CVE-2026-9540 vllm-project vllm OpenAI-compatible Serving Path denial of service

A vulnerability was identified in vllm-project vllm 0.19.0. This issue affects some unknown processing of the component OpenAI-compatible Serving Path. Such manipulation leads to denial of service. It is possible to launch the attack remotely. The exploit is publicly available and might be used...

CVE-2026-9540

A vulnerability was identified in vllm-project vllm 0.19.0. This issue affects some unknown processing of the component OpenAI-compatible Serving Path. Such manipulation leads to denial of service. It is possible to launch the attack remotely. The exploit is publicly available and might be used...

PT-2026-43245

A vulnerability was identified in vllm-project vllm 0.19.0. This issue affects some unknown processing of the component OpenAI-compatible Serving Path. Such manipulation leads to denial of service. It is possible to launch the attack remotely. The exploit is publicly available and might be used...

CVE-2026-44222

creationtimestamp| type| source ---|---|--- 2026-04-27 18:00:06+00:00| published-proof-of-concept| https://github.com/vllm-project/vllm/security/advisories/GHSA-hpv8-x276-m59f...

Improper Input Validation

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Improper Input Validation due to inconsistent downmixing behavior in the tomono process. An attacker can manipulate audio inputs to cause the AI mod...

Unsafe Dependency Resolution

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Unsafe Dependency Resolution in the process of loading sub-components with the trustremotecode parameter set to True, regardless of user...

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...

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...

GHSA-69J4-GRXJ-J64P vLLM vulnerable to DoS via large Chat Completion or Tokenization requests with specially crafted `chat_template_kwargs`

Summary The /v1/chat/completions and /tokenize endpoints allow a chattemplatekwargs request parameter that is used in the code before it is properly validated against the chat template. With the right chattemplatekwargs parameters, it is possible to block processing of the API server for long...

GHSA-MRW7-HF4F-83PF vLLM deserialization vulnerability leading to DoS and potential RCE

Summary A memory corruption vulnerability that leading to a crash denial-of-service and potentially remote code execution RCE exists in vLLM versions 0.10.2 and later, in the Completions API endpoint. When processing user-supplied prompt embeddings, the endpoint loads serialized tensors using...

GHSA-3F6C-7FW2-PPM4 vLLM is vulnerable to Server-Side Request Forgery (SSRF) through `MediaConnector` class

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 fetch and process media from user-provided URLs without adequate restrictions on the target hosts. This allows...

CVE-2025-6242

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 fetch and process media from user-provided URLs without adequate restrictions on the target hosts. This allows an...

GHSA-WR9H-G72X-MWHM vLLM is vulnerable to timing attack at bearer auth

Summary The API key support in vLLM performed validation using a method that was vulnerable to a timing attack. This could potentially allow an attacker to discover a valid API key using an approach more efficient than brute force. Details...

PT-2025-41177

Name of the Vulnerable Software and Affected Versions vLLM affected versions not specified Description An issue exists within the MediaConnector class in the vLLM project’s multimodal feature set. Specifically, the load from url and load from url async methods do not sufficiently restrict the...

EUVD-2025-6874

Malicious code in bioql PyPI...

EUVD-2025-7068

Malicious code in bioql PyPI...

GHSA-W6Q7-J642-7C25 vLLM has a Regular Expression Denial of Service (ReDoS, Exponential Complexity) Vulnerability in `pythonic_tool_parser.py`

Summary A Regular Expression Denial of Service ReDoS vulnerability exists in the file vllm/entrypoints/openai/toolparsers/pythonictoolparser.py of the vLLM project. The root cause is the use of a highly complex and nested regular expression for tool call detection, which can be exploited by an...

vLLM has a Regular Expression Denial of Service (ReDoS, Exponential Complexity) Vulnerability in `pythonic_tool_parser.py`

Summary A Regular Expression Denial of Service ReDoS vulnerability exists in the file vllm/entrypoints/openai/toolparsers/pythonictoolparser.py of the vLLM project. The root cause is the use of a highly complex and nested regular expression for tool call detection, which can be exploited by an...

Inefficient Algorithmic Complexity

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Inefficient Algorithmic Complexity through the inputprocessorforphi4mm function. An attacker can cause the application to consume excessive resource...

CVE-2024-9052

A flaw was found in the vLLM distributed training API. This vulnerability allows remote code execution via unsafe deserialization, which uses pickle.loads without sanitization...