https://db.gcve.eu Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Mon, 28 Sep 2026 18:20:57 +0000 https://db.gcve.eu/vuln/cve-2026-5241 <p><strong>Affected:</strong> huggingface/transformers, Red Hat OpenShift AI 2.25, Red Hat OpenShift AI 3.3, Red Hat OpenShift AI 3.4, Red Hat OpenShift Lightspeed, Red Hat AI Inference Server, Red Hat Ansible Automation Platform 2, Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat OpenShift AI (RHOAI)</p> <p>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, is overridden by untrusted serialized configuration data in a nested code path. Specifically, when loading a LightGlue model using `AutoModel.from_pretrained()` with `trust_remote_code=False`, the `LightGlueConfig` reads the `trust_remote_code` value from the untrusted `config.json` file and propagates it into nested `AutoConfig.from_pretrained()` calls. This results in the execution of attacker-provided Python modules, even when the victim explicitly disables remote code execution. The vulnerability poses a high risk for environments such as API inference servers, research notebooks, CI/CD pipelines, and model evaluation workers, potentially leading to credential theft, lateral movement, or persistence/backdoor deployment.</p> <p><strong>Affected:</strong> huggingface/transformers, Red Hat OpenShift AI 2.25, Red Hat OpenShift AI 3.3, Red Hat OpenShift AI 3.4, Red Hat OpenShift Lightspeed, Red Hat AI Inference Server, Red Hat Ansible Automation Platform 2, Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat OpenShift AI (RHOAI)</p> <p>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, is overridden by untrusted serialized configuration data in a nested code path. Specifically, when loading a LightGlue model using `AutoModel.from_pretrained()` with `trust_remote_code=False`, the `LightGlueConfig` reads the `trust_remote_code` value from the untrusted `config.json` file and propagates it into nested `AutoConfig.from_pretrained()` calls. This results in the execution of attacker-provided Python modules, even when the victim explicitly disables remote code execution. The vulnerability poses a high risk for environments such as API inference servers, research notebooks, CI/CD pipelines, and model evaluation workers, potentially leading to credential theft, lateral movement, or persistence/backdoor deployment.</p> https://db.gcve.eu/vuln/cve-2026-5241