PatchFirst · Vulnérabilités récentes
Vulnérabilités publiées pour Python au cours des 30 derniers jours : 360. Présentes dans le catalogue KEV : 1.
Vulnérabilités : 7131
picklescan before 0.0.28 fails to detect malicious torch.fx.experimental.symbolic_shapes.ShapeEnv.evaluate_guards_expression function calls in pickle files. Attackers can embed undetected code in pickle files that executes remote code when loaded by victims.
picklescan before 0.0.28 fails to detect malicious pickle files that exploit torch._dynamo.guards.GuardBuilder.get function in reduce methods. Attackers can craft pickle files with embedded code that evades picklescan detection and executes arbitrary commands when loaded.
picklescan before 0.0.33 fails to detect malicious pickle files using numpy.f2py.crackfortran.param_eval function in reduce methods, allowing attackers to bypass security checks. Remote attackers can embed undetected code in pickle files that executes during deserialization, enabling arbitrary code execution in applications loading untrusted pickle data.
picklescan before 0.0.30 fails to detect malicious pickle files that invoke torch.utils.bottleneck.__main__.run_autograd_prof function. Attackers can embed undetected code in pickle files that executes during deserialization, enabling remote code execution.
picklescan before 0.0.30 fails to detect malicious pickle files that exploit lib2to3.pgen2.pgen.ParserGenerator.make_label function in the reduce method. Attackers can craft malicious pickle files with embedded code that evades detection but executes arbitrary commands when pickle.load() is called.
picklescan before 0.0.30 fails to detect malicious pickle files using idlelib.run.Executive.runcode in reduce methods. Attackers can embed undetected code in pickle files that executes during pickle.load, enabling remote code execution in PyTorch models and supply chain attacks.
In nltk/nltk versions 3.9.3 and earlier, five Stanford interface classes (StanfordPOSTagger, StanfordNERTagger, StanfordParser, StanfordDependencyParser, and StanfordNeuralDependencyParser) are vulnerable to untrusted JAR code execution. These classes accept user-controllable JAR paths and execute them via the `java()` function, which invokes `subprocess.Popen()` without integrity verification. This vulnerability is identical to CVE-2026-0848, which was fixed for StanfordSegmenter by adding SHA256 verification. However, the fix was not applied to these additional classes, leaving them susceptible to arbitrary code execution when loading untru
A vulnerability in keras-team/keras version 3.14.0 allows for arbitrary code execution due to improper handling of deserialization in the `Lambda` layer. Specifically, the `_raise_for_lambda_deserialization()` function fails to enforce the safe-mode guard when `safe_mode` is set to `None`, which is the default value when `from_config()` is called outside of a `SafeModeScope` context. This logic error conflates `None` (unset/default-deny) with `False` (explicitly disabled), bypassing the guard and allowing attacker-controlled `marshal` bytecode to be deserialized. Affected call sites include `keras.layers.deserialize(config)`, `keras.models.cl
fast-mcp-telegram is a Telegram MCP Server. Prior to 0.19.1, fast-mcp-telegram validates HTTP Bearer tokens by joining the raw token string into a session-file path. The verifier rejects the exact reserved token telegram, but it does not reject path separators or normalize the path before checking whether the session file exists. A remote HTTP client can therefore authenticate as the default legacy session with a token such as ../fast-mcp-telegram/telegram when the documented default session file ~/.config/fast-mcp-telegram/telegram.session exists. This bypasses the reserved session name control that is intended to prevent HTTP multi-user ses
PraisonAI before 0.1.7 fails to validate that project_id in issue create and update request bodies belongs to the URL workspace. An attacker can create issues referencing projects from other workspaces, causing cross-tenant data pollution in project statistics aggregation without workspace constraints.
In MLflow versions prior to 3.14.0, when running with authentication enabled, the trace API endpoints lack proper authorization validators. This allows any authenticated user to bypass experiment-level authorization controls on all trace operations, including reading, deleting, and modifying traces on experiments they do not have permission to access. The issue arises from the `_before_request` handler, which does not register authorization validators for trace endpoints, resulting in requests proceeding without validation. This vulnerability can expose sensitive data, destroy audit logs, and allow unauthorized modifications.
Part of the "Hades" wave of the Shai-Hulud supply-chain campaign. On 2026-06-08, malicious phantom releases of uprobe were published to PyPI using stolen credentials. The package executes a bundled JavaScript payload (via the Bun runtime) on import that harvests and exfiltrates credentials and attempts self-propagation. This entry is a summary; behavior may not be fully characterized here. See the linked references for detailed analysis and indicators of compromise.
Part of the "Hades" wave of the Shai-Hulud supply-chain campaign. On 2026-06-08, malicious phantom releases of ufish were published to PyPI using stolen credentials. The package executes a bundled JavaScript payload (via the Bun runtime) on import that harvests and exfiltrates credentials and attempts self-propagation. This entry is a summary; behavior may not be fully characterized here. See the linked references for detailed analysis and indicators of compromise.
Part of the "Hades" wave of the Shai-Hulud supply-chain campaign. On 2026-06-08, malicious phantom releases of synago were published to PyPI using stolen credentials. The package executes a bundled JavaScript payload (via the Bun runtime) on import that harvests and exfiltrates credentials and attempts self-propagation. This entry is a summary; behavior may not be fully characterized here. See the linked references for detailed analysis and indicators of compromise.
Part of the "Hades" wave of the Shai-Hulud supply-chain campaign. On 2026-06-08, malicious phantom releases of pantheon-toolsets were published to PyPI using stolen credentials. The package executes a bundled JavaScript payload (via the Bun runtime) on import that harvests and exfiltrates credentials and attempts self-propagation. This entry is a summary; behavior may not be fully characterized here. See the linked references for detailed analysis and indicators of compromise.
Part of the "Hades" wave of the Shai-Hulud supply-chain campaign. On 2026-06-08, malicious phantom releases of pantheon-agents were published to PyPI using stolen credentials. The package executes a bundled JavaScript payload (via the Bun runtime) on import that harvests and exfiltrates credentials and attempts self-propagation. This entry is a summary; behavior may not be fully characterized here. See the linked references for detailed analysis and indicators of compromise.
Wagtail is an open source content management system built on Django. In versions prior to 7.0.8, 7.3.3 and 7.4.2, reflected cross-site scripting (XSS) vulnerability exists on the dynamic image URL generator view within the Wagtail admin interface. A user with a limited-permission editor account for the Wagtail admin could craft a URL that, when viewed by a user with higher privileges, could perform actions with that user's credentials. The vulnerability is present for all sites, even if they do not enable the dynamic image serve view. The vulnerability is not exploitable by an ordinary site visitor without access to the Wagtail admin. This is
Wagtail is an open source content management system built on Django. In versions prior to 7.0.8, 7.3.3 and 7.4.2, a low-level user with the "Can submit translation" permission can create translations for any page, including those they do not have permissions for. This issue has been fixed in versions 7.0.8, 7.3.3, and 7.4.2.
Wagtail is an open source content management system built on Django. In versions prior to 7.0.8, 7.3.3 and 7.4.2, due to a missing permission check on the image preview endpoint, a user with access to the Wagtail admin can preview any image. The existing data of the image object itself is not exposed. The vulnerability is not exploitable by an ordinary site visitor without access to the Wagtail admin. This issue has been fixed in versions 7.0.8, 7.3.3, and 7.4.2.
Wagtail is an open source content management system built on Django. In versions prior to 7.0.8, 7.3.3 and 7.4.2, the Documents and Images chooser's chosen endpoint incorrectly listed items for which the user has not been granted choose permission. A user with access to the Wagtail admin could see the filename and name and URLs of documents and images in those collections. The vulnerability is not exploitable by an ordinary site visitor without access to the Wagtail admin. This issue has been fixed in versions 7.0.8, 7.3.3, and 7.4.2.
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