Informational scan, not a security audit. How this is computed.
API keys, passwords or tokens committed into the repo.
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Packages you depend on that have known security holes (CVEs).
CVE-2025-2999 A vulnerability was found in PyTorch 2.6.0. It has been rated as criti ...CVE-2025-3730 A vulnerability, which was classified as problematic, was found in PyT ...CVE-2025-2953 torch: PyTorch torch.mkldnn_max_pool2d denial of serviceCVE-2025-3000 A vulnerability classified as critical has been found in PyTorch 2.6.0 ...CVE-2025-3001 A vulnerability classified as critical was found in PyTorch 2.6.0. Thi ...Your dependencies cross-checked against the OSV vulnerability database.
PYSEC-2026-2290 A vulnerability in the LightGlue model loading path of huggingface/transformers version 5.2.0 allows an attacker-controlled model repository to execute arbitrary code during model initialization. The PYSEC-2026-2102 AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. Prior to version 3.13.4, the C parser (the default for most installs) accepted null bytes and control characters in respPYSEC-2026-457 Arbitrary Code Execution in PillowPYSEC-2026-2178 Gradio before version 6.15.0 contains a cookie injection vulnerability that allows remote attackers to perform cross-Space session fixation by exploiting a shared module-level HTTP client used across PYSEC-2026-2179 Gradio before 6.16.0 contain a path traversal vulnerability in the FileExplorer component's preprocess() method that allows unauthenticated attackers to escape the configured root directory by supplyiPYSEC-2025-191 A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Affected by this issue is the function torch.mkldnn_max_pool2d. The manipulation leads to denial of servicePYSEC-2025-198 In PyTorch through 2.6.0, when eager is used, nn.PairwiseDistance(p=2) produces incorrect results.PYSEC-2025-199 In PyTorch before 2.7.0, when inductor is used, nn.Fold has an assertion error.PYSEC-2025-200 In PyTorch before 2.7.0, when torch.compile is used, FractionalMaxPool2d has inconsistent results.PYSEC-2025-201 In PyTorch before 2.7.0, bitwise_right_shift produces incorrect output for certain out-of-bounds values of the "other" argument.PYSEC-2025-202 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,PYSEC-2025-203 An issue in the component torch.linalg.lu of pytorch v2.8.0 allows attackers to cause a Denial of Service (DoS) when performing a slice operation.PYSEC-2025-204 pytorch v2.8.0 was discovered to display unexpected behavior when the components torch.rot90 and torch.randn_like are used together.PYSEC-2025-205 A syntax error in the component proxy_tensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service (DoS).PYSEC-2025-206 pytorch v2.8.0 was discovered to contain an integer overflow in the component torch.nan_to_num-.long().PYSEC-2025-207 A Name Error occurs in pytorch v2.7.0 when a PyTorch model consists of torch.cummin and is compiled by Inductor, leading to a Denial of Service (DoS).PYSEC-2025-208 A buffer overflow occurs in pytorch v2.7.0 when a PyTorch model consists of torch.nn.Conv2d, torch.nn.functional.hardshrink, and torch.Tensor.view-torch.mv() and is compiled by Inductor, leading to a PYSEC-2025-209 An issue in pytorch v2.7.0 can lead to a Denial of Service (DoS) when a PyTorch model consists of torch.Tensor.to_sparse() and torch.Tensor.to_dense() and is compiled by Inductor.PYSEC-2026-139 A vulnerability was identified in PyTorch 2.10.0. The affected element is an unknown function of the component pt2 Loading Handler. The manipulation leads to deserialization. The attack can only be pePYSEC-2026-1970 PyTorch Improper Resource Shutdown or Release vulnerabilityPYSEC-2026-2286 PyTorch is a Python package that provides tensor computation. Prior to version 2.10.0, a vulnerability in PyTorch's `weights_only` unpickler allows an attacker to craft a malicious checkpoint file (`.GHSA-c678-jfcj-6jmf PyTorch Tuple Handler is Vulnerable to Memory Corruption through Manipulation of None ArgumentGHSA-f4hp-rmr7-r7v8 PyTorch is Vulnerable to Memory Consumption through pad_packed_sequence FunctionGHSA-qfhq-4f3w-5fph PyTorch is vulnerable to memory corruption through its torch.lstm_cell functionGHSA-rrmf-rvhw-rf47 PyTorch is vulnerable to memory corruption through its torch.jit.script functionCode that can be exploited: injection, hardcoded credentials and similar.
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Packages that look intentionally malicious: typosquats, sneaky install scripts.
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A signal about how the project is maintained — not a vulnerability in your code. It doesn’t affect the verdict above.
Maintenance & supply-chain hygiene. A signal about the project, not a vulnerability in your code.
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