25 matches found
MAL-2026-3683 Malicious code in @dropout-ai/runtime (npm)
--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 2121b923a39177ed68ce5cf066cbb07891b7cb5d20ecf5ec66f2c953634eff10 On require/import, src/index.js replaces global.fetch with a wrapper that intercepts every fetch whose URL matches openai.com, anthropic.com,...
Malicious code in @dropout-ai/runtime (npm)
--- -= Per source details. Do not edit below this line.=- Source: amazon-inspector 2121b923a39177ed68ce5cf066cbb07891b7cb5d20ecf5ec66f2c953634eff10 On require/import, src/index.js replaces global.fetch with a wrapper that intercepts every fetch whose URL matches openai.com, anthropic.com,...
Scalable and Verifiable Federated Learning for Cross-Institution Financial Fraud Detection
The global financial ecosystem confronts a critical asymmetry: while fraud syndicates operate as borderless, distributed networks, banking institutions remain constrained by regulatory data silos, limiting visibility into cross-institutional threat patterns under strict privacy laws such as GDPR...
Clutch Control: An Attention-Based Combinatorial Bandit for Efficient Mutation in JavaScript Engine Fuzzing
JavaScript engines are widely used in web browsers, PDF readers, and server-side applications. The rise in concern over their security has led to the development of several targeted fuzzing techniques. However, existing approaches use random selection to determine where to perform mutations in...
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...
PyTorch before 3.7.0 has a bernoulli_p 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 fallback_random=True.
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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...
Linux Distros Unpatched Vulnerability : CVE-2025-46153
The Linux/Unix host has one or more packages installed that are impacted by a vulnerability without a vendor supplied patch available. - PyTorch before 3.7.0 has a bernoullip decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negativel...
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...
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...
DEBIAN-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...
UBUNTU-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...
Inefficient CPU Computation
Overview Affected versions of this package are vulnerable to Inefficient CPU Computation due to inconsistent behavior in the bernoullip function when used in RNG nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d. An attacker can cause unintended or incorrect dropout behavior in neural network layers b...
Inefficient CPU Computation
Overview torch is a Tensors and Dynamic neural networks in Python with strong GPU acceleration Affected versions of this package are vulnerable to Inefficient CPU Computation due to inconsistent behavior in the bernoullip function when used in RNG nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d. An...
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...
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...
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...
PT-2025-39383
Name of the Vulnerable Software and Affected Versions PyTorch versions prior to 3.7.0 Description The software contains an inconsistency in the bernoulli p decompose function within decompositions.py. This function does not fully align with the eager CPU implementation, which impacts the...