CVE-2025-66448

highPriorität · verfolgen · 35EPSS 0.007 · 51. PerzentilEUUS
grimoire priorityP2 · Scheduled
Exploitable?
—
no known exploitation
Likely / severe?
0.66% (51st) EPSS
CVSS 8.8 · high
Is it mine?
3 products
Prüfe deine Angriffsfläche
Who says so?
4 sources
cnnvd · enisa_euvd · osv · nvd

EPSS · bewertet 2026-10-27

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.11.1, vllm has a critical remote code execution vector in a config class named Nemotron_Nano_VL_Config. When vllm loads a model config that contains an auto_map entry, the config class resolves that mapping with get_class_from_dynamic_module(...) and immediately instantiates the returned class. This fetches and executes Python from the remote repository referenced in the auto_map string. Crucially, this happens even when the caller explicitly sets trust_remote_code=False in vllm.transformers_utils.config.get_config. In practice, an attacker can publish a benign-looking frontend repo whose config.json points via auto_map to a separate malicious backend repo; loading the frontend will silently run the backend’s code on the victim host. This vulnerability is fixed in 0.11.1.

01

cvss

Technischer Schweregrad, 0–10. Eine Zeile je Quelle.

8.8
010

Basiswert 0–10 · höher = schwerwiegender · Vektor überfahren zum Auflösen

v3.18.8highCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:Hprimary · NVD / NIST USAusnutzbarkeit 2.8 · Auswirkung 5.9
v3.17.1highCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:Hsecondary · ENISA EU
v3.17.1highCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:Hsecondary · security-advisories@github.comAusnutzbarkeit 1.2 · Auswirkung 5.9
v3.17.1highCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:Hsecondary · OSV
v3.18.1highCVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H/E:Usecondary · CVSS-BT (t0sche)
02

SSVC

Eine Handlungsentscheidung — aus Ausnutzung und Auswirkung.

Exploitation: none · Automatable: yes · Technical Impact: totalcoordinatorcisa_ssvcUS
03

schwächen

Die CWE-Schwächeklassen, zu denen dies gehört.

04

betroffene Produkte (3)

Betroffene Produkte und Versionsbereiche.

05

Advisories (2)

Hersteller- und Ökosystem-Meldungen dazu.

  • GHSA-8fr4-5q9j-m8gmvLLM vulnerable to remote code execution via transformers_utils/get_config2025-12-02ghsa · osvUS

    ### Summary `vllm` has a critical remote code execution vector in a config class named `Nemotron_Nano_VL_Config`. When `vllm` loads a model config that contains an `auto_map` entry, the config class resolves that mapping with `get_class_from_dynamic_module(...)` and immediately instantiates the returned class. This fetches and executes Python from the remote repository referenced in the `auto_map` string. Crucially, this happens even when the caller explicitly sets `trust_remote_code=False` in `vllm.transformers_utils.config.get_config`. In practice, an attacker can publish a benign-looking frontend repo whose `config.json` points via `auto_map` to a separate malicious backend repo; loading the frontend will silently run the backend’s code on the victim host. ### Details The vulnerable code resolves and instantiates classes from `auto_map` entries without checking whether those entries point to a different repo or whether remote code execution is allowed. ```python class Nemotron_Nano_VL_Config(PretrainedConfig): model_type = 'Llama_Nemotron_Nano_VL' def __init__(self, **kwargs): super().__init__(**kwargs) if vision_config is not None: assert "auto_map" in vision_config and "AutoConfig" in vision_config["auto_map"] # <-- vulnerable dynamic resolution + instantiation happens here vision_auto_config = get_class_from_dynamic_module(*vision_config["auto_map"]["AutoConfig"].split("--")[::-1]) self.vision_config = vision_auto_config(**vision_config) else: self.vision_config = PretrainedConfig() ``` `get_class_from_dynamic_module(...)` is capable of fetching and importing code from the Hugging Face repo specified in the mapping. `trust_remote_code` is not enforced for this code path. As a result, a frontend repo can redirect the loader to any backend repo and cause code execution, bypassing the `trust_remote_code` guard. ### Impact This is a critical vulnerability because it breaks the documented `trust_remote_code` safety boundary in a core model-loading utility. The vulnerable code lives in a common loading path, so any application, service, CI job, or developer machine that uses `vllm`’s transformer utilities to load configs can be affected. The attack requires only two repos and no user interaction beyond loading the frontend model. A successful exploit can execute arbitrary commands on the host. ### Fixes * https://github.com/vllm-project/vllm/pull/28126

  • PYSEC-2026-2015vLLM vulnerable to remote code execution via transformers_utils/get_config2026-07-07vendor · osvUS

    ### Summary `vllm` has a critical remote code execution vector in a config class named `Nemotron_Nano_VL_Config`. When `vllm` loads a model config that contains an `auto_map` entry, the config class resolves that mapping with `get_class_from_dynamic_module(...)` and immediately instantiates the returned class. This fetches and executes Python from the remote repository referenced in the `auto_map` string. Crucially, this happens even when the caller explicitly sets `trust_remote_code=False` in `vllm.transformers_utils.config.get_config`. In practice, an attacker can publish a benign-looking frontend repo whose `config.json` points via `auto_map` to a separate malicious backend repo; loading the frontend will silently run the backend’s code on the victim host. ### Details The vulnerable code resolves and instantiates classes from `auto_map` entries without checking whether those entries point to a different repo or whether remote code execution is allowed. ```python class Nemotron_Nano_VL_Config(PretrainedConfig): model_type = 'Llama_Nemotron_Nano_VL' def __init__(self, **kwargs): super().__init__(**kwargs) if vision_config is not None: assert "auto_map" in vision_config and "AutoConfig" in vision_config["auto_map"] # <-- vulnerable dynamic resolution + instantiation happens here vision_auto_config = get_class_from_dynamic_module(*vision_config["auto_map"]["AutoConfig"].split("--")[::-1]) self.vision_config = vision_auto_config(**vision_config) else: self.vision_config = PretrainedConfig() ``` `get_class_from_dynamic_module(...)` is capable of fetching and importing code from the Hugging Face repo specified in the mapping. `trust_remote_code` is not enforced for this code path. As a result, a frontend repo can redirect the loader to any backend repo and cause code execution, bypassing the `trust_remote_code` guard. ### Impact This is a critical vulnerability because it breaks the documented `trust_remote_code` safety boundary in a core model-loading utility. The vulnerable code lives in a common loading path, so any application, service, CI job, or developer machine that uses `vllm`’s transformer utilities to load configs can be affected. The attack requires only two repos and no user interaction beyond loading the frontend model. A successful exploit can execute arbitrary commands on the host. ### Fixes * https://github.com/vllm-project/vllm/pull/28126

06

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07

quellen

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veröffentlicht 2025-12-01geändert 2026-10-18
08

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