RFE Standards

Minimum Viable Standard MVS & Request for Evidence RFE Framework - Decompose bloated, legacy RFCs X.509/ASN.1 and RFC 3986 URIs into usage-driven, empirical standards. Coverage is dictated by observable real-world usage data plus an explicit Criticality Override Registry - not design-by-committee...

assimp:assimp_fuzzer: Use-of-uninitialized-value in aiMatrix4x4t<float>::Decompose

Detailed Report: https://oss-fuzz.com/testcase?key=5370859673157632 Project: assimp Fuzzing Engine: libFuzzer Fuzz Target: assimpfuzzer Job Type: libfuzzermsanassimp Platform Id: linux Crash Type: Use-of-uninitialized-value Crash Address: Crash State: aiMatrix4x4t::Decompose...

CVE-2026-22705

RustCrypto: Signatures offers support for digital signatures, which provide authentication of data using public-key cryptography. Prior to version 0.1.0-rc.2, a timing side-channel was discovered in the Decompose algorithm which is used during ML-DSA signing to generate hints for the signature...

EUVD-2026-1867

RustCrypto: Signatures has timing side-channel in ML-DSA decomposition...

GHSA-HCP2-X6J4-29J7 RustCrypto: Signatures has timing side-channel in ML-DSA decomposition

Summary A timing side-channel was discovered in the Decompose algorithm which is used during ML-DSA signing to generate hints for the signature. Details The analysis was performed using a constant-time analyzer that examines compiled assembly code for instructions with data-dependent timing...

RustCrypto: Signatures has timing side-channel in ML-DSA decomposition

Summary A timing side-channel was discovered in the Decompose algorithm which is used during ML-DSA signing to generate hints for the signature. Details The analysis was performed using a constant-time analyzer that examines compiled assembly code for instructions with data-dependent timing...

CVE-2026-22705

RustCrypto: Signatures offers support for digital signatures, which provide authentication of data using public-key cryptography. Prior to version 0.1.0-rc.2, a timing side-channel was discovered in the Decompose algorithm which is used during ML-DSA signing to generate hints for the signature...

CVE-2026-22705 RustCrypto: Signatures has timing side-channel in ML-DSA decomposition

RustCrypto: Signatures offers support for digital signatures, which provide authentication of data using public-key cryptography. Prior to version 0.1.0-rc.2, a timing side-channel was discovered in the Decompose algorithm which is used during ML-DSA signing to generate hints for the signature...

CVE-2026-22705 RustCrypto: Signatures has timing side-channel in ML-DSA decomposition

RustCrypto: Signatures offers support for digital signatures, which provide authentication of data using public-key cryptography. Prior to version 0.1.0-rc.2, a timing side-channel was discovered in the Decompose algorithm which is used during ML-DSA signing to generate hints for the signature...

CVE-2026-22705 RustCrypto: Signatures has timing side-channel in ML-DSA decomposition

RustCrypto: Signatures offers support for digital signatures, which provide authentication of data using public-key cryptography. Prior to version 0.1.0-rc.2, a timing side-channel was discovered in the Decompose algorithm which is used during ML-DSA signing to generate hints for the signature...

RustCrypto: Signatures 安全漏洞

RustCrypto: Signatures is a cryptographic signature algorithm open-sourced by Rust Crypto. A security vulnerability exists in RustCrypto: Signatures versions prior to 0.1.0-rc.2, which stems from the presence of timing side channels in the Decompose algorithm used during ML-DSA signing...

CVE-2026-22705: Use of a Cryptographic Primitive with a Risky Implementation

RustCrypto: Signatures offers support for digital signatures, which provide authentication of data using public-key cryptography. Prior to version 0.1.0-rc.2, a timing side-channel was discovered in the Decompose algorithm which is used during ML-DSA signing to generate hints for the signature...

RUSTSEC-2025-0144 Timing side-channel in ML-DSA decomposition

Summary A timing side-channel was discovered in the Decompose algorithm which is used during ML-DSA signing to generate hints for the signature. Details The analysis was performed using a constant-time analyzer that examines compiled assembly code for instructions with data-dependent timing...

Timing side-channel in ML-DSA decomposition

Summary A timing side-channel was discovered in the Decompose algorithm which is used during ML-DSA signing to generate hints for the signature. Details The analysis was performed using a constant-time analyzer that examines compiled assembly code for instructions with data-dependent timing...

The vulnerability of the bernoulli_p function in the decompose() function of the PyTorch machine learning framework allows attackers to compromise the confidentiality of the protected information.

The vulnerability of the bernoullip function in the PyTorch machine learning framework’s decompose method is related to inefficient calculations by the central processor. Exploiting this vulnerability could allow a malicious actor to compromise the confidentiality of the protected information...

BIT-PYTORCH-2025-46153

PyTorch before 3.7.0 has a bernoullip decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallbackrandom=True...

EUVD-2025-31108

Malicious code in bioql PyPI...

SUSE CVE-2025-46153

PyTorch before 3.7.0 has a bernoullip decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallbackrandom=True...

PYSEC-2025-202

PyTorch before 3.7.0 has a bernoullip decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallbackrandom=True...

CVE-2025-46153

PyTorch before 3.7.0 has a bernoullip decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallbackrandom=True...