CVE-2026-22778

vLLM is an inference and serving engine for large language models LLMs. From 0.8.3 to before 0.14.1, when an invalid image is sent to vLLM's multimodal endpoint, PIL throws an error. vLLM returns this error to the client, leaking a heap address. With this leak, we reduce ASLR from 4 billion guess...

CVE-2026-22778

vLLM is an inference and serving engine for large language models LLMs. From 0.8.3 to before 0.14.1, when an invalid image is sent to vLLM's multimodal endpoint, PIL throws an error. vLLM returns this error to the client, leaking a heap address. With this leak, we reduce ASLR from 4 billion guess...

CVE-2026-22778 vLLM leaks a heap address when PIL throws an error

vLLM is an inference and serving engine for large language models LLMs. From 0.8.3 to before 0.14.1, when an invalid image is sent to vLLM's multimodal endpoint, PIL throws an error. vLLM returns this error to the client, leaking a heap address. With this leak, we reduce ASLR from 4 billion guess...

CVE-2026-22778 vLLM leaks a heap address when PIL throws an error

vLLM is an inference and serving engine for large language models LLMs. From 0.8.3 to before 0.14.1, when an invalid image is sent to vLLM's multimodal endpoint, PIL throws an error. vLLM returns this error to the client, leaking a heap address. With this leak, we reduce ASLR from 4 billion guess...

Exploit for Code Injection in Vllm

No d...

GHSA-QH4C-XF7M-GXFC vLLM vulnerable to Server-Side Request Forgery (SSRF) through MediaConnector

Summary A Server-Side Request Forgery SSRF vulnerability exists in the MediaConnector class within the vLLM project's multimodal feature set. The loadfromurl and loadfromurlasync methods obtain and process media from URLs provided by users, using different Python parsing libraries when restrictin...

CVE-2026-24779

A flaw was found in vLLM, an inference and serving engine for large language models LLMs. A Server-Side Request Forgery SSRF vulnerability exists in the MediaConnector class, specifically within the loadfromurl and loadfromurlasync methods. An attacker can exploit differing interpretations of...

Server-side Request Forgery (SSRF)

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Server-side Request Forgery SSRF via the MediaConnector class. An attacker can access internal network resources and cause system instability or...

CVE-2026-24779

vLLM is an inference and serving engine for large language models LLMs. Prior to version 0.14.1, a Server-Side Request Forgery SSRF vulnerability exists in the MediaConnector class within the vLLM project's multimodal feature set. The loadfromurl and loadfromurlasync methods obtain and process...

CVE-2026-24779 vLLM vulnerable to Server-Side Request Forgery (SSRF) in `MediaConnector`

vLLM is an inference and serving engine for large language models LLMs. Prior to version 0.14.1, a Server-Side Request Forgery SSRF vulnerability exists in the MediaConnector class within the vLLM project's multimodal feature set. The loadfromurl and loadfromurlasync methods obtain and process...

CVE-2026-24779

CVE-2026-24779 is an SSRF vulnerability in vLLM’s MediaConnector. Before version 0.14.1, load_from_url and load_from_url_async fetch media from user-supplied URLs and validate via Python urllib urlparse, while the request is issued with requests/urllib3, whose parsing follows a different standard...

PT-2026-5029

Name of the Vulnerable Software and Affected Versions vLLM versions prior to 0.14.1 Description A Server-Side Request Forgery SSRF exists in the MediaConnector class within the multimodal feature set. The load from url and load from url async functions process media from user-provided URLs using...

GHSA-2PC9-4J83-QJMR vulnerabilities

Vulnerabilities for packages: tritonserver-backend-vllm-cuda-13.0, tritonserver-backend-vllm-cuda-12.9, py3-vllm-cuda-12.4...

CVE-2026-22807 vulnerabilities

Vulnerabilities for packages: tritonserver-backend-vllm-cuda-13.0, tritonserver-backend-vllm-cuda-12.9, py3-vllm-cuda-12.4...

CVE-2026-22807

vLLM is an inference and serving engine for large language models LLMs. Starting in version 0.10.1 and prior to version 0.14.0, vLLM loads Hugging Face automap dynamic modules during model resolution without gating on trustremotecode, allowing attacker-controlled Python code in a model repo/path ...

CVE-2026-22807 vLLM affected by RCE via auto_map dynamic module loading during model initialization

vLLM is an inference and serving engine for large language models LLMs. Starting in version 0.10.1 and prior to version 0.14.0, vLLM loads Hugging Face automap dynamic modules during model resolution without gating on trustremotecode, allowing attacker-controlled Python code in a model repo/path ...

GHSA-2PC9-4J83-QJMR vLLM affected by RCE via auto_map dynamic module loading during model initialization

Summary vLLM loads Hugging Face automap dynamic modules during model resolution without gating on trustremotecode, allowing attacker-controlled Python code in a model repo/path to execute at server startup. --- Impact An attacker who can influence the model repo/path local directory or remote...

Arbitrary Code Injection

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Arbitrary Code Injection via the automap process during model initialization, even when trustremotecode is false. An attacker can execute arbitrary...

vLLM affected by RCE via auto_map dynamic module loading during model initialization

Summary vLLM loads Hugging Face automap dynamic modules during model resolution without gating on trustremotecode, allowing attacker-controlled Python code in a model repo/path to execute at server startup. --- Impact An attacker who can influence the model repo/path local directory or remote...

PT-2026-3865

Name of the Vulnerable Software and Affected Versions vLLM versions 0.10.1 through 0.13.x Description vLLM is an inference and serving engine for large language models LLMs. The software loads Hugging Face auto map dynamic modules during model resolution without verifying trust remote code. This...