https://cve.radiocsirt.org Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Fri, 02 Oct 2026 13:39:57 +0000 https://cve.radiocsirt.org/vuln/bdu:2025-15447 bdu:2025-15447 https://cve.radiocsirt.org/vuln/bdu:2025-15447 https://cve.radiocsirt.org/vuln/euvd-2026-264499 EUVD-2026-264499 https://cve.radiocsirt.org/vuln/euvd-2026-264499 https://cve.radiocsirt.org/vuln/fkie_cve-2025-1889 <p>picklescan before 0.0.22 only considers standard pickle file extensions in the scope for its vulnerability scan. An attacker could craft a malicious model that uses Pickle and include a malicious pickle file with a non-standard file extension. Because the malicious pickle file inclusion is not considered as part of the scope of picklescan, the file would pass security checks and appear to be safe, when it could instead prove to be problematic.</p> <p>picklescan before 0.0.22 only considers standard pickle file extensions in the scope for its vulnerability scan. An attacker could craft a malicious model that uses Pickle and include a malicious pickle file with a non-standard file extension. Because the malicious pickle file inclusion is not considered as part of the scope of picklescan, the file would pass security checks and appear to be safe, when it could instead prove to be problematic.</p> https://cve.radiocsirt.org/vuln/fkie_cve-2025-1889 https://cve.radiocsirt.org/vuln/ghsa-769v-p64c-89pr <p><strong>Affected:</strong> PyPI: picklescan</p> <p>### CVE-2025-1889</p> <p>### Summary</p> <p>Picklescan fails to detect hidden pickle files embedded in PyTorch model archives due to its reliance on file extensions for detection. This allows an attacker to embed a secondary, malicious pickle file with a non-standard extension inside a model archive, which remains undetected by picklescan but is still loaded by PyTorch&#39;s torch.load() function. This can lead to arbitrary code execution when the model is loaded.</p> <p>### Details</p> <p>Picklescan primarily identifies pickle files by their extensions (e.g., .pkl, .pt). However, PyTorch allows specifying an alternative pickle file inside a model archive using the pickle_file parameter when calling torch.load(). This makes it possible to embed a malicious pickle file (e.g., config.p) inside the model while keeping the primary data.pkl file benign.</p> <p>A typical attack works as follows:</p> <p>- A PyTorch model (model.pt) is created and saved normally. - A second pickle file (config.p) containing a malicious payload is crafted. - The data.pkl file in the model is modified to contain an object that calls torch.load(model.pt, pickle_file=&#39;config.p&#39;), causing config.p to be loaded when the model is opened. - Since picklescan ignores non-standard extensions, it does not scan config.p, allowing the malicious payload to evade detection. - The issue is exacerbated by the fact that PyTorch models are widely shared in ML repositories and organizations, making it a potential supply-chain attack vector.</p> <p>### PoC ``` impor…</p> <p><strong>Affected:</strong> PyPI: picklescan</p> <p>### CVE-2025-1889</p> <p>### Summary</p> <p>Picklescan fails to detect hidden pickle files embedded in PyTorch model archives due to its reliance on file extensions for detection. This allows an attacker to embed a secondary, malicious pickle file with a non-standard extension inside a model archive, which remains undetected by picklescan but is still loaded by PyTorch&#39;s torch.load() function. This can lead to arbitrary code execution when the model is loaded.</p> <p>### Details</p> <p>Picklescan primarily identifies pickle files by their extensions (e.g., .pkl, .pt). However, PyTorch allows specifying an alternative pickle file inside a model archive using the pickle_file parameter when calling torch.load(). This makes it possible to embed a malicious pickle file (e.g., config.p) inside the model while keeping the primary data.pkl file benign.</p> <p>A typical attack works as follows:</p> <p>- A PyTorch model (model.pt) is created and saved normally. - A second pickle file (config.p) containing a malicious payload is crafted. - The data.pkl file in the model is modified to contain an object that calls torch.load(model.pt, pickle_file=&#39;config.p&#39;), causing config.p to be loaded when the model is opened. - Since picklescan ignores non-standard extensions, it does not scan config.p, allowing the malicious payload to evade detection. - The issue is exacerbated by the fact that PyTorch models are widely shared in ML repositories and organizations, making it a potential supply-chain attack vector.</p> <p>### PoC ``` impor…</p> https://cve.radiocsirt.org/vuln/ghsa-769v-p64c-89pr https://cve.radiocsirt.org/vuln/pysec-2025-19 <p><strong>Affected:</strong> PyPI: picklescan</p> <p>picklescan before 0.0.22 only considers standard pickle file extensions in the scope for its vulnerability scan. An attacker could craft a malicious model that uses Pickle and include a malicious pickle file with a non-standard file extension. Because the malicious pickle file inclusion is not considered as part of the scope of picklescan, the file would pass security checks and appear to be safe, when it could instead prove to be problematic.</p> <p><strong>Affected:</strong> PyPI: picklescan</p> <p>picklescan before 0.0.22 only considers standard pickle file extensions in the scope for its vulnerability scan. An attacker could craft a malicious model that uses Pickle and include a malicious pickle file with a non-standard file extension. Because the malicious pickle file inclusion is not considered as part of the scope of picklescan, the file would pass security checks and appear to be safe, when it could instead prove to be problematic.</p> https://cve.radiocsirt.org/vuln/pysec-2025-19