CVE-2026-12479

A path traversal vulnerability exists in keras-team/keras 3.14.0, in DiskIOStore.make, due to unsanitized user-provided layer names used to build directory paths (parent components not sanitized). Although forward slashes are restricted, directory traversal sequences can escape the intended tempo...

CVE-2026-46432

LMDeploy is a toolkit for compressing, deploying, and serving large language models. In versions 0.12.3 and prior, LMDeploy is vulnerable to arbitrary code execution through hardcoded "trustremotecode=True" in multiple HuggingFace model-loading call sites. At time of publication, there are no...

CVE-2026-46432

LMDeploy is a toolkit for compressing, deploying, and serving large language models. In versions 0.12.3 and prior, LMDeploy is vulnerable to arbitrary code execution through hardcoded "trustremotecode=True" in multiple HuggingFace model-loading call sites. At time of publication, there are no...

lmdeploy 代码注入漏洞

lmdeploy is a toolkit developed by InternLM for compressing, deploying, and serving LLMs. Versions of lmdeploy prior to 0.12.3 have a code injection vulnerability. This vulnerability stems from the hardcoding of trustremotecode=True at multiple HuggingFace model loading points, which may allow...

CVE-2026-46432 LMDeploy: Arbitrary code execution via hardcoded trust_remote_code=True in lmdeploy model initialization

LMDeploy is a toolkit for compressing, deploying, and serving large language models. In versions 0.12.3 and prior, LMDeploy is vulnerable to arbitrary code execution through hardcoded "trustremotecode=True" in multiple HuggingFace model-loading call sites. At time of publication, there are no...

CVE-2026-46432 LMDeploy: Arbitrary code execution via hardcoded trust_remote_code=True in lmdeploy model initialization

LMDeploy is a toolkit for compressing, deploying, and serving large language models. In versions 0.12.3 and prior, LMDeploy is vulnerable to arbitrary code execution through hardcoded "trustremotecode=True" in multiple HuggingFace model-loading call sites. At time of publication, there are no...

EUVD-2026-35873

LMDeploy is a toolkit for compressing, deploying, and serving large language models. In versions 0.12.3 and prior, LMDeploy is vulnerable to arbitrary code execution through hardcoded "trustremotecode=True" in multiple HuggingFace model-loading call sites. At time of publication, there are no...

CVE-2026-38950

An issue in ESA AnomalyMatch before 1.3.1 allow attackers to execute arbitrary code via crafted model checkpoint files. The affected components load model files from session directories using torch.load with unrestricted deserialization...

CVE-2026-31229

The Adversarial Robustness Toolbox ART thru 1.20.1 contains an insecure deserialization vulnerability CWE-502 in its Kubeflow component's model loading functionality. When loading model weights from a file e.g., model.pt during robustness evaluation, the code uses torch.load without the...

CVE-2026-6840

Missing bounds validation for operator could allow out of range operator-code lookup during model loading Affected version is prior to commit 1.30.0...

CVE-2026-5241

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 issue arises because the trustremotecode parameter, intended to prevent remote code execution, is...

CVE-2026-5241

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 issue arises because the trustremotecode parameter, intended to prevent remote code execution, is...

CVE-2026-5241

Technical details (affected products, versions, fixes, or exploit specifics) are not publicly available in the provided connected documents. Monitor for updates from vendors and security advisories.

PT-2026-45946

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 issue arises because the trust remote code parameter, intended to prevent remote code execution, ...

EUVD-2026-33942

OpenMed before 1.5.2 contains a remote code execution vulnerability in the PII privacy-filter model loading path. The privacy-filter dispatcher used broad substring matching on the user-supplied modelname parameter, allowing a value such as attacker/foo-privacy-filter-bar to route through a path...

CVE-2026-47117

OpenMed before 1.5.2 contains a remote code execution vulnerability in the PII privacy-filter model loading path. The privacy-filter dispatcher used broad substring matching on the user-supplied modelname parameter, allowing a value such as attacker/foo-privacy-filter-bar to route through a path...

CVE-2026-47117 OpenMed < 1.5.2 Remote Code Execution via PII Model Loading

OpenMed before 1.5.2 contains a remote code execution vulnerability in the PII privacy-filter model loading path. The privacy-filter dispatcher used broad substring matching on the user-supplied modelname parameter, allowing a value such as attacker/foo-privacy-filter-bar to route through a path...

CVE-2026-47117

OpenMed prior to version 1.5.2 is affected by a remote code execution vulnerability in the PII privacy-filter model loading path. The privacy-filter dispatcher uses broad substring matching on the user-supplied model_name, enabling a value like attacker/foo-privacy-filter-bar to route to a path t...

PT-2026-45783

Name of the Vulnerable Software and Affected Versions OpenMed versions prior to 1.5.2 Description Remote code execution is possible in the PII privacy-filter model loading path. The privacy-filter dispatcher uses broad substring matching on the user-supplied model name parameter, which allows a...

AnomalyMatch 安全漏洞

AnomalyMatch is a semi-supervised image anomaly detection tool open source by the European Space Agency. Versions of AnomalyMatch prior to 1.3.1 contained security vulnerabilities. These vulnerabilities stemmed from the use of torch.load to load model files without proper deserialization...