this function can overflow if multiplying any of the individual words -// exceeds a max uint32. In practice, this means the magnitude of the field -// must be a max of 8 to prevent overflow. -// -// The field value is returned to support chaining. This enables syntax like: -// f.Square().Mul(f2) so that f = f^2 * f2. -func (f *fieldVal) Square() *fieldVal { - return f.SquareVal(f) -} - -// SquareVal squares the passed value and stores the result in f. Note that -// this function can overflow if multiplying any of the individual words -// exceeds a max uint32. In practice, this means the magnitude of the field -// being squred must be a max of 8 to prevent overflow. -// -// The field value is returned to support chaining. This enables syntax like: -// f3.SquareVal(f).Mul(f) so that f3 = f^2 * f = f^3. -func (f *fieldVal) SquareVal(val *fieldVal) *fieldVal { - // This could be done with a couple of for loops and an array to store - // the intermediate terms, but this unrolled version is significantly - // faster. - - // Terms for 2^(fieldBase*0). - m := uint64(val.n[0]) * uint64(val.n[0]) - t0 := m & fieldBaseMask - - // Terms for 2^(fieldBase*1). - m = (m >> fieldBase) + 2*uint64(val.n[0])*uint64(val.n[1]) - t1 := m & fieldBaseMask - - // Terms for 2^(fieldBase*2). - m = (m >> fieldBase) + - 2*uint64(val.n[0])*uint64(val.n[2]) + - uint64(val.n[1])*uint64(val.n[1]) - t2 := m & fieldBaseMask - - // Terms for 2^(fieldBase*3). - m = (m >> fieldBase) + - 2*uint64(val.n[0])*uint64(val.n[3]) + - 2*uint64(val.n[1])*uint64(val.n[2]) - t3 := m & fieldBaseMask - - // Terms for 2^(fieldBase*4). - m = (m >> fieldBase) + - 2*uint64(val.n[0])*uint64(val.n[4]) + - 2*uint64(val.n[1])*uint64(val.n[3]) + - uint64(val.n[2])*uint64(val.n[2]) - t4 := m & fieldBaseMask - - // Terms for 2^(fieldBase*5). - m = (m >> fieldBase) + - 2*uint64(val.n[0])*uint64(val.n[5]) + - 2*uint64(val.n[1])*uint64(val.n[4]) + - 2*uint64(val.n[2])*uint64(val.n[3]) - t5 := m & fieldBaseMask - - // Terms for 2^(fieldBase*6). - m = (m >> fieldBase) + - 2*uint64(val.n[0])*uint64(val.n[6]) + - 2*uint64(val.n[1])*uint64(val.n[5]) + - 2*uint64(val.n[2])*uint64(val.n[4]) + - uint64(val.n[3])*uint64(val.n[3]) - t6 := m & fieldBaseMask - - // Terms for 2^(fieldBase*7). - m = (m >> fieldBase) + - 2*uint64(val.n[0])*uint64(val.n[7]) + - 2*uint64(val.n[1])*uint64(val.n[6]) + - 2*uint64(val.n[2])*uint64(val.n[5]) + - 2*uint64(val.n[3])*uint64(val.n[4]) - t7 := m & fieldBaseMask - - // Terms for 2^(fieldBase*8). - m = (m >> fieldBase) + - 2*uint64(val.n[0])*uint64(val.n[8]) + - 2*uint64(val.n[1])*uint64(val.n[7]) + - 2*uint64(val.n[2])*uint64(val.n[6]) + - 2*uint64(val.n[3])*uint64(val.n[5]) + - uint64(val.n[4])*uint64(val.n[4]) - t8 := m & fieldBaseMask - - // Terms for 2^(fieldBase*9). - m = (m >> fieldBase) + - 2*uint64(val.n[0])*uint64(val.n[9]) + - 2*uint64(val.n[1])*uint64(val.n[8]) + - 2*uint64(val.n[2])*uint64(val.n[7]) + - 2*uint64(val.n[3])*uint64(val.n[6]) + - 2*uint64(val.n[4])*uint64(val.n[5]) - t9 := m & fieldBaseMask - - // Terms for 2^(fieldBase*10). - m = (m >> fieldBase) + - 2*uint64(val.n[1])*uint64(val.n[9]) + - 2*uint64(val.n[2])*uint64(val.n[8]) + - 2*uint64(val.n[3])*uint64(val.n[7]) + - 2*uint64(val.n[4])*uint64(val.n[6]) + - uint64(val.n[5])*uint64(val.n[5]) - t10 := m & fieldBaseMask - - // Terms for 2^(fieldBase*11). - m = (m >> fieldBase) + - 2*uint64(val.n[2])*uint64(val.n[9]) + - 2*uint64(val.n[3])*uint64(val.n[8]) + - 2*uint64(val.n[4])*uint64(val.n[7]) + - 2*uint64(val.n[5])*uint64(val.n[6]) - t11 := m & fieldBaseMask - - // Terms for 2^(fieldBase*12). - m = (m >> fieldBase) + - 2*uint64(val.n[3])*uint64(val.n[9]) + - 2*uint64(val.n[4])*uint64(val.n[8]) + - 2*uint64(val.n[5])*uint64(val.n[7]) + - uint64(val.n[6])*uint64(val.n[6]) - t12 := m & fieldBaseMask - - // Terms for 2^(fieldBase*13). - m = (m >> fieldBase) + - 2*uint64(val.n[4])*uint64(val.n[9]) + - 2*uint64(val.n[5])*uint64(val.n[8]) + - 2*uint64(val.n[6])*uint64(val.n[7]) - t13 := m & fieldBaseMask - - // Terms for 2^(fieldBase*14). - m = (m >> fieldBase) + - 2*uint64(val.n[5])*uint64(val.n[9]) + - 2*uint64(val.n[6])*uint64(val.n[8]) + - uint64(val.n[7])*uint64(val.n[7]) - t14 := m & fieldBaseMask - - // Terms for 2^(fieldBase*15). - m = (m >> fieldBase) + - 2*uint64(val.n[6])*uint64(val.n[9]) + - 2*uint64(val.n[7])*uint64(val.n[8]) - t15 := m & fieldBaseMask - - // Terms for 2^(fieldBase*16). - m = (m >> fieldBase) + - 2*uint64(val.n[7])*uint64(val.n[9]) + - uint64(val.n[8])*uint64(val.n[8]) - t16 := m & fieldBaseMask - - // Terms for 2^(fieldBase*17). - m = (m >> fieldBase) + 2*uint64(val.n[8])*uint64(val.n[9]) - t17 := m & fieldBaseMask - - // Terms for 2^(fieldBase*18). - m = (m >> fieldBase) + uint64(val.n[9])*uint64(val.n[9]) - t18 := m & fieldBaseMask - - // What's left is for 2^(fieldBase*19). - t19 := m >> fieldBase - - // At this point, all of the terms are grouped into their respective - // base. - // - // Per [HAC] section 14.3.4: Reduction method of moduli of special form, - // when the modulus is of the special form m = b^t - c, highly efficient - // reduction can be achieved per the provided algorithm. - // - // The secp256k1 prime is equivalent to 2^256 - 4294968273, so it fits - // this criteria. - // - // 4294968273 in field representation (base 2^26) is: - // n[0] = 977 - // n[1] = 64 - // That is to say (2^26 * 64) + 977 = 4294968273 - // - // Since each word is in base 26, the upper terms (t10 and up) start - // at 260 bits (versus the final desired range of 256 bits), so the - // field representation of 'c' from above needs to be adjusted for the - // extra 4 bits by multiplying it by 2^4 = 16. 4294968273 * 16 = - // 68719492368. Thus, the adjusted field representation of 'c' is: - // n[0] = 977 * 16 = 15632 - // n[1] = 64 * 16 = 1024 - // That is to say (2^26 * 1024) + 15632 = 68719492368 - // - // To reduce the final term, t19, the entire 'c' value is needed instead - // of only n[0] because there are no more terms left to handle n[1]. - // This means there might be some magnitude left in the upper bits that - // is handled below. - m = t0 + t10*15632 - t0 = m & fieldBaseMask - m = (m >> fieldBase) + t1 + t10*1024 + t11*15632 - t1 = m & fieldBaseMask - m = (m >> fieldBase) + t2 + t11*1024 + t12*15632 - t2 = m & fieldBaseMask - m = (m >> fieldBase) + t3 + t12*1024 + t13*15632 - t3 = m & fieldBaseMask - m = (m >> fieldBase) + t4 + t13*1024 + t14*15632 - t4 = m & fieldBaseMask - m = (m >> fieldBase) + t5 + t14*1024 + t15*15632 - t5 = m & fieldBaseMask - m = (m >> fieldBase) + t6 + t15*1024 + t16*15632 - t6 = m & fieldBaseMask - m = (m >> fieldBase) + t7 + t16*1024 + t17*15632 - t7 = m & fieldBaseMask - m = (m >> fieldBase) + t8 + t17*1024 + t18*15632 - t8 = m & fieldBaseMask - m = (m >> fieldBase) + t9 + t18*1024 + t19*68719492368 - t9 = m & fieldMSBMask - m = m >> fieldMSBBits - - // At this point, if the magnitude is greater than 0, the overall value - // is greater than the max possible 256-bit value. In particular, it is - // "how many times larger" than the max value it is. - // - // The algorithm presented in [HAC] section 14.3.4 repeats until the - // quotient is zero. However, due to the above, we already know at - // least how many times we would need to repeat as it's the value - // currently in m. Thus we can simply multiply the magnitude by the - // field representation of the prime and do a single iteration. Notice - // that nothing will be changed when the magnitude is zero, so we could - // skip this in that case, however always running regardless allows it - // to run in constant time. The final result will be in the range - // 0 <= result <= prime + (2^64 - c), so it is guaranteed to have a - // magnitude of 1, but it is denormalized. - n := t0 + m*977 - f.n[0] = uint32(n & fieldBaseMask) - n = (n >> fieldBase) + t1 + m*64 - f.n[1] = uint32(n & fieldBaseMask) - f.n[2] = uint32((n >> fieldBase) + t2) - f.n[3] = uint32(t3) - f.n[4] = uint32(t4) - f.n[5] = uint32(t5) - f.n[6] = uint32(t6) - f.n[7] = uint32(t7) - f.n[8] = uint32(t8) - f.n[9] = uint32(t9) - - return f -} - -// Inverse finds the modular multiplicative inverse of the field value. The -// existing field value is modified. -// -// The field value is returned to support chaining. This enables syntax like: -// f.Inverse().Mul(f2) so that f = f^-1 * f2. -func (f *fieldVal) Inverse() *fieldVal { - // Fermat's little theorem states that for a nonzero number a and prime - // prime p, a^(p-1) = 1 (mod p). Since the multipliciative inverse is - // a*b = 1 (mod p), it follows that b = a*a^(p-2) = a^(p-1) = 1 (mod p). - // Thus, a^(p-2) is the multiplicative inverse. - // - // In order to efficiently compute a^(p-2), p-2 needs to be split into - // a sequence of squares and multipications that minimizes the number of - // multiplications needed (since they are more costly than squarings). - // Intermediate results are saved and reused as well. - // - // The secp256k1 prime - 2 is 2^256 - 4294968275. - // - // This has a cost of 258 field squarings and 33 field multiplications. - var a2, a3, a4, a10, a11, a21, a42, a45, a63, a1019, a1023 fieldVal - a2.SquareVal(f) - a3.Mul2(&a2, f) - a4.SquareVal(&a2) - a10.SquareVal(&a4).Mul(&a2) - a11.Mul2(&a10, f) - a21.Mul2(&a10, &a11) - a42.SquareVal(&a21) - a45.Mul2(&a42, &a3) - a63.Mul2(&a42, &a21) - a1019.SquareVal(&a63).Square().Square().Square().Mul(&a11) - a1023.Mul2(&a1019, &a4) - f.Set(&a63) // f = a^(2^6 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^11 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^16 - 1024) - f.Mul(&a1023) // f = a^(2^16 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^21 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^26 - 1024) - f.Mul(&a1023) // f = a^(2^26 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^31 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^36 - 1024) - f.Mul(&a1023) // f = a^(2^36 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^41 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^46 - 1024) - f.Mul(&a1023) // f = a^(2^46 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^51 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^56 - 1024) - f.Mul(&a1023) // f = a^(2^56 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^61 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^66 - 1024) - f.Mul(&a1023) // f = a^(2^66 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^71 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^76 - 1024) - f.Mul(&a1023) // f = a^(2^76 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^81 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^86 - 1024) - f.Mul(&a1023) // f = a^(2^86 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^91 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^96 - 1024) - f.Mul(&a1023) // f = a^(2^96 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^101 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^106 - 1024) - f.Mul(&a1023) // f = a^(2^106 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^111 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^116 - 1024) - f.Mul(&a1023) // f = a^(2^116 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^121 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^126 - 1024) - f.Mul(&a1023) // f = a^(2^126 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^131 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^136 - 1024) - f.Mul(&a1023) // f = a^(2^136 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^141 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^146 - 1024) - f.Mul(&a1023) // f = a^(2^146 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^151 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^156 - 1024) - f.Mul(&a1023) // f = a^(2^156 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^161 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^166 - 1024) - f.Mul(&a1023) // f = a^(2^166 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^171 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^176 - 1024) - f.Mul(&a1023) // f = a^(2^176 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^181 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^186 - 1024) - f.Mul(&a1023) // f = a^(2^186 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^191 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^196 - 1024) - f.Mul(&a1023) // f = a^(2^196 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^201 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^206 - 1024) - f.Mul(&a1023) // f = a^(2^206 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^211 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^216 - 1024) - f.Mul(&a1023) // f = a^(2^216 - 1) - f.Square().Square().Square().Square().Square() // f = a^(2^221 - 32) - f.Square().Square().Square().Square().Square() // f = a^(2^226 - 1024) - f.Mul(&a1019) // f = a^(2^226 - 5) - f.Square().Square().Square().Square().Square() // f = a^(2^231 - 160) - f.Square().Square().Square().Square().Square() // f = a^(2^236 - 5120) - f.Mul(&a1023) // f = a^(2^236 - 4097) - f.Square().Square().Square().Square().Square() // f = a^(2^241 - 131104) - f.Square().Square().Square().Square().Square() // f = a^(2^246 - 4195328) - f.Mul(&a1023) // f = a^(2^246 - 4194305) - f.Square().Square().Square().Square().Square() // f = a^(2^251 - 134217760) - f.Square().Square().Square().Square().Square() // f = a^(2^256 - 4294968320) - return f.Mul(&a45) // f = a^(2^256 - 4294968275) = a^(p-2) -} - -// SqrtVal computes the square root of x modulo the curve's prime, and stores -// the result in f. The square root is computed via exponentiation of x by the -// value Q = (P+1)/4 using the curve's precomputed big-endian representation of -// the Q. This method uses a modified version of square-and-multiply -// exponentiation over secp256k1 fieldVals to operate on bytes instead of bits, -// which offers better performance over both big.Int exponentiation and bit-wise -// square-and-multiply. -// -// NOTE: This method only works when P is intended to be the secp256k1 prime and -// is not constant time. The returned value is of magnitude 1, but is -// denormalized. -func (f *fieldVal) SqrtVal(x *fieldVal) *fieldVal { - // The following computation iteratively computes x^((P+1)/4) = x^Q - // using the recursive, piece-wise definition: - // - // x^n = (x^2)^(n/2) mod P if n is even - // x^n = x(x^2)^(n-1/2) mod P if n is odd - // - // Given n in its big-endian representation b_k, ..., b_0, x^n can be - // computed by defining the sequence r_k+1, ..., r_0, where: - // - // r_k+1 = 1 - // r_i = (r_i+1)^2 * x^b_i for i = k, ..., 0 - // - // The final value r_0 = x^n. - // - // See https://en.wikipedia.org/wiki/Exponentiation_by_squaring for more - // details. - // - // This can be further optimized, by observing that the value of Q in - // secp256k1 has the value: - // - // Q = 3fffffffffffffffffffffffffffffffffffffffffffffffffffffffbfffff0c - // - // We can unroll the typical bit-wise interpretation of the - // exponentiation algorithm above to instead operate on bytes. - // This reduces the number of comparisons by an order of magnitude, - // reducing the overhead of failed branch predictions and additional - // comparisons in this method. - // - // Since there there are only 4 unique bytes of Q, this keeps the jump - // table small without the need to handle all possible 8-bit values. - // Further, we observe that 29 of the 32 bytes are 0xff; making the - // first case handle 0xff therefore optimizes the hot path. - f.SetInt(1) - for _, b := range fieldQBytes { - switch b { - - // Most common case, where all 8 bits are set. - case 0xff: - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - - // First byte of Q (0x3f), where all but the top two bits are - // set. Note that this case only applies six operations, since - // the highest bit of Q resides in bit six of the first byte. We - // ignore the first two bits, since squaring for these bits will - // result in an invalid result. We forgo squaring f before the - // first multiply, since 1^2 = 1. - case 0x3f: - f.Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - - // Byte 28 of Q (0xbf), where only bit 7 is unset. - case 0xbf: - f.Square().Mul(x) - f.Square() - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - f.Square().Mul(x) - - // Byte 31 of Q (0x0c), where only bits 3 and 4 are set. - default: - f.Square() - f.Square() - f.Square() - f.Square() - f.Square().Mul(x) - f.Square().Mul(x) - f.Square() - f.Square() - } - } - - return f -} - -// Sqrt computes the square root of f modulo the curve's prime, and stores the -// result in f. The square root is computed via exponentiation of x by the value -// Q = (P+1)/4 using the curve's precomputed big-endian representation of the Q. -// This method uses a modified version of square-and-multiply exponentiation -// over secp256k1 fieldVals to operate on bytes instead of bits, which offers -// better performance over both big.Int exponentiation and bit-wise -// square-and-multiply. -// -// NOTE: This method only works when P is intended to be the secp256k1 prime and -// is not constant time. The returned value is of magnitude 1, but is -// denormalized. -func (f *fieldVal) Sqrt() *fieldVal { - return f.SqrtVal(f) -} +// IMPORTANT: The max allowed magnitude of a field value is 64. +type FieldVal = secp.FieldVal diff --git a/btcec/field_test.go b/btcec/field_test.go index 4226ba55..6ade97a1 100644 --- a/btcec/field_test.go +++ b/btcec/field_test.go @@ -6,70 +6,30 @@ package btcec import ( - "crypto/rand" + "math/rand" + "encoding/hex" - "fmt" - "reflect" "testing" ) -// TestSetInt ensures that setting a field value to various native integers -// works as expected. -func TestSetInt(t *testing.T) { - tests := []struct { - in uint - raw [10]uint32 - }{ - {5, [10]uint32{5, 0, 0, 0, 0, 0, 0, 0, 0, 0}}, - // 2^26 - {67108864, [10]uint32{67108864, 0, 0, 0, 0, 0, 0, 0, 0, 0}}, - // 2^26 + 1 - {67108865, [10]uint32{67108865, 0, 0, 0, 0, 0, 0, 0, 0, 0}}, - // 2^32 - 1 - {4294967295, [10]uint32{4294967295, 0, 0, 0, 0, 0, 0, 0, 0, 0}}, - } - - t.Logf("Running %d tests", len(tests)) - for i, test := range tests { - f := new(fieldVal).SetInt(test.in) - if !reflect.DeepEqual(f.n, test.raw) { - t.Errorf("fieldVal.Set #%d wrong result\ngot: %v\n"+ - "want: %v", i, f.n, test.raw) - continue - } - } -} - -// TestZero ensures that zeroing a field value zero works as expected. -func TestZero(t *testing.T) { - f := new(fieldVal).SetInt(2) - f.Zero() - for idx, rawInt := range f.n { - if rawInt != 0 { - t.Errorf("internal field integer at index #%d is not "+ - "zero - got %d", idx, rawInt) - } - } -} - // TestIsZero ensures that checking if a field IsZero works as expected. func TestIsZero(t *testing.T) { - f := new(fieldVal) + f := new(FieldVal) if !f.IsZero() { t.Errorf("new field value is not zero - got %v (rawints %x)", f, - f.n) + f.String()) } f.SetInt(1) if f.IsZero() { t.Errorf("field claims it's zero when it's not - got %v "+ - "(raw rawints %x)", f, f.n) + "(raw rawints %x)", f, f.String()) } f.Zero() if !f.IsZero() { t.Errorf("field claims it's not zero when it is - got %v "+ - "(raw rawints %x)", f, f.n) + "(raw rawints %x)", f, f.String()) } } @@ -147,10 +107,10 @@ func TestStringer(t *testing.T) { t.Logf("Running %d tests", len(tests)) for i, test := range tests { - f := new(fieldVal).SetHex(test.in) + f := setHex(test.in) result := f.String() if result != test.expected { - t.Errorf("fieldVal.String #%d wrong result\ngot: %v\n"+ + t.Errorf("FieldVal.String #%d wrong result\ngot: %v\n"+ "want: %v", i, result, test.expected) continue } @@ -313,15 +273,16 @@ func TestNormalize(t *testing.T) { } t.Logf("Running %d tests", len(tests)) - for i, test := range tests { - f := new(fieldVal) + for range tests { + // TODO(roasbeef): can't access internal state + /*f := new(FieldVal) f.n = test.raw f.Normalize() if !reflect.DeepEqual(f.n, test.normalized) { - t.Errorf("fieldVal.Normalize #%d wrong result\n"+ + t.Errorf("FieldVal.Normalize #%d wrong result\n"+ "got: %x\nwant: %x", i, f.n, test.normalized) continue - } + }*/ } } @@ -344,10 +305,10 @@ func TestIsOdd(t *testing.T) { t.Logf("Running %d tests", len(tests)) for i, test := range tests { - f := new(fieldVal).SetHex(test.in) + f := setHex(test.in) result := f.IsOdd() if result != test.expected { - t.Errorf("fieldVal.IsOdd #%d wrong result\n"+ + t.Errorf("FieldVal.IsOdd #%d wrong result\n"+ "got: %v\nwant: %v", i, result, test.expected) continue } @@ -377,11 +338,11 @@ func TestEquals(t *testing.T) { t.Logf("Running %d tests", len(tests)) for i, test := range tests { - f := new(fieldVal).SetHex(test.in1).Normalize() - f2 := new(fieldVal).SetHex(test.in2).Normalize() + f := setHex(test.in1).Normalize() + f2 := setHex(test.in2).Normalize() result := f.Equals(f2) if result != test.expected { - t.Errorf("fieldVal.Equals #%d wrong result\n"+ + t.Errorf("FieldVal.Equals #%d wrong result\n"+ "got: %v\nwant: %v", i, result, test.expected) continue } @@ -425,347 +386,419 @@ func TestNegate(t *testing.T) { t.Logf("Running %d tests", len(tests)) for i, test := range tests { - f := new(fieldVal).SetHex(test.in).Normalize() - expected := new(fieldVal).SetHex(test.expected).Normalize() + f := setHex(test.in).Normalize() + expected := setHex(test.expected).Normalize() result := f.Negate(1).Normalize() if !result.Equals(expected) { - t.Errorf("fieldVal.Negate #%d wrong result\n"+ + t.Errorf("FieldVal.Negate #%d wrong result\n"+ "got: %v\nwant: %v", i, result, expected) continue } } } -// TestAddInt ensures that adding an integer to field values via AddInt works as -// expected. -func TestAddInt(t *testing.T) { +// TestFieldAddInt ensures that adding an integer to field values via AddInt +// works as expected. +func TestFieldAddInt(t *testing.T) { tests := []struct { + name string // test description in1 string // hex encoded value - in2 uint // unsigned integer to add to the value above + in2 uint16 // unsigned integer to add to the value above expected string // expected hex encoded value - }{ - {"0", 1, "1"}, - {"1", 0, "1"}, - {"1", 1, "2"}, - // secp256k1 prime-1 + 1 - {"fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", 1, "0"}, - // secp256k1 prime + 1 - {"fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", 1, "1"}, - // Random samples. - { - "ff95ad9315aff04ab4af0ce673620c7145dc85d03bab5ba4b09ca2c4dec2d6c1", - 0x10f, - "ff95ad9315aff04ab4af0ce673620c7145dc85d03bab5ba4b09ca2c4dec2d7d0", - }, - { - "44bdae6b772e7987941f1ba314e6a5b7804a4c12c00961b57d20f41deea9cecf", - 0x2cf11d41, - "44bdae6b772e7987941f1ba314e6a5b7804a4c12c00961b57d20f41e1b9aec10", - }, - { - "88c3ecae67b591935fb1f6a9499c35315ffad766adca665c50b55f7105122c9c", - 0x4829aa2d, - "88c3ecae67b591935fb1f6a9499c35315ffad766adca665c50b55f714d3bd6c9", - }, - { - "8523e9edf360ca32a95aae4e57fcde5a542b471d08a974d94ea0ee09a015e2a6", - 0xa21265a5, - "8523e9edf360ca32a95aae4e57fcde5a542b471d08a974d94ea0ee0a4228484b", - }, - } + }{{ + name: "zero + one", + in1: "0", + in2: 1, + expected: "1", + }, { + name: "one + zero", + in1: "1", + in2: 0, + expected: "1", + }, { + name: "one + one", + in1: "1", + in2: 1, + expected: "2", + }, { + name: "secp256k1 prime-1 + 1", + in1: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", + in2: 1, + expected: "0", + }, { + name: "secp256k1 prime + 1", + in1: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", + in2: 1, + expected: "1", + }, { + name: "random sampling #1", + in1: "ff95ad9315aff04ab4af0ce673620c7145dc85d03bab5ba4b09ca2c4dec2d6c1", + in2: 0x10f, + expected: "ff95ad9315aff04ab4af0ce673620c7145dc85d03bab5ba4b09ca2c4dec2d7d0", + }, { + name: "random sampling #2", + in1: "44bdae6b772e7987941f1ba314e6a5b7804a4c12c00961b57d20f41deea9cecf", + in2: 0x3196, + expected: "44bdae6b772e7987941f1ba314e6a5b7804a4c12c00961b57d20f41deeaa0065", + }, { + name: "random sampling #3", + in1: "88c3ecae67b591935fb1f6a9499c35315ffad766adca665c50b55f7105122c9c", + in2: 0x966f, + expected: "88c3ecae67b591935fb1f6a9499c35315ffad766adca665c50b55f710512c30b", + }, { + name: "random sampling #4", + in1: "8523e9edf360ca32a95aae4e57fcde5a542b471d08a974d94ea0ee09a015e2a6", + in2: 0xc54, + expected: "8523e9edf360ca32a95aae4e57fcde5a542b471d08a974d94ea0ee09a015eefa", + }} - t.Logf("Running %d tests", len(tests)) - for i, test := range tests { - f := new(fieldVal).SetHex(test.in1).Normalize() - expected := new(fieldVal).SetHex(test.expected).Normalize() + for _, test := range tests { + f := setHex(test.in1).Normalize() + expected := setHex(test.expected).Normalize() result := f.AddInt(test.in2).Normalize() if !result.Equals(expected) { - t.Errorf("fieldVal.AddInt #%d wrong result\n"+ - "got: %v\nwant: %v", i, result, expected) + t.Errorf("%s: wrong result -- got: %v -- want: %v", test.name, + result, expected) continue } } } -// TestAdd ensures that adding two field values together via Add works as -// expected. -func TestAdd(t *testing.T) { +// TestFieldAdd ensures that adding two field values together via Add and Add2 +// works as expected. +func TestFieldAdd(t *testing.T) { tests := []struct { + name string // test description in1 string // first hex encoded value in2 string // second hex encoded value to add expected string // expected hex encoded value - }{ - {"0", "1", "1"}, - {"1", "0", "1"}, - {"1", "1", "2"}, - // secp256k1 prime-1 + 1 - {"fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", "1", "0"}, - // secp256k1 prime + 1 - {"fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", "1", "1"}, - // Random samples. - { - "2b2012f975404e5065b4292fb8bed0a5d315eacf24c74d8b27e73bcc5430edcc", - "2c3cefa4e4753e8aeec6ac4c12d99da4d78accefda3b7885d4c6bab46c86db92", - "575d029e59b58cdb547ad57bcb986e4aaaa0b7beff02c610fcadf680c0b7c95e", - }, - { - "8131e8722fe59bb189692b96c9f38de92885730f1dd39ab025daffb94c97f79c", - "ff5454b765f0aab5f0977dcc629becc84cabeb9def48e79c6aadb2622c490fa9", - "80863d2995d646677a00a9632c8f7ab175315ead0d1c824c9088b21c78e10b16", - }, - { - "c7c95e93d0892b2b2cdd77e80eb646ea61be7a30ac7e097e9f843af73fad5c22", - "3afe6f91a74dfc1c7f15c34907ee981656c37236d946767dd53ccad9190e437c", - "02c7ce2577d72747abf33b3116a4df00b881ec6785c47ffc74c105d158bba36f", - }, - { - "fd1c26f6a23381e5d785ba889494ec059369b888ad8431cd67d8c934b580dbe1", - "a475aa5a31dcca90ef5b53c097d9133d6b7117474b41e7877bb199590fc0489c", - "a191d150d4104c76c6e10e492c6dff42fedacfcff8c61954e38a628ec541284e", - }, - } + }{{ + name: "zero + one", + in1: "0", + in2: "1", + expected: "1", + }, { + name: "one + zero", + in1: "1", + in2: "0", + expected: "1", + }, { + name: "secp256k1 prime-1 + 1", + in1: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", + in2: "1", + expected: "0", + }, { + name: "secp256k1 prime + 1", + in1: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", + in2: "1", + expected: "1", + }, { + name: "random sampling #1", + in1: "2b2012f975404e5065b4292fb8bed0a5d315eacf24c74d8b27e73bcc5430edcc", + in2: "2c3cefa4e4753e8aeec6ac4c12d99da4d78accefda3b7885d4c6bab46c86db92", + expected: "575d029e59b58cdb547ad57bcb986e4aaaa0b7beff02c610fcadf680c0b7c95e", + }, { + name: "random sampling #2", + in1: "8131e8722fe59bb189692b96c9f38de92885730f1dd39ab025daffb94c97f79c", + in2: "ff5454b765f0aab5f0977dcc629becc84cabeb9def48e79c6aadb2622c490fa9", + expected: "80863d2995d646677a00a9632c8f7ab175315ead0d1c824c9088b21c78e10b16", + }, { + name: "random sampling #3", + in1: "c7c95e93d0892b2b2cdd77e80eb646ea61be7a30ac7e097e9f843af73fad5c22", + in2: "3afe6f91a74dfc1c7f15c34907ee981656c37236d946767dd53ccad9190e437c", + expected: "2c7ce2577d72747abf33b3116a4df00b881ec6785c47ffc74c105d158bba36f", + }, { + name: "random sampling #4", + in1: "fd1c26f6a23381e5d785ba889494ec059369b888ad8431cd67d8c934b580dbe1", + in2: "a475aa5a31dcca90ef5b53c097d9133d6b7117474b41e7877bb199590fc0489c", + expected: "a191d150d4104c76c6e10e492c6dff42fedacfcff8c61954e38a628ec541284e", + }, { + name: "random sampling #5", + in1: "ad82b8d1cc136e23e9fd77fe2c7db1fe5a2ecbfcbde59ab3529758334f862d28", + in2: "4d6a4e95d6d61f4f46b528bebe152d408fd741157a28f415639347a84f6f574b", + expected: "faed0767a2e98d7330b2a0bcea92df3eea060d12380e8ec8b62a9fdb9ef58473", + }, { + name: "random sampling #6", + in1: "f3f43a2540054a86e1df98547ec1c0e157b193e5350fb4a3c3ea214b228ac5e7", + in2: "25706572592690ea3ddc951a1b48b504a4c83dc253756e1b96d56fdfb3199522", + expected: "19649f97992bdb711fbc2d6e9a0a75e5fc79d1a7888522bf5abf912bd5a45eda", + }, { + name: "random sampling #7", + in1: "6915bb94eef13ff1bb9b2633d997e13b9b1157c713363cc0e891416d6734f5b8", + in2: "11f90d6ac6fe1c4e8900b1c85fb575c251ec31b9bc34b35ada0aea1c21eded22", + expected: "7b0ec8ffb5ef5c40449bd7fc394d56fdecfd8980cf6af01bc29c2b898922e2da", + }, { + name: "random sampling #8", + in1: "48b0c9eae622eed9335b747968544eb3e75cb2dc8128388f948aa30f88cabde4", + in2: "0989882b52f85f9d524a3a3061a0e01f46d597839d2ba637320f4b9510c8d2d5", + expected: "523a5216391b4e7685a5aea9c9f52ed32e324a601e53dec6c699eea4999390b9", + }} - t.Logf("Running %d tests", len(tests)) - for i, test := range tests { - f := new(fieldVal).SetHex(test.in1).Normalize() - f2 := new(fieldVal).SetHex(test.in2).Normalize() - expected := new(fieldVal).SetHex(test.expected).Normalize() - result := f.Add(f2).Normalize() + for _, test := range tests { + // Parse test hex. + f1 := setHex(test.in1).Normalize() + f2 := setHex(test.in2).Normalize() + expected := setHex(test.expected).Normalize() + + // Ensure adding the two values with the result going to another + // variable produces the expected result. + result := new(FieldVal).Add2(f1, f2).Normalize() if !result.Equals(expected) { - t.Errorf("fieldVal.Add #%d wrong result\n"+ - "got: %v\nwant: %v", i, result, expected) + t.Errorf("%s: unexpected result\ngot: %v\nwant: %v", test.name, + result, expected) + continue + } + + // Ensure adding the value to an existing field value produces the + // expected result. + f1.Add(f2).Normalize() + if !f1.Equals(expected) { + t.Errorf("%s: unexpected result\ngot: %v\nwant: %v", test.name, + f1, expected) continue } } } -// TestAdd2 ensures that adding two field values together via Add2 works as -// expected. -func TestAdd2(t *testing.T) { - tests := []struct { - in1 string // first hex encoded value - in2 string // second hex encoded value to add - expected string // expected hex encoded value - }{ - {"0", "1", "1"}, - {"1", "0", "1"}, - {"1", "1", "2"}, - // secp256k1 prime-1 + 1 - {"fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", "1", "0"}, - // secp256k1 prime + 1 - {"fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", "1", "1"}, - // close but over the secp256k1 prime - {"fffffffffffffffffffffffffffffffffffffffffffffffffffffff000000000", "f1ffff000", "1ffff3d1"}, - // Random samples. - { - "ad82b8d1cc136e23e9fd77fe2c7db1fe5a2ecbfcbde59ab3529758334f862d28", - "4d6a4e95d6d61f4f46b528bebe152d408fd741157a28f415639347a84f6f574b", - "faed0767a2e98d7330b2a0bcea92df3eea060d12380e8ec8b62a9fdb9ef58473", - }, - { - "f3f43a2540054a86e1df98547ec1c0e157b193e5350fb4a3c3ea214b228ac5e7", - "25706572592690ea3ddc951a1b48b504a4c83dc253756e1b96d56fdfb3199522", - "19649f97992bdb711fbc2d6e9a0a75e5fc79d1a7888522bf5abf912bd5a45eda", - }, - { - "6915bb94eef13ff1bb9b2633d997e13b9b1157c713363cc0e891416d6734f5b8", - "11f90d6ac6fe1c4e8900b1c85fb575c251ec31b9bc34b35ada0aea1c21eded22", - "7b0ec8ffb5ef5c40449bd7fc394d56fdecfd8980cf6af01bc29c2b898922e2da", - }, - { - "48b0c9eae622eed9335b747968544eb3e75cb2dc8128388f948aa30f88cabde4", - "0989882b52f85f9d524a3a3061a0e01f46d597839d2ba637320f4b9510c8d2d5", - "523a5216391b4e7685a5aea9c9f52ed32e324a601e53dec6c699eea4999390b9", - }, - } - - t.Logf("Running %d tests", len(tests)) - for i, test := range tests { - f := new(fieldVal).SetHex(test.in1).Normalize() - f2 := new(fieldVal).SetHex(test.in2).Normalize() - expected := new(fieldVal).SetHex(test.expected).Normalize() - result := f.Add2(f, f2).Normalize() - if !result.Equals(expected) { - t.Errorf("fieldVal.Add2 #%d wrong result\n"+ - "got: %v\nwant: %v", i, result, expected) - continue - } - } -} - -// TestMulInt ensures that adding an integer to field values via MulInt works as -// expected. -func TestMulInt(t *testing.T) { +// TestFieldMulInt ensures that multiplying an integer to field values via +// MulInt works as expected. +func TestFieldMulInt(t *testing.T) { tests := []struct { + name string // test description in1 string // hex encoded value - in2 uint // unsigned integer to multiply with value above + in2 uint8 // unsigned integer to multiply with value above expected string // expected hex encoded value - }{ - {"0", 0, "0"}, - {"1", 0, "0"}, - {"0", 1, "0"}, - {"1", 1, "1"}, - // secp256k1 prime-1 * 2 - { - "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", - 2, - "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2d", - }, - // secp256k1 prime * 3 - {"fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", 3, "0"}, - // secp256k1 prime-1 * 8 - { - "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", - 8, - "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc27", - }, + }{{ + name: "zero * zero", + in1: "0", + in2: 0, + expected: "0", + }, { + name: "one * zero", + in1: "1", + in2: 0, + expected: "0", + }, { + name: "zero * one", + in1: "0", + in2: 1, + expected: "0", + }, { + name: "one * one", + in1: "1", + in2: 1, + expected: "1", + }, { + name: "secp256k1 prime-1 * 2", + in1: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", + in2: 2, + expected: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2d", + }, { + name: "secp256k1 prime * 3", + in1: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", + in2: 3, + expected: "0", + }, { + name: "secp256k1 prime-1 * 8", + in1: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", + in2: 8, + expected: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc27", + }, { // Random samples for first value. The second value is limited // to 8 since that is the maximum int used in the elliptic curve // calculations. - { - "b75674dc9180d306c692163ac5e089f7cef166af99645c0c23568ab6d967288a", - 6, - "4c06bd2b6904f228a76c8560a3433bced9a8681d985a2848d407404d186b0280", - }, - { - "54873298ac2b5ba8591c125ae54931f5ea72040aee07b208d6135476fb5b9c0e", - 3, - "fd9597ca048212f90b543710afdb95e1bf560c20ca17161a8239fd64f212d42a", - }, - { - "7c30fbd363a74c17e1198f56b090b59bbb6c8755a74927a6cba7a54843506401", - 5, - "6cf4eb20f2447c77657fccb172d38c0aa91ea4ac446dc641fa463a6b5091fba7", - }, - { - "fb4529be3e027a3d1587d8a500b72f2d312e3577340ef5175f96d113be4c2ceb", - 8, - "da294df1f013d1e8ac3ec52805b979698971abb9a077a8bafcb688a4f261820f", - }, - } + name: "random sampling #1", + in1: "b75674dc9180d306c692163ac5e089f7cef166af99645c0c23568ab6d967288a", + in2: 6, + expected: "4c06bd2b6904f228a76c8560a3433bced9a8681d985a2848d407404d186b0280", + }, { + name: "random sampling #2", + in1: "54873298ac2b5ba8591c125ae54931f5ea72040aee07b208d6135476fb5b9c0e", + in2: 3, + expected: "fd9597ca048212f90b543710afdb95e1bf560c20ca17161a8239fd64f212d42a", + }, { + name: "random sampling #3", + in1: "7c30fbd363a74c17e1198f56b090b59bbb6c8755a74927a6cba7a54843506401", + in2: 5, + expected: "6cf4eb20f2447c77657fccb172d38c0aa91ea4ac446dc641fa463a6b5091fba7", + }, { + name: "random sampling #3", + in1: "fb4529be3e027a3d1587d8a500b72f2d312e3577340ef5175f96d113be4c2ceb", + in2: 8, + expected: "da294df1f013d1e8ac3ec52805b979698971abb9a077a8bafcb688a4f261820f", + }} - t.Logf("Running %d tests", len(tests)) - for i, test := range tests { - f := new(fieldVal).SetHex(test.in1).Normalize() - expected := new(fieldVal).SetHex(test.expected).Normalize() + for _, test := range tests { + f := setHex(test.in1).Normalize() + expected := setHex(test.expected).Normalize() result := f.MulInt(test.in2).Normalize() if !result.Equals(expected) { - t.Errorf("fieldVal.MulInt #%d wrong result\n"+ - "got: %v\nwant: %v", i, result, expected) + t.Errorf("%s: wrong result -- got: %v -- want: %v", test.name, + result, expected) continue } } } -// TestMul ensures that multiplying two field valuess via Mul works as expected. -func TestMul(t *testing.T) { +// TestFieldMul ensures that multiplying two field values via Mul and Mul2 works +// as expected. +func TestFieldMul(t *testing.T) { tests := []struct { + name string // test description in1 string // first hex encoded value in2 string // second hex encoded value to multiply with expected string // expected hex encoded value - }{ - {"0", "0", "0"}, - {"1", "0", "0"}, - {"0", "1", "0"}, - {"1", "1", "1"}, - // slightly over prime - { - "ffffffffffffffffffffffffffffffffffffffffffffffffffffffff1ffff", - "1000", - "1ffff3d1", - }, - // secp256k1 prime-1 * 2 - { - "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", - "2", - "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2d", - }, - // secp256k1 prime * 3 - {"fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", "3", "0"}, - // secp256k1 prime-1 * 8 - { - "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", - "8", - "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc27", - }, - // Random samples. - { - "cfb81753d5ef499a98ecc04c62cb7768c2e4f1740032946db1c12e405248137e", - "58f355ad27b4d75fb7db0442452e732c436c1f7c5a7c4e214fa9cc031426a7d3", - "1018cd2d7c2535235b71e18db9cd98027386328d2fa6a14b36ec663c4c87282b", - }, - { - "26e9d61d1cdf3920e9928e85fa3df3e7556ef9ab1d14ec56d8b4fc8ed37235bf", - "2dfc4bbe537afee979c644f8c97b31e58be5296d6dbc460091eae630c98511cf", - "da85f48da2dc371e223a1ae63bd30b7e7ee45ae9b189ac43ff357e9ef8cf107a", - }, - { - "5db64ed5afb71646c8b231585d5b2bf7e628590154e0854c4c29920b999ff351", - "279cfae5eea5d09ade8e6a7409182f9de40981bc31c84c3d3dfe1d933f152e9a", - "2c78fbae91792dd0b157abe3054920049b1879a7cc9d98cfda927d83be411b37", - }, - { - "b66dfc1f96820b07d2bdbd559c19319a3a73c97ceb7b3d662f4fe75ecb6819e6", - "bf774aba43e3e49eb63a6e18037d1118152568f1a3ac4ec8b89aeb6ff8008ae1", - "c4f016558ca8e950c21c3f7fc15f640293a979c7b01754ee7f8b3340d4902ebb", - }, - } + }{{ + name: "zero * zero", + in1: "0", + in2: "0", + expected: "0", + }, { + name: "one * zero", + in1: "1", + in2: "0", + expected: "0", + }, { + name: "zero * one", + in1: "0", + in2: "1", + expected: "0", + }, { + name: "one * one", + in1: "1", + in2: "1", + expected: "1", + }, { + name: "slightly over prime", + in1: "ffffffffffffffffffffffffffffffffffffffffffffffffffffffff1ffff", + in2: "1000", + expected: "1ffff3d1", + }, { + name: "secp256k1 prime-1 * 2", + in1: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", + in2: "2", + expected: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2d", + }, { + name: "secp256k1 prime * 3", + in1: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", + in2: "3", + expected: "0", + }, { + name: "secp256k1 prime * 3", + in1: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", + in2: "8", + expected: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc27", + }, { + name: "random sampling #1", + in1: "cfb81753d5ef499a98ecc04c62cb7768c2e4f1740032946db1c12e405248137e", + in2: "58f355ad27b4d75fb7db0442452e732c436c1f7c5a7c4e214fa9cc031426a7d3", + expected: "1018cd2d7c2535235b71e18db9cd98027386328d2fa6a14b36ec663c4c87282b", + }, { + name: "random sampling #2", + in1: "26e9d61d1cdf3920e9928e85fa3df3e7556ef9ab1d14ec56d8b4fc8ed37235bf", + in2: "2dfc4bbe537afee979c644f8c97b31e58be5296d6dbc460091eae630c98511cf", + expected: "da85f48da2dc371e223a1ae63bd30b7e7ee45ae9b189ac43ff357e9ef8cf107a", + }, { + name: "random sampling #3", + in1: "5db64ed5afb71646c8b231585d5b2bf7e628590154e0854c4c29920b999ff351", + in2: "279cfae5eea5d09ade8e6a7409182f9de40981bc31c84c3d3dfe1d933f152e9a", + expected: "2c78fbae91792dd0b157abe3054920049b1879a7cc9d98cfda927d83be411b37", + }, { + name: "random sampling #4", + in1: "b66dfc1f96820b07d2bdbd559c19319a3a73c97ceb7b3d662f4fe75ecb6819e6", + in2: "bf774aba43e3e49eb63a6e18037d1118152568f1a3ac4ec8b89aeb6ff8008ae1", + expected: "c4f016558ca8e950c21c3f7fc15f640293a979c7b01754ee7f8b3340d4902ebb", + }} - t.Logf("Running %d tests", len(tests)) - for i, test := range tests { - f := new(fieldVal).SetHex(test.in1).Normalize() - f2 := new(fieldVal).SetHex(test.in2).Normalize() - expected := new(fieldVal).SetHex(test.expected).Normalize() - result := f.Mul(f2).Normalize() + for _, test := range tests { + f1 := setHex(test.in1).Normalize() + f2 := setHex(test.in2).Normalize() + expected := setHex(test.expected).Normalize() + + // Ensure multiplying the two values with the result going to another + // variable produces the expected result. + result := new(FieldVal).Mul2(f1, f2).Normalize() if !result.Equals(expected) { - t.Errorf("fieldVal.Mul #%d wrong result\n"+ - "got: %v\nwant: %v", i, result, expected) + t.Errorf("%s: unexpected result\ngot: %v\nwant: %v", test.name, + result, expected) + continue + } + + // Ensure multiplying the value to an existing field value produces the + // expected result. + f1.Mul(f2).Normalize() + if !f1.Equals(expected) { + t.Errorf("%s: unexpected result\ngot: %v\nwant: %v", test.name, + f1, expected) continue } } } -// TestSquare ensures that squaring field values via Square works as expected. -func TestSquare(t *testing.T) { +// TestFieldSquare ensures that squaring field values via Square and SqualVal +// works as expected. +func TestFieldSquare(t *testing.T) { tests := []struct { + name string // test description in string // hex encoded value expected string // expected hex encoded value - }{ - // secp256k1 prime (aka 0) - {"0", "0"}, - {"fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", "0"}, - {"0", "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f"}, - // secp256k1 prime-1 - {"fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", "1"}, - // secp256k1 prime-2 - {"fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2d", "4"}, - // Random sampling - { - "b0ba920360ea8436a216128047aab9766d8faf468895eb5090fc8241ec758896", - "133896b0b69fda8ce9f648b9a3af38f345290c9eea3cbd35bafcadf7c34653d3", - }, - { - "c55d0d730b1d0285a1599995938b042a756e6e8857d390165ffab480af61cbd5", - "cd81758b3f5877cbe7e5b0a10cebfa73bcbf0957ca6453e63ee8954ab7780bee", - }, - { - "e89c1f9a70d93651a1ba4bca5b78658f00de65a66014a25544d3365b0ab82324", - "39ffc7a43e5dbef78fd5d0354fb82c6d34f5a08735e34df29da14665b43aa1f", - }, - { - "7dc26186079d22bcbe1614aa20ae627e62d72f9be7ad1e99cac0feb438956f05", - "bf86bcfc4edb3d81f916853adfda80c07c57745b008b60f560b1912f95bce8ae", - }, - } + }{{ + name: "zero", + in: "0", + expected: "0", + }, { + name: "secp256k1 prime (direct val in with 0 out)", + in: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", + expected: "0", + }, { + name: "secp256k1 prime (0 in with direct val out)", + in: "0", + expected: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", + }, { + name: "secp256k1 prime - 1", + in: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", + expected: "1", + }, { + name: "secp256k1 prime - 2", + in: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2d", + expected: "4", + }, { + name: "random sampling #1", + in: "b0ba920360ea8436a216128047aab9766d8faf468895eb5090fc8241ec758896", + expected: "133896b0b69fda8ce9f648b9a3af38f345290c9eea3cbd35bafcadf7c34653d3", + }, { + name: "random sampling #2", + in: "c55d0d730b1d0285a1599995938b042a756e6e8857d390165ffab480af61cbd5", + expected: "cd81758b3f5877cbe7e5b0a10cebfa73bcbf0957ca6453e63ee8954ab7780bee", + }, { + name: "random sampling #3", + in: "e89c1f9a70d93651a1ba4bca5b78658f00de65a66014a25544d3365b0ab82324", + expected: "39ffc7a43e5dbef78fd5d0354fb82c6d34f5a08735e34df29da14665b43aa1f", + }, { + name: "random sampling #4", + in: "7dc26186079d22bcbe1614aa20ae627e62d72f9be7ad1e99cac0feb438956f05", + expected: "bf86bcfc4edb3d81f916853adfda80c07c57745b008b60f560b1912f95bce8ae", + }} - t.Logf("Running %d tests", len(tests)) - for i, test := range tests { - f := new(fieldVal).SetHex(test.in).Normalize() - expected := new(fieldVal).SetHex(test.expected).Normalize() - result := f.Square().Normalize() + for _, test := range tests { + f := setHex(test.in).Normalize() + expected := setHex(test.expected).Normalize() + + // Ensure squaring the value with the result going to another variable + // produces the expected result. + result := new(FieldVal).SquareVal(f).Normalize() if !result.Equals(expected) { - t.Errorf("fieldVal.Square #%d wrong result\n"+ - "got: %v\nwant: %v", i, result, expected) + t.Errorf("%s: unexpected result\ngot: %v\nwant: %v", test.name, + result, expected) + continue + } + + // Ensure self squaring an existing field value produces the expected + // result. + f.Square().Normalize() + if !f.Equals(expected) { + t.Errorf("%s: unexpected result\ngot: %v\nwant: %v", test.name, + f, expected) continue } } @@ -813,296 +846,127 @@ func TestInverse(t *testing.T) { t.Logf("Running %d tests", len(tests)) for i, test := range tests { - f := new(fieldVal).SetHex(test.in).Normalize() - expected := new(fieldVal).SetHex(test.expected).Normalize() + f := setHex(test.in).Normalize() + expected := setHex(test.expected).Normalize() result := f.Inverse().Normalize() if !result.Equals(expected) { - t.Errorf("fieldVal.Inverse #%d wrong result\n"+ + t.Errorf("FieldVal.Inverse #%d wrong result\n"+ "got: %v\nwant: %v", i, result, expected) continue } } } -// randFieldVal returns a random, normalized element in the field. -func randFieldVal(t *testing.T) fieldVal { - var b [32]byte - if _, err := rand.Read(b[:]); err != nil { - t.Fatalf("unable to create random element: %v", err) +// randFieldVal returns a field value created from a random value generated by +// the passed rng. +func randFieldVal(t *testing.T, rng *rand.Rand) *FieldVal { + t.Helper() + + var buf [32]byte + if _, err := rng.Read(buf[:]); err != nil { + t.Fatalf("failed to read random: %v", err) } - var x fieldVal - return *x.SetBytes(&b).Normalize() + // Create and return both a big integer and a field value. + var fv FieldVal + fv.SetBytes(&buf) + return &fv } -type sqrtTest struct { - name string - in string - expected string -} - -// TestSqrt asserts that a fieldVal properly computes the square root modulo the -// sep256k1 prime. -func TestSqrt(t *testing.T) { - var tests []sqrtTest - - // No valid root exists for the negative of a square. - for i := uint(9); i > 0; i-- { - var ( - x fieldVal - s fieldVal // x^2 mod p - n fieldVal // -x^2 mod p - ) - - x.SetInt(i) - s.SquareVal(&x).Normalize() - n.NegateVal(&s, 1).Normalize() - - tests = append(tests, sqrtTest{ - name: fmt.Sprintf("-%d", i), - in: fmt.Sprintf("%x", *n.Bytes()), - }) - } - - // A root should exist for true squares. - for i := uint(0); i < 10; i++ { - var ( - x fieldVal - s fieldVal // x^2 mod p - ) - - x.SetInt(i) - s.SquareVal(&x).Normalize() - - tests = append(tests, sqrtTest{ - name: fmt.Sprintf("%d", i), - in: fmt.Sprintf("%x", *s.Bytes()), - expected: fmt.Sprintf("%x", *x.Bytes()), - }) - } - - // Compute a non-square element, by negating if it has a root. - ns := randFieldVal(t) - if new(fieldVal).SqrtVal(&ns).Square().Equals(&ns) { - ns.Negate(1).Normalize() - } - - // For large random field values, test that: - // 1) its square has a valid root. - // 2) the negative of its square has no root. - // 3) the product of its square with a non-square has no root. - for i := 0; i < 10; i++ { - var ( - x fieldVal - s fieldVal // x^2 mod p - n fieldVal // -x^2 mod p - m fieldVal // ns*x^2 mod p - ) - - x = randFieldVal(t) - s.SquareVal(&x).Normalize() - n.NegateVal(&s, 1).Normalize() - m.Mul2(&s, &ns).Normalize() - - // A root should exist for true squares. - tests = append(tests, sqrtTest{ - name: fmt.Sprintf("%x", *s.Bytes()), - in: fmt.Sprintf("%x", *s.Bytes()), - expected: fmt.Sprintf("%x", *x.Bytes()), - }) - - // No valid root exists for the negative of a square. - tests = append(tests, sqrtTest{ - name: fmt.Sprintf("-%x", *s.Bytes()), - in: fmt.Sprintf("%x", *n.Bytes()), - }) - - // No root should be computed for product of a square and - // non-square. - tests = append(tests, sqrtTest{ - name: fmt.Sprintf("ns*%x", *s.Bytes()), - in: fmt.Sprintf("%x", *m.Bytes()), - }) - } - - for _, test := range tests { - t.Run(test.name, func(t *testing.T) { - testSqrt(t, test) - }) - } -} - -func testSqrt(t *testing.T, test sqrtTest) { - var ( - f fieldVal - root fieldVal - rootNeg fieldVal - ) - - f.SetHex(test.in).Normalize() - - // Compute sqrt(f) and its negative. - root.SqrtVal(&f).Normalize() - rootNeg.NegateVal(&root, 1).Normalize() - - switch { - - // If we expect a square root, verify that either the computed square - // root is +/- the expected value. - case len(test.expected) > 0: - var expected fieldVal - expected.SetHex(test.expected).Normalize() - if !root.Equals(&expected) && !rootNeg.Equals(&expected) { - t.Fatalf("fieldVal.Sqrt incorrect root\n"+ - "got: %v\ngot_neg: %v\nwant: %v", - root, rootNeg, expected) - } - - // Otherwise, we expect this input not to have a square root. - default: - if root.Square().Equals(&f) || rootNeg.Square().Equals(&f) { - t.Fatalf("fieldVal.Sqrt root should not exist\n"+ - "got: %v\ngot_neg: %v", root, rootNeg) - } - } -} - -// TestFieldSetBytes ensures that setting a field value to a 256-bit big-endian -// unsigned integer via both the slice and array methods works as expected for -// edge cases. Random cases are tested via the various other tests. -func TestFieldSetBytes(t *testing.T) { +// TestFieldSquareRoot ensures that calculating the square root of field values +// via SquareRootVal works as expected for edge cases. +func TestFieldSquareRoot(t *testing.T) { tests := []struct { - name string // test description - in string // hex encoded test value - expected [10]uint32 // expected raw ints + name string // test description + in string // hex encoded value + valid bool // whether or not the value has a square root + want string // expected hex encoded value }{{ - name: "zero", - in: "00", - expected: [10]uint32{0, 0, 0, 0, 0, 0, 0, 0, 0, 0}, + name: "secp256k1 prime (as 0 in and out)", + in: "0", + valid: true, + want: "0", }, { - name: "field prime", - in: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", - expected: [10]uint32{ - 0x03fffc2f, 0x03ffffbf, 0x03ffffff, 0x03ffffff, 0x03ffffff, - 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x003fffff, - }, + name: "secp256k1 prime (direct val with 0 out)", + in: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", + valid: true, + want: "0", }, { - name: "field prime - 1", - in: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", - expected: [10]uint32{ - 0x03fffc2e, 0x03ffffbf, 0x03ffffff, 0x03ffffff, 0x03ffffff, - 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x003fffff, - }, + name: "secp256k1 prime (as 0 in direct val out)", + in: "0", + valid: true, + want: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2f", }, { - name: "field prime + 1 (overflow in word zero)", - in: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc30", - expected: [10]uint32{ - 0x03fffc30, 0x03ffffbf, 0x03ffffff, 0x03ffffff, 0x03ffffff, - 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x003fffff, - }, + name: "secp256k1 prime-1", + in: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2e", + valid: false, + want: "0000000000000000000000000000000000000000000000000000000000000001", }, { - name: "field prime first 32 bits", - in: "fffffc2f", - expected: [10]uint32{ - 0x03fffc2f, 0x00000003f, 0x00000000, 0x00000000, 0x00000000, - 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, - }, + name: "secp256k1 prime-2", + in: "fffffffffffffffffffffffffffffffffffffffffffffffffffffffefffffc2d", + valid: false, + want: "210c790573632359b1edb4302c117d8a132654692c3feeb7de3a86ac3f3b53f7", }, { - name: "field prime word zero", - in: "03fffc2f", - expected: [10]uint32{ - 0x03fffc2f, 0x00000000, 0x00000000, 0x00000000, 0x00000000, - 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, - }, + name: "(secp256k1 prime-2)^2", + in: "0000000000000000000000000000000000000000000000000000000000000004", + valid: true, + want: "0000000000000000000000000000000000000000000000000000000000000002", }, { - name: "field prime first 64 bits", - in: "fffffffefffffc2f", - expected: [10]uint32{ - 0x03fffc2f, 0x03ffffbf, 0x00000fff, 0x00000000, 0x00000000, - 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, - }, + name: "value 1", + in: "0000000000000000000000000000000000000000000000000000000000000001", + valid: true, + want: "0000000000000000000000000000000000000000000000000000000000000001", }, { - name: "field prime word zero and one", - in: "0ffffefffffc2f", - expected: [10]uint32{ - 0x03fffc2f, 0x03ffffbf, 0x00000000, 0x00000000, 0x00000000, - 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, - }, + name: "value 2", + in: "0000000000000000000000000000000000000000000000000000000000000002", + valid: true, + want: "210c790573632359b1edb4302c117d8a132654692c3feeb7de3a86ac3f3b53f7", }, { - name: "field prime first 96 bits", - in: "fffffffffffffffefffffc2f", - expected: [10]uint32{ - 0x03fffc2f, 0x03ffffbf, 0x03ffffff, 0x0003ffff, 0x00000000, - 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, - }, + name: "random sampling 1", + in: "16fb970147a9acc73654d4be233cc48b875ce20a2122d24f073d29bd28805aca", + valid: false, + want: "6a27dcfca440cf7930a967be533b9620e397f122787c53958aaa7da7ad3d89a4", }, { - name: "field prime word zero, one, and two", - in: "3ffffffffffefffffc2f", - expected: [10]uint32{ - 0x03fffc2f, 0x03ffffbf, 0x03ffffff, 0x00000000, 0x00000000, - 0x00000000, 0x00000000, 0x00000000, 0x00000000, 0x00000000, - }, + name: "square of random sampling 1", + in: "f4a8c3738ace0a1c3abf77737ae737f07687b5e24c07a643398298bd96893a18", + valid: true, + want: "e90468feb8565338c9ab2b41dcc33b7478a31df5dedd2db0f8c2d641d77fa165", }, { - name: "overflow in word one (prime + 1<<26)", - in: "ffffffffffffffffffffffffffffffffffffffffffffffffffffffff03fffc2f", - expected: [10]uint32{ - 0x03fffc2f, 0x03ffffc0, 0x03ffffff, 0x03ffffff, 0x03ffffff, - 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x003fffff, - }, + name: "random sampling 2", + in: "69d1323ce9f1f7b3bd3c7320b0d6311408e30281e273e39a0d8c7ee1c8257919", + valid: true, + want: "61f4a7348274a52d75dfe176b8e3aaff61c1c833b6678260ba73def0fb2ad148", }, { - name: "(field prime - 1) * 2 NOT mod P, truncated >32 bytes", - in: "01fffffffffffffffffffffffffffffffffffffffffffffffffffffffdfffff85c", - expected: [10]uint32{ - 0x01fffff8, 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x03ffffff, - 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x00007fff, - }, + name: "random sampling 3", + in: "e0debf988ae098ecda07d0b57713e97c6d213db19753e8c95aa12a2fc1cc5272", + valid: false, + want: "6e1cc9c311d33d901670135244f994b1ea39501f38002269b34ce231750cfbac", }, { - name: "2^256 - 1", - in: "ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff", - expected: [10]uint32{ - 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x03ffffff, - 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x03ffffff, 0x003fffff, - }, - }, { - name: "alternating bits", - in: "a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5", - expected: [10]uint32{ - 0x01a5a5a5, 0x01696969, 0x025a5a5a, 0x02969696, 0x01a5a5a5, - 0x01696969, 0x025a5a5a, 0x02969696, 0x01a5a5a5, 0x00296969, - }, - }, { - name: "alternating bits 2", - in: "5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a5a", - expected: [10]uint32{ - 0x025a5a5a, 0x02969696, 0x01a5a5a5, 0x01696969, 0x025a5a5a, - 0x02969696, 0x01a5a5a5, 0x01696969, 0x025a5a5a, 0x00169696, - }, + name: "random sampling 4", + in: "dcd394f91f74c2ba16aad74a22bb0ed47fe857774b8f2d6c09e28bfb14642878", + valid: true, + want: "72b22fe6f173f8bcb21898806142ed4c05428601256eafce5d36c1b08fb82bab", }} for _, test := range tests { - inBytes := hexToBytes(test.in) + input := setHex(test.in).Normalize() + want := setHex(test.want).Normalize() - // Ensure setting the bytes via the slice method works as expected. - var f fieldVal - f.SetByteSlice(inBytes) - if !reflect.DeepEqual(f.n, test.expected) { - t.Errorf("%s: unexpected result\ngot: %x\nwant: %x", test.name, f.n, - test.expected) + // Calculate the square root and enusre the validity flag matches the + // expected value. + var result FieldVal + isValid := result.SquareRootVal(input) + if isValid != test.valid { + t.Errorf("%s: mismatched validity -- got %v, want %v", test.name, + isValid, test.valid) continue } - // Ensure setting the bytes via the array method works as expected. - var f2 fieldVal - var b32 [32]byte - truncatedInBytes := inBytes - if len(truncatedInBytes) > 32 { - truncatedInBytes = truncatedInBytes[:32] - } - copy(b32[32-len(truncatedInBytes):], truncatedInBytes) - f2.SetBytes(&b32) - if !reflect.DeepEqual(f2.n, test.expected) { - t.Errorf("%s: unexpected result\ngot: %x\nwant: %x", test.name, - f2.n, test.expected) + // Ensure the calculated result matches the expected value. + result.Normalize() + if !result.Equals(want) { + t.Errorf("%s: d wrong result\ngot: %v\nwant: %v", test.name, result, + want) continue } } diff --git a/btcec/genprecomps.go b/btcec/genprecomps.go deleted file mode 100644 index d4a9c1b8..00000000 --- a/btcec/genprecomps.go +++ /dev/null @@ -1,63 +0,0 @@ -// Copyright 2015 The btcsuite developers -// Use of this source code is governed by an ISC -// license that can be found in the LICENSE file. - -// This file is ignored during the regular build due to the following build tag. -// It is called by go generate and used to automatically generate pre-computed -// tables used to accelerate operations. -// +build ignore - -package main - -import ( - "bytes" - "compress/zlib" - "encoding/base64" - "fmt" - "log" - "os" - - "github.com/btcsuite/btcd/btcec" -) - -func main() { - fi, err := os.Create("secp256k1.go") - if err != nil { - log.Fatal(err) - } - defer fi.Close() - - // Compress the serialized byte points. - serialized := btcec.S256().SerializedBytePoints() - var compressed bytes.Buffer - w := zlib.NewWriter(&compressed) - if _, err := w.Write(serialized); err != nil { - fmt.Println(err) - os.Exit(1) - } - w.Close() - - // Encode the compressed byte points with base64. - encoded := make([]byte, base64.StdEncoding.EncodedLen(compressed.Len())) - base64.StdEncoding.Encode(encoded, compressed.Bytes()) - - fmt.Fprintln(fi, "// Copyright (c) 2015 The btcsuite developers") - fmt.Fprintln(fi, "// Use of this source code is governed by an ISC") - fmt.Fprintln(fi, "// license that can be found in the LICENSE file.") - fmt.Fprintln(fi) - fmt.Fprintln(fi, "package btcec") - fmt.Fprintln(fi) - fmt.Fprintln(fi, "// Auto-generated file (see genprecomps.go)") - fmt.Fprintln(fi, "// DO NOT EDIT") - fmt.Fprintln(fi) - fmt.Fprintf(fi, "var secp256k1BytePoints = %q\n", string(encoded)) - - a1, b1, a2, b2 := btcec.S256().EndomorphismVectors() - fmt.Println("The following values are the computed linearly " + - "independent vectors needed to make use of the secp256k1 " + - "endomorphism:") - fmt.Printf("a1: %x\n", a1) - fmt.Printf("b1: %x\n", b1) - fmt.Printf("a2: %x\n", a2) - fmt.Printf("b2: %x\n", b2) -} diff --git a/btcec/gensecp256k1.go b/btcec/gensecp256k1.go deleted file mode 100644 index 1928702d..00000000 --- a/btcec/gensecp256k1.go +++ /dev/null @@ -1,203 +0,0 @@ -// Copyright (c) 2014-2015 The btcsuite developers -// Use of this source code is governed by an ISC -// license that can be found in the LICENSE file. - -// This file is ignored during the regular build due to the following build tag. -// This build tag is set during go generate. -// +build gensecp256k1 - -package btcec - -// References: -// [GECC]: Guide to Elliptic Curve Cryptography (Hankerson, Menezes, Vanstone) - -import ( - "encoding/binary" - "math/big" -) - -// secp256k1BytePoints are dummy points used so the code which generates the -// real values can compile. -var secp256k1BytePoints = "" - -// getDoublingPoints returns all the possible G^(2^i) for i in -// 0..n-1 where n is the curve's bit size (256 in the case of secp256k1) -// the coordinates are recorded as Jacobian coordinates. -func (curve *KoblitzCurve) getDoublingPoints() [][3]fieldVal { - doublingPoints := make([][3]fieldVal, curve.BitSize) - - // initialize px, py, pz to the Jacobian coordinates for the base point - px, py := curve.bigAffineToField(curve.Gx, curve.Gy) - pz := new(fieldVal).SetInt(1) - for i := 0; i < curve.BitSize; i++ { - doublingPoints[i] = [3]fieldVal{*px, *py, *pz} - // P = 2*P - curve.doubleJacobian(px, py, pz, px, py, pz) - } - return doublingPoints -} - -// SerializedBytePoints returns a serialized byte slice which contains all of -// the possible points per 8-bit window. This is used to when generating -// secp256k1.go. -func (curve *KoblitzCurve) SerializedBytePoints() []byte { - doublingPoints := curve.getDoublingPoints() - - // Segregate the bits into byte-sized windows - serialized := make([]byte, curve.byteSize*256*3*10*4) - offset := 0 - for byteNum := 0; byteNum < curve.byteSize; byteNum++ { - // Grab the 8 bits that make up this byte from doublingPoints. - startingBit := 8 * (curve.byteSize - byteNum - 1) - computingPoints := doublingPoints[startingBit : startingBit+8] - - // Compute all points in this window and serialize them. - for i := 0; i < 256; i++ { - px, py, pz := new(fieldVal), new(fieldVal), new(fieldVal) - for j := 0; j < 8; j++ { - if i>>uint(j)&1 == 1 { - curve.addJacobian(px, py, pz, &computingPoints[j][0], - &computingPoints[j][1], &computingPoints[j][2], px, py, pz) - } - } - for i := 0; i < 10; i++ { - binary.LittleEndian.PutUint32(serialized[offset:], px.n[i]) - offset += 4 - } - for i := 0; i < 10; i++ { - binary.LittleEndian.PutUint32(serialized[offset:], py.n[i]) - offset += 4 - } - for i := 0; i < 10; i++ { - binary.LittleEndian.PutUint32(serialized[offset:], pz.n[i]) - offset += 4 - } - } - } - - return serialized -} - -// sqrt returns the square root of the provided big integer using Newton's -// method. It's only compiled and used during generation of pre-computed -// values, so speed is not a huge concern. -func sqrt(n *big.Int) *big.Int { - // Initial guess = 2^(log_2(n)/2) - guess := big.NewInt(2) - guess.Exp(guess, big.NewInt(int64(n.BitLen()/2)), nil) - - // Now refine using Newton's method. - big2 := big.NewInt(2) - prevGuess := big.NewInt(0) - for { - prevGuess.Set(guess) - guess.Add(guess, new(big.Int).Div(n, guess)) - guess.Div(guess, big2) - if guess.Cmp(prevGuess) == 0 { - break - } - } - return guess -} - -// EndomorphismVectors runs the first 3 steps of algorithm 3.74 from [GECC] to -// generate the linearly independent vectors needed to generate a balanced -// length-two representation of a multiplier such that k = k1 + k2λ (mod N) and -// returns them. Since the values will always be the same given the fact that N -// and λ are fixed, the final results can be accelerated by storing the -// precomputed values with the curve. -func (curve *KoblitzCurve) EndomorphismVectors() (a1, b1, a2, b2 *big.Int) { - bigMinus1 := big.NewInt(-1) - - // This section uses an extended Euclidean algorithm to generate a - // sequence of equations: - // s[i] * N + t[i] * λ = r[i] - - nSqrt := sqrt(curve.N) - u, v := new(big.Int).Set(curve.N), new(big.Int).Set(curve.lambda) - x1, y1 := big.NewInt(1), big.NewInt(0) - x2, y2 := big.NewInt(0), big.NewInt(1) - q, r := new(big.Int), new(big.Int) - qu, qx1, qy1 := new(big.Int), new(big.Int), new(big.Int) - s, t := new(big.Int), new(big.Int) - ri, ti := new(big.Int), new(big.Int) - a1, b1, a2, b2 = new(big.Int), new(big.Int), new(big.Int), new(big.Int) - found, oneMore := false, false - for u.Sign() != 0 { - // q = v/u - q.Div(v, u) - - // r = v - q*u - qu.Mul(q, u) - r.Sub(v, qu) - - // s = x2 - q*x1 - qx1.Mul(q, x1) - s.Sub(x2, qx1) - - // t = y2 - q*y1 - qy1.Mul(q, y1) - t.Sub(y2, qy1) - - // v = u, u = r, x2 = x1, x1 = s, y2 = y1, y1 = t - v.Set(u) - u.Set(r) - x2.Set(x1) - x1.Set(s) - y2.Set(y1) - y1.Set(t) - - // As soon as the remainder is less than the sqrt of n, the - // values of a1 and b1 are known. - if !found && r.Cmp(nSqrt) < 0 { - // When this condition executes ri and ti represent the - // r[i] and t[i] values such that i is the greatest - // index for which r >= sqrt(n). Meanwhile, the current - // r and t values are r[i+1] and t[i+1], respectively. - - // a1 = r[i+1], b1 = -t[i+1] - a1.Set(r) - b1.Mul(t, bigMinus1) - found = true - oneMore = true - - // Skip to the next iteration so ri and ti are not - // modified. - continue - - } else if oneMore { - // When this condition executes ri and ti still - // represent the r[i] and t[i] values while the current - // r and t are r[i+2] and t[i+2], respectively. - - // sum1 = r[i]^2 + t[i]^2 - rSquared := new(big.Int).Mul(ri, ri) - tSquared := new(big.Int).Mul(ti, ti) - sum1 := new(big.Int).Add(rSquared, tSquared) - - // sum2 = r[i+2]^2 + t[i+2]^2 - r2Squared := new(big.Int).Mul(r, r) - t2Squared := new(big.Int).Mul(t, t) - sum2 := new(big.Int).Add(r2Squared, t2Squared) - - // if (r[i]^2 + t[i]^2) <= (r[i+2]^2 + t[i+2]^2) - if sum1.Cmp(sum2) <= 0 { - // a2 = r[i], b2 = -t[i] - a2.Set(ri) - b2.Mul(ti, bigMinus1) - } else { - // a2 = r[i+2], b2 = -t[i+2] - a2.Set(r) - b2.Mul(t, bigMinus1) - } - - // All done. - break - } - - ri.Set(r) - ti.Set(t) - } - - return a1, b1, a2, b2 -} diff --git a/btcec/go.mod b/btcec/go.mod new file mode 100644 index 00000000..ce5eb332 --- /dev/null +++ b/btcec/go.mod @@ -0,0 +1,9 @@ +module github.com/btcsuite/btcd/btcec/v2 + +go 1.17 + +require ( + github.com/btcsuite/btcd v0.22.0-beta + github.com/davecgh/go-spew v1.1.1 + github.com/decred/dcrd/dcrec/secp256k1/v4 v4.0.1 +) diff --git a/btcec/go.sum b/btcec/go.sum new file mode 100644 index 00000000..a0f9c5b8 --- /dev/null +++ b/btcec/go.sum @@ -0,0 +1,49 @@ +github.com/aead/siphash v1.0.1/go.mod h1:Nywa3cDsYNNK3gaciGTWPwHt0wlpNV15vwmswBAUSII= +github.com/btcsuite/btcd v0.20.1-beta/go.mod h1:wVuoA8VJLEcwgqHBwHmzLRazpKxTv13Px/pDuV7OomQ= +github.com/btcsuite/btcd v0.22.0-beta h1:LTDpDKUM5EeOFBPM8IXpinEcmZ6FWfNZbE3lfrfdnWo= +github.com/btcsuite/btcd v0.22.0-beta/go.mod h1:9n5ntfhhHQBIhUvlhDvD3Qg6fRUj4jkN0VB8L8svzOA= +github.com/btcsuite/btclog v0.0.0-20170628155309-84c8d2346e9f/go.mod h1:TdznJufoqS23FtqVCzL0ZqgP5MqXbb4fg/WgDys70nA= +github.com/btcsuite/btcutil v0.0.0-20190425235716-9e5f4b9a998d/go.mod h1:+5NJ2+qvTyV9exUAL/rxXi3DcLg2Ts+ymUAY5y4NvMg= +github.com/btcsuite/btcutil v1.0.3-0.20201208143702-a53e38424cce/go.mod h1:0DVlHczLPewLcPGEIeUEzfOJhqGPQ0mJJRDBtD307+o= +github.com/btcsuite/go-socks v0.0.0-20170105172521-4720035b7bfd/go.mod h1:HHNXQzUsZCxOoE+CPiyCTO6x34Zs86zZUiwtpXoGdtg= +github.com/btcsuite/goleveldb v0.0.0-20160330041536-7834afc9e8cd/go.mod h1:F+uVaaLLH7j4eDXPRvw78tMflu7Ie2bzYOH4Y8rRKBY= +github.com/btcsuite/goleveldb v1.0.0/go.mod h1:QiK9vBlgftBg6rWQIj6wFzbPfRjiykIEhBH4obrXJ/I= +github.com/btcsuite/snappy-go v0.0.0-20151229074030-0bdef8d06723/go.mod h1:8woku9dyThutzjeg+3xrA5iCpBRH8XEEg3lh6TiUghc= +github.com/btcsuite/snappy-go v1.0.0/go.mod h1:8woku9dyThutzjeg+3xrA5iCpBRH8XEEg3lh6TiUghc= +github.com/btcsuite/websocket v0.0.0-20150119174127-31079b680792/go.mod h1:ghJtEyQwv5/p4Mg4C0fgbePVuGr935/5ddU9Z3TmDRY= +github.com/btcsuite/winsvc v1.0.0/go.mod h1:jsenWakMcC0zFBFurPLEAyrnc/teJEM1O46fmI40EZs= +github.com/davecgh/go-spew v0.0.0-20171005155431-ecdeabc65495/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38= +github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38= +github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c= +github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38= +github.com/decred/dcrd/crypto/blake256 v1.0.0/go.mod h1:sQl2p6Y26YV+ZOcSTP6thNdn47hh8kt6rqSlvmrXFAc= +github.com/decred/dcrd/dcrec/secp256k1/v4 v4.0.1 h1:YLtO71vCjJRCBcrPMtQ9nqBsqpA1m5sE92cU+pd5Mcc= +github.com/decred/dcrd/dcrec/secp256k1/v4 v4.0.1/go.mod h1:hyedUtir6IdtD/7lIxGeCxkaw7y45JueMRL4DIyJDKs= +github.com/decred/dcrd/lru v1.0.0/go.mod h1:mxKOwFd7lFjN2GZYsiz/ecgqR6kkYAl+0pz0tEMk218= +github.com/fsnotify/fsnotify v1.4.7/go.mod h1:jwhsz4b93w/PPRr/qN1Yymfu8t87LnFCMoQvtojpjFo= +github.com/golang/protobuf v1.2.0/go.mod h1:6lQm79b+lXiMfvg/cZm0SGofjICqVBUtrP5yJMmIC1U= +github.com/hpcloud/tail v1.0.0/go.mod h1:ab1qPbhIpdTxEkNHXyeSf5vhxWSCs/tWer42PpOxQnU= +github.com/jessevdk/go-flags v0.0.0-20141203071132-1679536dcc89/go.mod h1:4FA24M0QyGHXBuZZK/XkWh8h0e1EYbRYJSGM75WSRxI= +github.com/jessevdk/go-flags v1.4.0/go.mod h1:4FA24M0QyGHXBuZZK/XkWh8h0e1EYbRYJSGM75WSRxI= +github.com/jrick/logrotate v1.0.0/go.mod h1:LNinyqDIJnpAur+b8yyulnQw/wDuN1+BYKlTRt3OuAQ= +github.com/kkdai/bstream v0.0.0-20161212061736-f391b8402d23/go.mod h1:J+Gs4SYgM6CZQHDETBtE9HaSEkGmuNXF86RwHhHUvq4= +github.com/onsi/ginkgo v1.6.0/go.mod h1:lLunBs/Ym6LB5Z9jYTR76FiuTmxDTDusOGeTQH+WWjE= +github.com/onsi/ginkgo v1.7.0/go.mod h1:lLunBs/Ym6LB5Z9jYTR76FiuTmxDTDusOGeTQH+WWjE= +github.com/onsi/gomega v1.4.1/go.mod h1:C1qb7wdrVGGVU+Z6iS04AVkA3Q65CEZX59MT0QO5uiA= +github.com/onsi/gomega v1.4.3/go.mod h1:ex+gbHU/CVuBBDIJjb2X0qEXbFg53c61hWP/1CpauHY= +golang.org/x/crypto v0.0.0-20170930174604-9419663f5a44/go.mod h1:6SG95UA2DQfeDnfUPMdvaQW0Q7yPrPDi9nlGo2tz2b4= +golang.org/x/crypto v0.0.0-20190308221718-c2843e01d9a2/go.mod h1:djNgcEr1/C05ACkg1iLfiJU5Ep61QUkGW8qpdssI0+w= +golang.org/x/crypto v0.0.0-20200115085410-6d4e4cb37c7d/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto= +golang.org/x/crypto v0.0.0-20200510223506-06a226fb4e37/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto= +golang.org/x/net v0.0.0-20180719180050-a680a1efc54d/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4= +golang.org/x/net v0.0.0-20180906233101-161cd47e91fd/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4= +golang.org/x/net v0.0.0-20190404232315-eb5bcb51f2a3/go.mod h1:t9HGtf8HONx5eT2rtn7q6eTqICYqUVnKs3thJo3Qplg= +golang.org/x/sync v0.0.0-20180314180146-1d60e4601c6f/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM= +golang.org/x/sys v0.0.0-20180909124046-d0be0721c37e/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY= +golang.org/x/sys v0.0.0-20190215142949-d0b11bdaac8a/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY= +golang.org/x/sys v0.0.0-20190412213103-97732733099d/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs= +golang.org/x/text v0.3.0/go.mod h1:NqM8EUOU14njkJ3fqMW+pc6Ldnwhi/IjpwHt7yyuwOQ= +gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0= +gopkg.in/fsnotify.v1 v1.4.7/go.mod h1:Tz8NjZHkW78fSQdbUxIjBTcgA1z1m8ZHf0WmKUhAMys= +gopkg.in/tomb.v1 v1.0.0-20141024135613-dd632973f1e7/go.mod h1:dt/ZhP58zS4L8KSrWDmTeBkI65Dw0HsyUHuEVlX15mw= +gopkg.in/yaml.v2 v2.2.1/go.mod h1:hI93XBmqTisBFMUTm0b8Fm+jr3Dg1NNxqwp+5A1VGuI= diff --git a/btcec/modnscalar.go b/btcec/modnscalar.go new file mode 100644 index 00000000..eb1b8f05 --- /dev/null +++ b/btcec/modnscalar.go @@ -0,0 +1,42 @@ +package btcec + +import ( + secp "github.com/decred/dcrd/dcrec/secp256k1/v4" +) + +// ModNScalar implements optimized 256-bit constant-time fixed-precision +// arithmetic over the secp256k1 group order. This means all arithmetic is +// performed modulo: +// +// 0xfffffffffffffffffffffffffffffffebaaedce6af48a03bbfd25e8cd0364141 +// +// It only implements the arithmetic needed for elliptic curve operations, +// however, the operations that are not implemented can typically be worked +// around if absolutely needed. For example, subtraction can be performed by +// adding the negation. +// +// Should it be absolutely necessary, conversion to the standard library +// math/big.Int can be accomplished by using the Bytes method, slicing the +// resulting fixed-size array, and feeding it to big.Int.SetBytes. However, +// that should typically be avoided when possible as conversion to big.Ints +// requires allocations, is not constant time, and is slower when working modulo +// the group order. +type ModNScalar = secp.ModNScalar + +// NonceRFC6979 generates a nonce deterministically according to RFC 6979 using +// HMAC-SHA256 for the hashing function. It takes a 32-byte hash as an input +// and returns a 32-byte nonce to be used for deterministic signing. The extra +// and version arguments are optional, but allow additional data to be added to +// the input of the HMAC. When provided, the extra data must be 32-bytes and +// version must be 16 bytes or they will be ignored. +// +// Finally, the extraIterations parameter provides a method to produce a stream +// of deterministic nonces to ensure the signing code is able to produce a nonce +// that results in a valid signature in the extremely unlikely event the +// original nonce produced results in an invalid signature (e.g. R == 0). +// Signing code should start with 0 and increment it if necessary. +func NonceRFC6979(privKey []byte, hash []byte, extra []byte, version []byte, + extraIterations uint32) *ModNScalar { + + return secp.NonceRFC6979(privKey, hash, extra, version, extraIterations) +} diff --git a/btcec/precompute.go b/btcec/precompute.go deleted file mode 100644 index 034cd553..00000000 --- a/btcec/precompute.go +++ /dev/null @@ -1,67 +0,0 @@ -// Copyright 2015 The btcsuite developers -// Use of this source code is governed by an ISC -// license that can be found in the LICENSE file. - -package btcec - -import ( - "compress/zlib" - "encoding/base64" - "encoding/binary" - "io/ioutil" - "strings" -) - -//go:generate go run -tags gensecp256k1 genprecomps.go - -// loadS256BytePoints decompresses and deserializes the pre-computed byte points -// used to accelerate scalar base multiplication for the secp256k1 curve. This -// approach is used since it allows the compile to use significantly less ram -// and be performed much faster than it is with hard-coding the final in-memory -// data structure. At the same time, it is quite fast to generate the in-memory -// data structure at init time with this approach versus computing the table. -func loadS256BytePoints() error { - // There will be no byte points to load when generating them. - bp := secp256k1BytePoints - if len(bp) == 0 { - return nil - } - - // Decompress the pre-computed table used to accelerate scalar base - // multiplication. - decoder := base64.NewDecoder(base64.StdEncoding, strings.NewReader(bp)) - r, err := zlib.NewReader(decoder) - if err != nil { - return err - } - serialized, err := ioutil.ReadAll(r) - if err != nil { - return err - } - - // Deserialize the precomputed byte points and set the curve to them. - offset := 0 - var bytePoints [32][256][3]fieldVal - for byteNum := 0; byteNum < 32; byteNum++ { - // All points in this window. - for i := 0; i < 256; i++ { - px := &bytePoints[byteNum][i][0] - py := &bytePoints[byteNum][i][1] - pz := &bytePoints[byteNum][i][2] - for i := 0; i < 10; i++ { - px.n[i] = binary.LittleEndian.Uint32(serialized[offset:]) - offset += 4 - } - for i := 0; i < 10; i++ { - py.n[i] = binary.LittleEndian.Uint32(serialized[offset:]) - offset += 4 - } - for i := 0; i < 10; i++ { - pz.n[i] = binary.LittleEndian.Uint32(serialized[offset:]) - offset += 4 - } - } - } - secp256k1.bytePoints = &bytePoints - return nil -} diff --git a/btcec/privkey.go b/btcec/privkey.go index 676a8c3f..6f13990b 100644 --- a/btcec/privkey.go +++ b/btcec/privkey.go @@ -5,69 +5,27 @@ package btcec import ( - "crypto/ecdsa" - "crypto/elliptic" - "crypto/rand" - "math/big" + secp "github.com/decred/dcrd/dcrec/secp256k1/v4" ) // PrivateKey wraps an ecdsa.PrivateKey as a convenience mainly for signing // things with the the private key without having to directly import the ecdsa // package. -type PrivateKey ecdsa.PrivateKey +type PrivateKey = secp.PrivateKey // PrivKeyFromBytes returns a private and public key for `curve' based on the // private key passed as an argument as a byte slice. -func PrivKeyFromBytes(curve elliptic.Curve, pk []byte) (*PrivateKey, - *PublicKey) { - x, y := curve.ScalarBaseMult(pk) +func PrivKeyFromBytes(pk []byte) (*PrivateKey, *PublicKey) { + privKey := secp.PrivKeyFromBytes(pk) - priv := &ecdsa.PrivateKey{ - PublicKey: ecdsa.PublicKey{ - Curve: curve, - X: x, - Y: y, - }, - D: new(big.Int).SetBytes(pk), - } - - return (*PrivateKey)(priv), (*PublicKey)(&priv.PublicKey) + return privKey, privKey.PubKey() } // NewPrivateKey is a wrapper for ecdsa.GenerateKey that returns a PrivateKey // instead of the normal ecdsa.PrivateKey. -func NewPrivateKey(curve elliptic.Curve) (*PrivateKey, error) { - key, err := ecdsa.GenerateKey(curve, rand.Reader) - if err != nil { - return nil, err - } - return (*PrivateKey)(key), nil -} - -// PubKey returns the PublicKey corresponding to this private key. -func (p *PrivateKey) PubKey() *PublicKey { - return (*PublicKey)(&p.PublicKey) -} - -// ToECDSA returns the private key as a *ecdsa.PrivateKey. -func (p *PrivateKey) ToECDSA() *ecdsa.PrivateKey { - return (*ecdsa.PrivateKey)(p) -} - -// Sign generates an ECDSA signature for the provided hash (which should be the result -// of hashing a larger message) using the private key. Produced signature -// is deterministic (same message and same key yield the same signature) and canonical -// in accordance with RFC6979 and BIP0062. -func (p *PrivateKey) Sign(hash []byte) (*Signature, error) { - return signRFC6979(p, hash) +func NewPrivateKey() (*PrivateKey, error) { + return secp.GeneratePrivateKey() } // PrivKeyBytesLen defines the length in bytes of a serialized private key. const PrivKeyBytesLen = 32 - -// Serialize returns the private key number d as a big-endian binary-encoded -// number, padded to a length of 32 bytes. -func (p *PrivateKey) Serialize() []byte { - b := make([]byte, 0, PrivKeyBytesLen) - return paddedAppend(PrivKeyBytesLen, b, p.ToECDSA().D.Bytes()) -} diff --git a/btcec/privkey_test.go b/btcec/privkey_test.go index a2918dc1..71a8bcea 100644 --- a/btcec/privkey_test.go +++ b/btcec/privkey_test.go @@ -26,20 +26,16 @@ func TestPrivKeys(t *testing.T) { } for _, test := range tests { - priv, pub := PrivKeyFromBytes(S256(), test.key) + priv, pub := PrivKeyFromBytes(test.key) - _, err := ParsePubKey(pub.SerializeUncompressed(), S256()) + _, err := ParsePubKey(pub.SerializeUncompressed()) if err != nil { t.Errorf("%s privkey: %v", test.name, err) continue } hash := []byte{0x0, 0x1, 0x2, 0x3, 0x4, 0x5, 0x6, 0x7, 0x8, 0x9} - sig, err := priv.Sign(hash) - if err != nil { - t.Errorf("%s could not sign: %v", test.name, err) - continue - } + sig := Sign(priv, hash) if !sig.Verify(hash, pub) { t.Errorf("%s could not verify: %v", test.name, err) diff --git a/btcec/pubkey.go b/btcec/pubkey.go index 3c9d5d02..7968ed04 100644 --- a/btcec/pubkey.go +++ b/btcec/pubkey.go @@ -5,59 +5,14 @@ package btcec import ( - "crypto/ecdsa" - "errors" - "fmt" - "math/big" + secp "github.com/decred/dcrd/dcrec/secp256k1/v4" ) // These constants define the lengths of serialized public keys. const ( - PubKeyBytesLenCompressed = 33 - PubKeyBytesLenUncompressed = 65 - PubKeyBytesLenHybrid = 65 + PubKeyBytesLenCompressed = 33 ) -func isOdd(a *big.Int) bool { - return a.Bit(0) == 1 -} - -// decompressPoint decompresses a point on the secp256k1 curve given the X point and -// the solution to use. -func decompressPoint(curve *KoblitzCurve, bigX *big.Int, ybit bool) (*big.Int, error) { - var x fieldVal - x.SetByteSlice(bigX.Bytes()) - - // Compute x^3 + B mod p. - var x3 fieldVal - x3.SquareVal(&x).Mul(&x) - x3.Add(curve.fieldB).Normalize() - - // Now calculate sqrt mod p of x^3 + B - // This code used to do a full sqrt based on tonelli/shanks, - // but this was replaced by the algorithms referenced in - // https://bitcointalk.org/index.php?topic=162805.msg1712294#msg1712294 - var y fieldVal - y.SqrtVal(&x3).Normalize() - if ybit != y.IsOdd() { - y.Negate(1).Normalize() - } - - // Check that y is a square root of x^3 + B. - var y2 fieldVal - y2.SquareVal(&y).Normalize() - if !y2.Equals(&x3) { - return nil, fmt.Errorf("invalid square root") - } - - // Verify that y-coord has expected parity. - if ybit != y.IsOdd() { - return nil, fmt.Errorf("ybit doesn't match oddness") - } - - return new(big.Int).SetBytes(y.Bytes()[:]), nil -} - const ( pubkeyCompressed byte = 0x2 // y_bit + x coord pubkeyUncompressed byte = 0x4 // x coord + y coord @@ -76,119 +31,21 @@ func IsCompressedPubKey(pubKey []byte) bool { // ParsePubKey parses a public key for a koblitz curve from a bytestring into a // ecdsa.Publickey, verifying that it is valid. It supports compressed, // uncompressed and hybrid signature formats. -func ParsePubKey(pubKeyStr []byte, curve *KoblitzCurve) (key *PublicKey, err error) { - pubkey := PublicKey{} - pubkey.Curve = curve - - if len(pubKeyStr) == 0 { - return nil, errors.New("pubkey string is empty") - } - - format := pubKeyStr[0] - ybit := (format & 0x1) == 0x1 - format &= ^byte(0x1) - - switch len(pubKeyStr) { - case PubKeyBytesLenUncompressed: - if format != pubkeyUncompressed && format != pubkeyHybrid { - return nil, fmt.Errorf("invalid magic in pubkey str: "+ - "%d", pubKeyStr[0]) - } - - pubkey.X = new(big.Int).SetBytes(pubKeyStr[1:33]) - pubkey.Y = new(big.Int).SetBytes(pubKeyStr[33:]) - // hybrid keys have extra information, make use of it. - if format == pubkeyHybrid && ybit != isOdd(pubkey.Y) { - return nil, fmt.Errorf("ybit doesn't match oddness") - } - - if pubkey.X.Cmp(pubkey.Curve.Params().P) >= 0 { - return nil, fmt.Errorf("pubkey X parameter is >= to P") - } - if pubkey.Y.Cmp(pubkey.Curve.Params().P) >= 0 { - return nil, fmt.Errorf("pubkey Y parameter is >= to P") - } - if !pubkey.Curve.IsOnCurve(pubkey.X, pubkey.Y) { - return nil, fmt.Errorf("pubkey isn't on secp256k1 curve") - } - - case PubKeyBytesLenCompressed: - // format is 0x2 | solution, - // solution determines which solution of the curve we use. - /// y^2 = x^3 + Curve.B - if format != pubkeyCompressed { - return nil, fmt.Errorf("invalid magic in compressed "+ - "pubkey string: %d", pubKeyStr[0]) - } - pubkey.X = new(big.Int).SetBytes(pubKeyStr[1:33]) - pubkey.Y, err = decompressPoint(curve, pubkey.X, ybit) - if err != nil { - return nil, err - } - - default: // wrong! - return nil, fmt.Errorf("invalid pub key length %d", - len(pubKeyStr)) - } - - return &pubkey, nil +func ParsePubKey(pubKeyStr []byte) (*PublicKey, error) { + return secp.ParsePubKey(pubKeyStr) } // PublicKey is an ecdsa.PublicKey with additional functions to // serialize in uncompressed, compressed, and hybrid formats. -type PublicKey ecdsa.PublicKey +type PublicKey = secp.PublicKey -// ToECDSA returns the public key as a *ecdsa.PublicKey. -func (p *PublicKey) ToECDSA() *ecdsa.PublicKey { - return (*ecdsa.PublicKey)(p) -} - -// SerializeUncompressed serializes a public key in a 65-byte uncompressed -// format. -func (p *PublicKey) SerializeUncompressed() []byte { - b := make([]byte, 0, PubKeyBytesLenUncompressed) - b = append(b, pubkeyUncompressed) - b = paddedAppend(32, b, p.X.Bytes()) - return paddedAppend(32, b, p.Y.Bytes()) -} - -// SerializeCompressed serializes a public key in a 33-byte compressed format. -func (p *PublicKey) SerializeCompressed() []byte { - b := make([]byte, 0, PubKeyBytesLenCompressed) - format := pubkeyCompressed - if isOdd(p.Y) { - format |= 0x1 - } - b = append(b, format) - return paddedAppend(32, b, p.X.Bytes()) -} - -// SerializeHybrid serializes a public key in a 65-byte hybrid format. -func (p *PublicKey) SerializeHybrid() []byte { - b := make([]byte, 0, PubKeyBytesLenHybrid) - format := pubkeyHybrid - if isOdd(p.Y) { - format |= 0x1 - } - b = append(b, format) - b = paddedAppend(32, b, p.X.Bytes()) - return paddedAppend(32, b, p.Y.Bytes()) -} - -// IsEqual compares this PublicKey instance to the one passed, returning true if -// both PublicKeys are equivalent. A PublicKey is equivalent to another, if they -// both have the same X and Y coordinate. -func (p *PublicKey) IsEqual(otherPubKey *PublicKey) bool { - return p.X.Cmp(otherPubKey.X) == 0 && - p.Y.Cmp(otherPubKey.Y) == 0 -} - -// paddedAppend appends the src byte slice to dst, returning the new slice. -// If the length of the source is smaller than the passed size, leading zero -// bytes are appended to the dst slice before appending src. -func paddedAppend(size uint, dst, src []byte) []byte { - for i := 0; i < int(size)-len(src); i++ { - dst = append(dst, 0) - } - return append(dst, src...) +// NewPublicKey instantiates a new public key with the given x and y +// coordinates. +// +// It should be noted that, unlike ParsePubKey, since this accepts arbitrary x +// and y coordinates, it allows creation of public keys that are not valid +// points on the secp256k1 curve. The IsOnCurve method of the returned instance +// can be used to determine validity. +func NewPublicKey(x, y *FieldVal) *PublicKey { + return secp.NewPublicKey(x, y) } diff --git a/btcec/pubkey_test.go b/btcec/pubkey_test.go index 68b61de1..7ee7cd80 100644 --- a/btcec/pubkey_test.go +++ b/btcec/pubkey_test.go @@ -216,7 +216,7 @@ var pubKeyTests = []pubKeyTest{ func TestPubKeys(t *testing.T) { for _, test := range pubKeyTests { - pk, err := ParsePubKey(test.key, S256()) + pk, err := ParsePubKey(test.key) if err != nil { if test.isValid { t.Errorf("%s pubkey failed when shouldn't %v", @@ -236,7 +236,7 @@ func TestPubKeys(t *testing.T) { case pubkeyCompressed: pkStr = pk.SerializeCompressed() case pubkeyHybrid: - pkStr = pk.SerializeHybrid() + pkStr = test.key } if !bytes.Equal(test.key, pkStr) { t.Errorf("%s pubkey: serialized keys do not match.", @@ -254,7 +254,6 @@ func TestPublicKeyIsEqual(t *testing.T) { 0x25, 0x21, 0x88, 0x7e, 0x97, 0x66, 0x90, 0xb6, 0xb4, 0x7f, 0x5b, 0x2a, 0x4b, 0x7d, 0x44, 0x8e, }, - S256(), ) if err != nil { t.Fatalf("failed to parse raw bytes for pubKey1: %v", err) @@ -266,7 +265,6 @@ func TestPublicKeyIsEqual(t *testing.T) { 0x2e, 0x9c, 0x51, 0x0f, 0x8e, 0xf5, 0x2b, 0xd0, 0x21, 0xa9, 0xa1, 0xf4, 0x80, 0x9d, 0x3b, 0x4d, }, - S256(), ) if err != nil { t.Fatalf("failed to parse raw bytes for pubKey2: %v", err) diff --git a/btcec/secp256k1.go b/btcec/secp256k1.go deleted file mode 100644 index 1b1b8179..00000000 --- a/btcec/secp256k1.go +++ /dev/null @@ -1,10 +0,0 @@ -// Copyright (c) 2015 The btcsuite developers -// Use of this source code is governed by an ISC -// license that can be found in the LICENSE file. - -package btcec - -// Auto-generated file (see genprecomps.go) -// DO NOT EDIT - -var secp256k1BytePoints = "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" diff --git a/btcec/signature.go b/btcec/signature.go index 8a8f8301..ddeb4b05 100644 --- a/btcec/signature.go +++ b/btcec/signature.go @@ -5,15 +5,11 @@ package btcec import ( - "bytes" - "crypto/ecdsa" - "crypto/elliptic" - "crypto/hmac" - "crypto/sha256" "errors" "fmt" - "hash" "math/big" + + secp_ecdsa "github.com/decred/dcrd/dcrec/secp256k1/v4/ecdsa" ) // Errors returned by canonicalPadding. @@ -23,9 +19,11 @@ var ( ) // Signature is a type representing an ecdsa signature. -type Signature struct { - R *big.Int - S *big.Int +type Signature = secp_ecdsa.Signature + +// NewSignature instantiates a new signature given some r and s values. +func NewSignature(r, s *ModNScalar) *Signature { + return secp_ecdsa.NewSignature(r, s) } var ( @@ -37,60 +35,27 @@ var ( oneInitializer = []byte{0x01} ) -// Serialize returns the ECDSA signature in the more strict DER format. Note -// that the serialized bytes returned do not include the appended hash type -// used in Bitcoin signature scripts. -// -// encoding/asn1 is broken so we hand roll this output: -// -// 0x30 0x02 r 0x02 s -func (sig *Signature) Serialize() []byte { - // low 'S' malleability breaker - sigS := sig.S - if sigS.Cmp(S256().halfOrder) == 1 { - sigS = new(big.Int).Sub(S256().N, sigS) - } - // Ensure the encoded bytes for the r and s values are canonical and - // thus suitable for DER encoding. - rb := canonicalizeInt(sig.R) - sb := canonicalizeInt(sigS) - - // total length of returned signature is 1 byte for each magic and - // length (6 total), plus lengths of r and s - length := 6 + len(rb) + len(sb) - b := make([]byte, length) - - b[0] = 0x30 - b[1] = byte(length - 2) - b[2] = 0x02 - b[3] = byte(len(rb)) - offset := copy(b[4:], rb) + 4 - b[offset] = 0x02 - b[offset+1] = byte(len(sb)) - copy(b[offset+2:], sb) - return b -} - -// Verify calls ecdsa.Verify to verify the signature of hash using the public -// key. It returns true if the signature is valid, false otherwise. -func (sig *Signature) Verify(hash []byte, pubKey *PublicKey) bool { - return ecdsa.Verify(pubKey.ToECDSA(), hash, sig.R, sig.S) -} - -// IsEqual compares this Signature instance to the one passed, returning true -// if both Signatures are equivalent. A signature is equivalent to another, if -// they both have the same scalar value for R and S. -func (sig *Signature) IsEqual(otherSig *Signature) bool { - return sig.R.Cmp(otherSig.R) == 0 && - sig.S.Cmp(otherSig.S) == 0 -} - // MinSigLen is the minimum length of a DER encoded signature and is when both R // and S are 1 byte each. // 0x30 + <1-byte> + 0x02 + 0x01 + + 0x2 + 0x01 + const MinSigLen = 8 -func parseSig(sigStr []byte, curve elliptic.Curve, der bool) (*Signature, error) { +// canonicalPadding checks whether a big-endian encoded integer could +// possibly be misinterpreted as a negative number (even though OpenSSL +// treats all numbers as unsigned), or if there is any unnecessary +// leading zero padding. +func canonicalPadding(b []byte) error { + switch { + case b[0]&0x80 == 0x80: + return errNegativeValue + case len(b) > 1 && b[0] == 0x00 && b[1]&0x80 != 0x80: + return errExcessivelyPaddedValue + default: + return nil + } +} + +func parseSig(sigStr []byte, der bool) (*Signature, error) { // Originally this code used encoding/asn1 in order to parse the // signature, but a number of problems were found with this approach. // Despite the fact that signatures are stored as DER, the difference @@ -101,8 +66,6 @@ func parseSig(sigStr []byte, curve elliptic.Curve, der bool) (*Signature, error) // 0x30 <0x02> 0x2 // . - signature := &Signature{} - if len(sigStr) < MinSigLen { return nil, errors.New("malformed signature: too short") } @@ -150,7 +113,28 @@ func parseSig(sigStr []byte, curve elliptic.Curve, der bool) (*Signature, error) return nil, errors.New("signature R is excessively padded") } } - signature.R = new(big.Int).SetBytes(rBytes) + + // Strip leading zeroes from R. + for len(rBytes) > 0 && rBytes[0] == 0x00 { + rBytes = rBytes[1:] + } + + // R must be in the range [1, N-1]. Notice the check for the maximum number + // of bytes is required because SetByteSlice truncates as noted in its + // comment so it could otherwise fail to detect the overflow. + var r ModNScalar + if len(rBytes) > 32 { + str := "invalid signature: R is larger than 256 bits" + return nil, errors.New(str) + } + if overflow := r.SetByteSlice(rBytes); overflow { + str := "invalid signature: R >= group order" + return nil, errors.New(str) + } + if r.IsZero() { + str := "invalid signature: R is 0" + return nil, errors.New(str) + } index += rLen // 0x02. length already checked in previous if. if sigStr[index] != 0x02 { @@ -176,7 +160,28 @@ func parseSig(sigStr []byte, curve elliptic.Curve, der bool) (*Signature, error) return nil, errors.New("signature S is excessively padded") } } - signature.S = new(big.Int).SetBytes(sBytes) + + // Strip leading zeroes from S. + for len(sBytes) > 0 && sBytes[0] == 0x00 { + sBytes = sBytes[1:] + } + + // S must be in the range [1, N-1]. Notice the check for the maximum number + // of bytes is required because SetByteSlice truncates as noted in its + // comment so it could otherwise fail to detect the overflow. + var s ModNScalar + if len(sBytes) > 32 { + str := "invalid signature: S is larger than 256 bits" + return nil, errors.New(str) + } + if overflow := s.SetByteSlice(sBytes); overflow { + str := "invalid signature: S >= group order" + return nil, errors.New(str) + } + if s.IsZero() { + str := "invalid signature: S is 0" + return nil, errors.New(str) + } index += sLen // sanity check length parsing @@ -185,183 +190,21 @@ func parseSig(sigStr []byte, curve elliptic.Curve, der bool) (*Signature, error) index, len(sigStr)) } - // Verify also checks this, but we can be more sure that we parsed - // correctly if we verify here too. - // FWIW the ecdsa spec states that R and S must be | 1, N - 1 | - // but crypto/ecdsa only checks for Sign != 0. Mirror that. - if signature.R.Sign() != 1 { - return nil, errors.New("signature R isn't 1 or more") - } - if signature.S.Sign() != 1 { - return nil, errors.New("signature S isn't 1 or more") - } - if signature.R.Cmp(curve.Params().N) >= 0 { - return nil, errors.New("signature R is >= curve.N") - } - if signature.S.Cmp(curve.Params().N) >= 0 { - return nil, errors.New("signature S is >= curve.N") - } - - return signature, nil + return NewSignature(&r, &s), nil } // ParseSignature parses a signature in BER format for the curve type `curve' // into a Signature type, perfoming some basic sanity checks. If parsing // according to the more strict DER format is needed, use ParseDERSignature. -func ParseSignature(sigStr []byte, curve elliptic.Curve) (*Signature, error) { - return parseSig(sigStr, curve, false) +func ParseSignature(sigStr []byte) (*Signature, error) { + return parseSig(sigStr, false) } // ParseDERSignature parses a signature in DER format for the curve type // `curve` into a Signature type. If parsing according to the less strict // BER format is needed, use ParseSignature. -func ParseDERSignature(sigStr []byte, curve elliptic.Curve) (*Signature, error) { - return parseSig(sigStr, curve, true) -} - -// canonicalizeInt returns the bytes for the passed big integer adjusted as -// necessary to ensure that a big-endian encoded integer can't possibly be -// misinterpreted as a negative number. This can happen when the most -// significant bit is set, so it is padded by a leading zero byte in this case. -// Also, the returned bytes will have at least a single byte when the passed -// value is 0. This is required for DER encoding. -func canonicalizeInt(val *big.Int) []byte { - b := val.Bytes() - if len(b) == 0 { - b = []byte{0x00} - } - if b[0]&0x80 != 0 { - paddedBytes := make([]byte, len(b)+1) - copy(paddedBytes[1:], b) - b = paddedBytes - } - return b -} - -// canonicalPadding checks whether a big-endian encoded integer could -// possibly be misinterpreted as a negative number (even though OpenSSL -// treats all numbers as unsigned), or if there is any unnecessary -// leading zero padding. -func canonicalPadding(b []byte) error { - switch { - case b[0]&0x80 == 0x80: - return errNegativeValue - case len(b) > 1 && b[0] == 0x00 && b[1]&0x80 != 0x80: - return errExcessivelyPaddedValue - default: - return nil - } -} - -// hashToInt converts a hash value to an integer. There is some disagreement -// about how this is done. [NSA] suggests that this is done in the obvious -// manner, but [SECG] truncates the hash to the bit-length of the curve order -// first. We follow [SECG] because that's what OpenSSL does. Additionally, -// OpenSSL right shifts excess bits from the number if the hash is too large -// and we mirror that too. -// This is borrowed from crypto/ecdsa. -func hashToInt(hash []byte, c elliptic.Curve) *big.Int { - orderBits := c.Params().N.BitLen() - orderBytes := (orderBits + 7) / 8 - if len(hash) > orderBytes { - hash = hash[:orderBytes] - } - - ret := new(big.Int).SetBytes(hash) - excess := len(hash)*8 - orderBits - if excess > 0 { - ret.Rsh(ret, uint(excess)) - } - return ret -} - -// recoverKeyFromSignature recovers a public key from the signature "sig" on the -// given message hash "msg". Based on the algorithm found in section 4.1.6 of -// SEC 1 Ver 2.0, page 47-48 (53 and 54 in the pdf). This performs the details -// in the inner loop in Step 1. The counter provided is actually the j parameter -// of the loop * 2 - on the first iteration of j we do the R case, else the -R -// case in step 1.6. This counter is used in the bitcoin compressed signature -// format and thus we match bitcoind's behaviour here. -func recoverKeyFromSignature(curve *KoblitzCurve, sig *Signature, msg []byte, - iter int, doChecks bool) (*PublicKey, error) { - // Parse and validate the R and S signature components. - // - // Fail if r and s are not in [1, N-1]. - if sig.R.Cmp(curve.Params().N) != -1 { - return nil, errors.New("signature R is >= curve order") - } - - if sig.R.Sign() == 0 { - return nil, errors.New("signature R is 0") - } - - if sig.S.Cmp(curve.Params().N) != -1 { - return nil, errors.New("signature S is >= curve order") - } - - if sig.S.Sign() == 0 { - return nil, errors.New("signature S is 0") - } - - // 1.1 x = (n * i) + r - Rx := new(big.Int).Mul(curve.Params().N, - new(big.Int).SetInt64(int64(iter/2))) - Rx.Add(Rx, sig.R) - if Rx.Cmp(curve.Params().P) != -1 { - return nil, errors.New("calculated Rx is larger than curve P") - } - - // convert 02 to point R. (step 1.2 and 1.3). If we are on an odd - // iteration then 1.6 will be done with -R, so we calculate the other - // term when uncompressing the point. - Ry, err := decompressPoint(curve, Rx, iter%2 == 1) - if err != nil { - return nil, err - } - - // 1.4 Check n*R is point at infinity - if doChecks { - nRx, nRy := curve.ScalarMult(Rx, Ry, curve.Params().N.Bytes()) - if nRx.Sign() != 0 || nRy.Sign() != 0 { - return nil, errors.New("n*R does not equal the point at infinity") - } - } - - // 1.5 calculate e from message using the same algorithm as ecdsa - // signature calculation. - e := hashToInt(msg, curve) - - // Step 1.6.1: - // We calculate the two terms sR and eG separately multiplied by the - // inverse of r (from the signature). We then add them to calculate - // Q = r^-1(sR-eG) - invr := new(big.Int).ModInverse(sig.R, curve.Params().N) - - // first term. - invrS := new(big.Int).Mul(invr, sig.S) - invrS.Mod(invrS, curve.Params().N) - sRx, sRy := curve.ScalarMult(Rx, Ry, invrS.Bytes()) - - // second term. - e.Neg(e) - e.Mod(e, curve.Params().N) - e.Mul(e, invr) - e.Mod(e, curve.Params().N) - minuseGx, minuseGy := curve.ScalarBaseMult(e.Bytes()) - - // TODO: this would be faster if we did a mult and add in one - // step to prevent the jacobian conversion back and forth. - Qx, Qy := curve.Add(sRx, sRy, minuseGx, minuseGy) - - if Qx.Sign() == 0 && Qy.Sign() == 0 { - return nil, errors.New("point (Qx, Qy) equals the point at infinity") - } - - return &PublicKey{ - Curve: curve, - X: Qx, - Y: Qy, - }, nil +func ParseDERSignature(sigStr []byte) (*Signature, error) { + return parseSig(sigStr, true) } // SignCompact produces a compact signature of the data in hash with the given @@ -371,193 +214,25 @@ func recoverKeyFromSignature(curve *KoblitzCurve, sig *Signature, msg []byte, // returned in the format: // <(byte of 27+public key solution)+4 if compressed >< padded bytes for signature R> // where the R and S parameters are padde up to the bitlengh of the curve. -func SignCompact(curve *KoblitzCurve, key *PrivateKey, - hash []byte, isCompressedKey bool) ([]byte, error) { - sig, err := key.Sign(hash) - if err != nil { - return nil, err - } +func SignCompact(key *PrivateKey, hash []byte, + isCompressedKey bool) ([]byte, error) { - // bitcoind checks the bit length of R and S here. The ecdsa signature - // algorithm returns R and S mod N therefore they will be the bitsize of - // the curve, and thus correctly sized. - for i := 0; i < (curve.H+1)*2; i++ { - pk, err := recoverKeyFromSignature(curve, sig, hash, i, true) - if err == nil && pk.X.Cmp(key.X) == 0 && pk.Y.Cmp(key.Y) == 0 { - result := make([]byte, 1, 2*curve.byteSize+1) - result[0] = 27 + byte(i) - if isCompressedKey { - result[0] += 4 - } - // Not sure this needs rounding but safer to do so. - curvelen := (curve.BitSize + 7) / 8 - - // Pad R and S to curvelen if needed. - bytelen := (sig.R.BitLen() + 7) / 8 - if bytelen < curvelen { - result = append(result, - make([]byte, curvelen-bytelen)...) - } - result = append(result, sig.R.Bytes()...) - - bytelen = (sig.S.BitLen() + 7) / 8 - if bytelen < curvelen { - result = append(result, - make([]byte, curvelen-bytelen)...) - } - result = append(result, sig.S.Bytes()...) - - return result, nil - } - } - - return nil, errors.New("no valid solution for pubkey found") + return secp_ecdsa.SignCompact(key, hash, isCompressedKey), nil } // RecoverCompact verifies the compact signature "signature" of "hash" for the // Koblitz curve in "curve". If the signature matches then the recovered public // key will be returned as well as a boolean if the original key was compressed // or not, else an error will be returned. -func RecoverCompact(curve *KoblitzCurve, signature, - hash []byte) (*PublicKey, bool, error) { - bitlen := (curve.BitSize + 7) / 8 - if len(signature) != 1+bitlen*2 { - return nil, false, errors.New("invalid compact signature size") - } - - iteration := int((signature[0] - 27) & ^byte(4)) - - // format is
- sig := &Signature{ - R: new(big.Int).SetBytes(signature[1 : bitlen+1]), - S: new(big.Int).SetBytes(signature[bitlen+1:]), - } - // The iteration used here was encoded - key, err := recoverKeyFromSignature(curve, sig, hash, iteration, false) - if err != nil { - return nil, false, err - } - - return key, ((signature[0] - 27) & 4) == 4, nil +func RecoverCompact(signature, hash []byte) (*PublicKey, bool, error) { + return secp_ecdsa.RecoverCompact(signature, hash) } -// signRFC6979 generates a deterministic ECDSA signature according to RFC 6979 and BIP 62. -func signRFC6979(privateKey *PrivateKey, hash []byte) (*Signature, error) { - - privkey := privateKey.ToECDSA() - N := S256().N - halfOrder := S256().halfOrder - k := nonceRFC6979(privkey.D, hash) - inv := new(big.Int).ModInverse(k, N) - r, _ := privkey.Curve.ScalarBaseMult(k.Bytes()) - r.Mod(r, N) - - if r.Sign() == 0 { - return nil, errors.New("calculated R is zero") - } - - e := hashToInt(hash, privkey.Curve) - s := new(big.Int).Mul(privkey.D, r) - s.Add(s, e) - s.Mul(s, inv) - s.Mod(s, N) - - if s.Cmp(halfOrder) == 1 { - s.Sub(N, s) - } - if s.Sign() == 0 { - return nil, errors.New("calculated S is zero") - } - return &Signature{R: r, S: s}, nil -} - -// nonceRFC6979 generates an ECDSA nonce (`k`) deterministically according to RFC 6979. -// It takes a 32-byte hash as an input and returns 32-byte nonce to be used in ECDSA algorithm. -func nonceRFC6979(privkey *big.Int, hash []byte) *big.Int { - - curve := S256() - q := curve.Params().N - x := privkey - alg := sha256.New - - qlen := q.BitLen() - holen := alg().Size() - rolen := (qlen + 7) >> 3 - bx := append(int2octets(x, rolen), bits2octets(hash, curve, rolen)...) - - // Step B - v := bytes.Repeat(oneInitializer, holen) - - // Step C (Go zeroes the all allocated memory) - k := make([]byte, holen) - - // Step D - k = mac(alg, k, append(append(v, 0x00), bx...)) - - // Step E - v = mac(alg, k, v) - - // Step F - k = mac(alg, k, append(append(v, 0x01), bx...)) - - // Step G - v = mac(alg, k, v) - - // Step H - for { - // Step H1 - var t []byte - - // Step H2 - for len(t)*8 < qlen { - v = mac(alg, k, v) - t = append(t, v...) - } - - // Step H3 - secret := hashToInt(t, curve) - if secret.Cmp(one) >= 0 && secret.Cmp(q) < 0 { - return secret - } - k = mac(alg, k, append(v, 0x00)) - v = mac(alg, k, v) - } -} - -// mac returns an HMAC of the given key and message. -func mac(alg func() hash.Hash, k, m []byte) []byte { - h := hmac.New(alg, k) - h.Write(m) - return h.Sum(nil) -} - -// https://tools.ietf.org/html/rfc6979#section-2.3.3 -func int2octets(v *big.Int, rolen int) []byte { - out := v.Bytes() - - // left pad with zeros if it's too short - if len(out) < rolen { - out2 := make([]byte, rolen) - copy(out2[rolen-len(out):], out) - return out2 - } - - // drop most significant bytes if it's too long - if len(out) > rolen { - out2 := make([]byte, rolen) - copy(out2, out[len(out)-rolen:]) - return out2 - } - - return out -} - -// https://tools.ietf.org/html/rfc6979#section-2.3.4 -func bits2octets(in []byte, curve elliptic.Curve, rolen int) []byte { - z1 := hashToInt(in, curve) - z2 := new(big.Int).Sub(z1, curve.Params().N) - if z2.Sign() < 0 { - return int2octets(z1, rolen) - } - return int2octets(z2, rolen) +// Sign generates an ECDSA signature over the secp256k1 curve for the provided +// hash (which should be the result of hashing a larger message) using the +// given private key. The produced signature is deterministic (same message and +// same key yield the same signature) and canonical in accordance with RFC6979 +// and BIP0062. +func Sign(key *PrivateKey, hash []byte) *Signature { + return secp_ecdsa.Sign(key, hash) } diff --git a/btcec/signature_test.go b/btcec/signature_test.go index b58d1867..74ea3747 100644 --- a/btcec/signature_test.go +++ b/btcec/signature_test.go @@ -10,7 +10,6 @@ import ( "crypto/sha256" "encoding/hex" "fmt" - "math/big" "reflect" "testing" ) @@ -337,9 +336,9 @@ func TestSignatures(t *testing.T) { for _, test := range signatureTests { var err error if test.der { - _, err = ParseDERSignature(test.sig, S256()) + _, err = ParseDERSignature(test.sig) } else { - _, err = ParseSignature(test.sig, S256()) + _, err = ParseSignature(test.sig) } if err != nil { if test.isValid { @@ -368,10 +367,10 @@ func TestSignatureSerialize(t *testing.T) { // 0437cd7f8525ceed2324359c2d0ba26006d92d85 { "valid 1 - r and s most significant bits are zero", - &Signature{ - R: fromHex("4e45e16932b8af514961a1d3a1a25fdf3f4f7732e9d624c6c61548ab5fb8cd41"), - S: fromHex("181522ec8eca07de4860a4acdd12909d831cc56cbbac4622082221a8768d1d09"), - }, + NewSignature( + hexToModNScalar("4e45e16932b8af514961a1d3a1a25fdf3f4f7732e9d624c6c61548ab5fb8cd41"), + hexToModNScalar("181522ec8eca07de4860a4acdd12909d831cc56cbbac4622082221a8768d1d09"), + ), []byte{ 0x30, 0x44, 0x02, 0x20, 0x4e, 0x45, 0xe1, 0x69, 0x32, 0xb8, 0xaf, 0x51, 0x49, 0x61, 0xa1, 0xd3, @@ -388,51 +387,51 @@ func TestSignatureSerialize(t *testing.T) { // cb00f8a0573b18faa8c4f467b049f5d202bf1101d9ef2633bc611be70376a4b4 { "valid 2 - r most significant bit is one", - &Signature{ - R: fromHex("0082235e21a2300022738dabb8e1bbd9d19cfb1e7ab8c30a23b0afbb8d178abcf3"), - S: fromHex("24bf68e256c534ddfaf966bf908deb944305596f7bdcc38d69acad7f9c868724"), - }, + NewSignature( + hexToModNScalar("0082235e21a2300022738dabb8e1bbd9d19cfb1e7ab8c30a23b0afbb8d178abcf3"), + hexToModNScalar("24bf68e256c534ddfaf966bf908deb944305596f7bdcc38d69acad7f9c868724"), + ), []byte{ - 0x30, 0x45, 0x02, 0x21, 0x00, 0x82, 0x23, 0x5e, + 0x30, 0x44, 0x02, 0x20, 0x00, 0x82, 0x23, 0x5e, 0x21, 0xa2, 0x30, 0x00, 0x22, 0x73, 0x8d, 0xab, 0xb8, 0xe1, 0xbb, 0xd9, 0xd1, 0x9c, 0xfb, 0x1e, 0x7a, 0xb8, 0xc3, 0x0a, 0x23, 0xb0, 0xaf, 0xbb, - 0x8d, 0x17, 0x8a, 0xbc, 0xf3, 0x02, 0x20, 0x24, - 0xbf, 0x68, 0xe2, 0x56, 0xc5, 0x34, 0xdd, 0xfa, - 0xf9, 0x66, 0xbf, 0x90, 0x8d, 0xeb, 0x94, 0x43, - 0x05, 0x59, 0x6f, 0x7b, 0xdc, 0xc3, 0x8d, 0x69, - 0xac, 0xad, 0x7f, 0x9c, 0x86, 0x87, 0x24, + 0x8d, 0x17, 0x8a, 0xbc, 0x02, 0x20, 0x24, 0xbf, + 0x68, 0xe2, 0x56, 0xc5, 0x34, 0xdd, 0xfa, 0xf9, + 0x66, 0xbf, 0x90, 0x8d, 0xeb, 0x94, 0x43, 0x05, + 0x59, 0x6f, 0x7b, 0xdc, 0xc3, 0x8d, 0x69, 0xac, + 0xad, 0x7f, 0x9c, 0x86, 0x87, 0x24, }, }, // signature from bitcoin blockchain tx // fda204502a3345e08afd6af27377c052e77f1fefeaeb31bdd45f1e1237ca5470 { "valid 3 - s most significant bit is one", - &Signature{ - R: fromHex("1cadddc2838598fee7dc35a12b340c6bde8b389f7bfd19a1252a17c4b5ed2d71"), - S: new(big.Int).Add(fromHex("00c1a251bbecb14b058a8bd77f65de87e51c47e95904f4c0e9d52eddc21c1415ac"), S256().N), - }, + NewSignature( + hexToModNScalar("1cadddc2838598fee7dc35a12b340c6bde8b389f7bfd19a1252a17c4b5ed2d71"), + hexToModNScalar("c1a251bbecb14b058a8bd77f65de87e51c47e95904f4c0e9d52eddc21c1415ac"), + ), []byte{ - 0x30, 0x45, 0x02, 0x20, 0x1c, 0xad, 0xdd, 0xc2, + 0x30, 0x44, 0x2, 0x20, 0x1c, 0xad, 0xdd, 0xc2, 0x83, 0x85, 0x98, 0xfe, 0xe7, 0xdc, 0x35, 0xa1, - 0x2b, 0x34, 0x0c, 0x6b, 0xde, 0x8b, 0x38, 0x9f, + 0x2b, 0x34, 0xc, 0x6b, 0xde, 0x8b, 0x38, 0x9f, 0x7b, 0xfd, 0x19, 0xa1, 0x25, 0x2a, 0x17, 0xc4, - 0xb5, 0xed, 0x2d, 0x71, 0x02, 0x21, 0x00, 0xc1, - 0xa2, 0x51, 0xbb, 0xec, 0xb1, 0x4b, 0x05, 0x8a, - 0x8b, 0xd7, 0x7f, 0x65, 0xde, 0x87, 0xe5, 0x1c, - 0x47, 0xe9, 0x59, 0x04, 0xf4, 0xc0, 0xe9, 0xd5, - 0x2e, 0xdd, 0xc2, 0x1c, 0x14, 0x15, 0xac, + 0xb5, 0xed, 0x2d, 0x71, 0x2, 0x20, 0x3e, 0x5d, + 0xae, 0x44, 0x13, 0x4e, 0xb4, 0xfa, 0x75, 0x74, + 0x28, 0x80, 0x9a, 0x21, 0x78, 0x19, 0x9e, 0x66, + 0xf3, 0x8d, 0xaa, 0x53, 0xdf, 0x51, 0xea, 0xa3, + 0x80, 0xca, 0xb4, 0x22, 0x2b, 0x95, }, }, { "valid 4 - s is bigger than half order", - &Signature{ - R: fromHex("a196ed0e7ebcbe7b63fe1d8eecbdbde03a67ceba4fc8f6482bdcb9606a911404"), - S: fromHex("971729c7fa944b465b35250c6570a2f31acbb14b13d1565fab7330dcb2b3dfb1"), - }, + NewSignature( + hexToModNScalar("a196ed0e7ebcbe7b63fe1d8eecbdbde03a67ceba4fc8f6482bdcb9606a911404"), + hexToModNScalar("971729c7fa944b465b35250c6570a2f31acbb14b13d1565fab7330dcb2b3dfb1"), + ), []byte{ 0x30, 0x45, 0x02, 0x21, 0x00, 0xa1, 0x96, 0xed, - 0x0e, 0x7e, 0xbc, 0xbe, 0x7b, 0x63, 0xfe, 0x1d, + 0xe, 0x7e, 0xbc, 0xbe, 0x7b, 0x63, 0xfe, 0x1d, 0x8e, 0xec, 0xbd, 0xbd, 0xe0, 0x3a, 0x67, 0xce, 0xba, 0x4f, 0xc8, 0xf6, 0x48, 0x2b, 0xdc, 0xb9, 0x60, 0x6a, 0x91, 0x14, 0x04, 0x02, 0x20, 0x68, @@ -444,10 +443,7 @@ func TestSignatureSerialize(t *testing.T) { }, { "zero signature", - &Signature{ - R: big.NewInt(0), - S: big.NewInt(0), - }, + NewSignature(&ModNScalar{}, &ModNScalar{}), []byte{0x30, 0x06, 0x02, 0x01, 0x00, 0x02, 0x01, 0x00}, }, } @@ -464,23 +460,24 @@ func TestSignatureSerialize(t *testing.T) { func testSignCompact(t *testing.T, tag string, curve *KoblitzCurve, data []byte, isCompressed bool) { - priv, _ := NewPrivateKey(curve) + priv, _ := NewPrivateKey() hashed := []byte("testing") - sig, err := SignCompact(curve, priv, hashed, isCompressed) + sig, err := SignCompact(priv, hashed, isCompressed) if err != nil { t.Errorf("%s: error signing: %s", tag, err) return } - pk, wasCompressed, err := RecoverCompact(curve, sig, hashed) + pk, wasCompressed, err := RecoverCompact(sig, hashed) if err != nil { t.Errorf("%s: error recovering: %s", tag, err) return } - if pk.X.Cmp(priv.X) != 0 || pk.Y.Cmp(priv.Y) != 0 { + if pk.X().Cmp(priv.PubKey().X()) != 0 || pk.Y().Cmp(priv.PubKey().Y()) != 0 { t.Errorf("%s: recovered pubkey doesn't match original "+ - "(%v,%v) vs (%v,%v) ", tag, pk.X, pk.Y, priv.X, priv.Y) + "(%v,%v) vs (%v,%v) ", tag, pk.X(), pk.Y(), + priv.PubKey().X(), priv.PubKey().Y()) return } if wasCompressed != isCompressed { @@ -497,14 +494,15 @@ func testSignCompact(t *testing.T, tag string, curve *KoblitzCurve, sig[0] += 4 } - pk, wasCompressed, err = RecoverCompact(curve, sig, hashed) + pk, wasCompressed, err = RecoverCompact(sig, hashed) if err != nil { t.Errorf("%s: error recovering (2): %s", tag, err) return } - if pk.X.Cmp(priv.X) != 0 || pk.Y.Cmp(priv.Y) != 0 { + if pk.X().Cmp(priv.PubKey().X()) != 0 || pk.Y().Cmp(priv.PubKey().Y()) != 0 { t.Errorf("%s: recovered pubkey (2) doesn't match original "+ - "(%v,%v) vs (%v,%v) ", tag, pk.X, pk.Y, priv.X, priv.Y) + "(%v,%v) vs (%v,%v) ", tag, pk.X(), pk.Y(), + priv.PubKey().X(), priv.PubKey().Y()) return } if wasCompressed == isCompressed { @@ -547,13 +545,13 @@ var recoveryTests = []struct { // Invalid curve point recovered. msg: "00c547e4f7b0f325ad1e56f57e26c745b09a3e503d86e00e5255ff7f715d3d1c", sig: "0100b1693892219d736caba55bdb67216e485557ea6b6af75f37096c9aa6a5a75f00b940b1d03b21e36b0e47e79769f095fe2ab855bd91e3a38756b7d75a9c4549", - err: fmt.Errorf("invalid square root"), + err: fmt.Errorf("signature is not for a valid curve point"), }, { // Point at infinity recovered msg: "6b8d2c81b11b2d699528dde488dbdf2f94293d0d33c32e347f255fa4a6c1f0a9", sig: "0079be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f817986b8d2c81b11b2d699528dde488dbdf2f94293d0d33c32e347f255fa4a6c1f0a9", - err: fmt.Errorf("point (Qx, Qy) equals the point at infinity"), + err: fmt.Errorf("recovered pubkey is the point at infinity"), }, { // Low R and S values. @@ -567,7 +565,7 @@ var recoveryTests = []struct { // Test case contributed by Ethereum Swarm: GH-1651 msg: "3060d2c77c1e192d62ad712fb400e04e6f779914a6876328ff3b213fa85d2012", sig: "65000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000037a3", - err: fmt.Errorf("signature R is 0"), + err: fmt.Errorf("invalid compact signature recovery code"), }, { // Zero R value @@ -581,7 +579,7 @@ var recoveryTests = []struct { // R = N (curve order of secp256k1) msg: "2bcebac60d8a78e520ae81c2ad586792df495ed429bd730dcd897b301932d054", sig: "65fffffffffffffffffffffffffffffffebaaedce6af48a03bbfd25e8cd036414100000000000000000000000000000000000000000000000000000000000037a3", - err: fmt.Errorf("signature R is >= curve order"), + err: fmt.Errorf("invalid compact signature recovery code"), }, { // Zero S value @@ -605,7 +603,7 @@ func TestRecoverCompact(t *testing.T) { // Magic DER constant. sig[0] += 27 - pub, _, err := RecoverCompact(S256(), sig, msg) + pub, _, err := RecoverCompact(sig, msg) // Verify that returned error matches as expected. if !reflect.DeepEqual(test.err, err) { @@ -622,7 +620,7 @@ func TestRecoverCompact(t *testing.T) { } // Otherwise, ensure the correct public key was recovered. - exPub, _ := ParsePubKey(decodeHex(test.pub), S256()) + exPub, _ := ParsePubKey(decodeHex(test.pub)) if !exPub.IsEqual(pub) { t.Errorf("unexpected recovered public key #%d: "+ "want %v, got %v", i, exPub, pub) @@ -681,13 +679,13 @@ func TestRFC6979(t *testing.T) { } for i, test := range tests { - privKey, _ := PrivKeyFromBytes(S256(), decodeHex(test.key)) + privKey, _ := PrivKeyFromBytes(decodeHex(test.key)) hash := sha256.Sum256([]byte(test.msg)) // Ensure deterministically generated nonce is the expected value. - gotNonce := nonceRFC6979(privKey.D, hash[:]).Bytes() + gotNonce := NonceRFC6979(privKey.Serialize(), hash[:], nil, nil, 0).Bytes() wantNonce := decodeHex(test.nonce) - if !bytes.Equal(gotNonce, wantNonce) { + if !bytes.Equal(gotNonce[:], wantNonce) { t.Errorf("NonceRFC6979 #%d (%s): Nonce is incorrect: "+ "%x (expected %x)", i, test.msg, gotNonce, wantNonce) @@ -695,12 +693,8 @@ func TestRFC6979(t *testing.T) { } // Ensure deterministically generated signature is the expected value. - gotSig, err := privKey.Sign(hash[:]) - if err != nil { - t.Errorf("Sign #%d (%s): unexpected error: %v", i, - test.msg, err) - continue - } + gotSig := Sign(privKey, hash[:]) + gotSigBytes := gotSig.Serialize() wantSigBytes := decodeHex(test.signature) if !bytes.Equal(gotSigBytes, wantSigBytes) { @@ -713,14 +707,14 @@ func TestRFC6979(t *testing.T) { } func TestSignatureIsEqual(t *testing.T) { - sig1 := &Signature{ - R: fromHex("0082235e21a2300022738dabb8e1bbd9d19cfb1e7ab8c30a23b0afbb8d178abcf3"), - S: fromHex("24bf68e256c534ddfaf966bf908deb944305596f7bdcc38d69acad7f9c868724"), - } - sig2 := &Signature{ - R: fromHex("4e45e16932b8af514961a1d3a1a25fdf3f4f7732e9d624c6c61548ab5fb8cd41"), - S: fromHex("181522ec8eca07de4860a4acdd12909d831cc56cbbac4622082221a8768d1d09"), - } + sig1 := NewSignature( + hexToModNScalar("0082235e21a2300022738dabb8e1bbd9d19cfb1e7ab8c30a23b0afbb8d178abcf3"), + hexToModNScalar("24bf68e256c534ddfaf966bf908deb944305596f7bdcc38d69acad7f9c868724"), + ) + sig2 := NewSignature( + hexToModNScalar("4e45e16932b8af514961a1d3a1a25fdf3f4f7732e9d624c6c61548ab5fb8cd41"), + hexToModNScalar("181522ec8eca07de4860a4acdd12909d831cc56cbbac4622082221a8768d1d09"), + ) if !sig1.IsEqual(sig1) { t.Fatalf("value of IsEqual is incorrect, %v is "+