CVE-2026-27893
highpriority · track · 0EPSS 0.014 · 72 %ileDEEUUSEPSS · scored 2026-10-27
vLLM is an inference and serving engine for large language models (LLMs). Starting in version 0.10.1 and prior to version 0.18.0, two model implementation files hardcode `trust_remote_code=True` when loading sub-components, bypassing the user's explicit `--trust-remote-code=False` security opt-out. This enables remote code execution via malicious model repositories even when the user has explicitly disabled remote code trust. Version 0.18.0 patches the issue.
cvss
Technical severity, 0–10. One row per scoring source.
base score 0–10 · higher = more severe · hover a vector to decode
ssvc
A stakeholder decision — act, attend, or track — from exploitation and impact.
weaknesses
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affected products (6)
Products and version ranges known to be affected.
advisories (3)
Vendor and ecosystem advisories describing this.
- WID-SEC-W-2026-0890vllm: Schwachstelle ermöglicht CodeausführungDeutsch2026-03-26csaf · cert_bundDE
Ein entfernter, anonymer Angreifer kann eine Schwachstelle in vllm ausnutzen, um beliebigen Programmcode auszuführen.
- GHSA-7972-pg2x-xr59vLLM has Hardcoded Trust Override in Model Files Enables RCE Despite Explicit User Opt-Out2026-03-27ghsa · osvUS
### Summary Two model implementation files hardcode `trust_remote_code=True` when loading sub-components, bypassing the user's explicit `--trust-remote-code=False` security opt-out. This enables remote code execution via malicious model repositories even when the user has explicitly disabled remote code trust. ### Details **Affected files (latest main branch):** 1. `vllm/model_executor/models/nemotron_vl.py:430` ```python vision_model = AutoModel.from_config(config.vision_config, trust_remote_code=True) ``` 2. vllm/model_executor/models/kimi_k25.py:177 ```python cached_get_image_processor(self.ctx.model_config.model, trust_remote_code=True) ``` Both pass a hardcoded trust_remote_code=True to HuggingFace API calls, overriding the user's global --trust-remote-code=False setting. Relation to prior CVEs: - CVE-2025-66448 fixed auto_map resolution in vllm/transformers_utils/config.py (config loading path) - CVE-2026-22807 fixed broader auto_map at startup - Both fixes are present in the current code. These hardcoded instances in model files survived both patches — different code paths. ### Impact Remote code execution. An attacker can craft a malicious model repository that executes arbitrary Python code when loaded by vLLM, even when the user has explicitly set --trust-remote-code=False. This undermines the security guarantee that trust_remote_code=False is intended to provide. Remediation: Replace hardcoded trust_remote_code=True with self.config.model_config.trust_remote_code in both files. Raise a clear error if the model component requires remote code but the user hasn't opted in.
- PYSEC-2026-22972026-03-27vendor · osvUS
vLLM is an inference and serving engine for large language models (LLMs). Starting in version 0.10.1 and prior to version 0.18.0, two model implementation files hardcode `trust_remote_code=True` when loading sub-components, bypassing the user's explicit `--trust-remote-code=False` security opt-out. This enables remote code execution via malicious model repositories even when the user has explicitly disabled remote code trust. Version 0.18.0 patches the issue.
also known as (6)
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sources
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references (24)
External citations — patches, advisories, analysis.
- https://github.com/vllm-project/vllm/commit/00bd08edeee5dd4d4c13277c0114a464011acf72cnnvd
- https://github.com/vllm-project/vllm/pull/36192cnnvd
- https://github.com/vllm-project/vllm/releasesPatchcnnvd
- https://github.com/vllm-project/vllm/security/advisories/GHSA-7972-pg2x-xr59cnnvd
- https://github.com/vllm-project/vllm/commit/00bd08edeee5dd4d4c13277c0114a464011acf72enisa_euvd
- https://github.com/vllm-project/vllm/pull/36192enisa_euvd
- https://github.com/vllm-project/vllm/security/advisories/GHSA-7972-pg2x-xr59enisa_euvd
- https://access.redhat.com/errata/RHSA-2026:10140nvd
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