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-2026-44513

A flaw was found in Diffusers, a library for pretrained diffusion models. A remote attacker could exploit a bypass in the trustremotecode mechanism within the DiffusionPipeline.frompretrained function. This vulnerability allows for arbitrary remote code execution, even when the user explicitly se...

CVE-2026-4944

vllm-project/vllm version 0.14.1 contains a vulnerability where the trustremotecode=True parameter is hardcoded in two model implementation files vllm/modelexecutor/models/nemotronvl.py and vllm/modelexecutor/models/kimik25.py. This bypasses the user's explicit --trust-remote-code=False setting,...

CVE-2026-45829

A pre-authentication, code injection vulnerability in version 1.0.0 or later of the ChromaDB Python project allows an unauthenticated attacker to run arbitrary code on the server by sending a malicious model repository and trustremotecode set to true in...

CVE-2026-44513 Diffusers: `trust_remote_code` bypass via `custom_pipeline` and local custom components

Diffusers is the a library for pretrained diffusion models. Prior to 0.38.0, a trustremotecode bypass in DiffusionPipeline.frompretrained allows arbitrary remote code execution despite the user passing trustremotecode=False or omitting it, which is the default. The vulnerability has three variant...

sglang 注入漏洞

SGLang is a programming language and runtime system developed by SGL-project, aimed at accelerating large model inference. Versions of SGLang 0.5.9 and earlier contained a injection vulnerability. This vulnerability stemmed from the operation of the gettokenizer function in the...

vLLM 安全漏洞

vLLM is an open-source LLM-based inference and service engine that features high throughput and efficient memory usage. Versions of vLLM prior to 0.10.1 to 0.18.0 contained a security vulnerability. This vulnerability stemmed from the hardcoding of trustremotecode=True in two model implementation...

Hardcoded trust_remote_code=True in Model Implementations Bypasses User Security Control

This report is not public...