GHSA-9HCF-V7M4-6M2J vLLM allows clients to crash the openai server with invalid regex

Impact A denial of service bug caused the vLLM server to crash if an invalid regex was provided while using structured output. This vulnerability is similar to GHSA-6qc9-v4r8-22xg, but for regex instead of a JSON schema. Issue with more details: https://github.com/vllm-project/vllm/issues/17313...

Uncaught Exception

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Uncaught Exception through the guidedjson parameter when using xgrammar validation. An attacker can cause the application to crash by sending an...

GHSA-6QC9-V4R8-22XG vLLM DOS: Remotely kill vllm over http with invalid JSON schema

Summary Hitting the /v1/completions API with a invalid jsonschema as a Guided Param will kill the vllm server Details The following API call venv derekh@ip-172-31-15-108 $ curl -s http://localhost:8000/v1/completions -H "Content-Type: application/json" -d '"model":...

vLLM DOS: Remotely kill vllm over http with invalid JSON schema

Summary Hitting the /v1/completions API with a invalid jsonschema as a Guided Param will kill the vllm server Details The following API call venv derekh@ip-172-31-15-108 $ curl -s http://localhost:8000/v1/completions -H "Content-Type: application/json" -d '"model":...

Regular Expression Denial of Service (ReDoS)

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Regular Expression Denial of Service ReDoS in multiple locations in the code. An attacker can cause a denial of service by supplying specially craft...

GHSA-J828-28RJ-HFHP vLLM vulnerable to Regular Expression Denial of Service

Summary A recent review identified several regular expressions in the vllm codebase that are susceptible to Regular Expression Denial of Service ReDoS attacks. These patterns, if fed with crafted or malicious input, may cause severe performance degradation due to catastrophic backtracking. 1...

vLLM vulnerable to Regular Expression Denial of Service

Summary A recent review identified several regular expressions in the vllm codebase that are susceptible to Regular Expression Denial of Service ReDoS attacks. These patterns, if fed with crafted or malicious input, may cause severe performance degradation due to catastrophic backtracking. 1...

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...

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...

Regular Expression Denial of Service (ReDoS)

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Regular Expression Denial of Service ReDoS through the pythonictoolparser.py. An attacker can cause severe performance degradation or make the servi...

PT-2025-23227 · Vllm · Vllm

Name of the Vulnerable Software and Affected Versions: vLLM versions 0.8.0 through 0.8.x Description: The issue is a Denial of Service ReDoS that causes the vLLM server to crash if an invalid regex is provided while using structured output. This is similar to a previously identified issue, but it...

PT-2025-23136 · Vllm · Vllm

Name of the Vulnerable Software and Affected Versions: vLLM versions 0.7.0 through 0.8.x Description: The issue concerns a security and data integrity problem in the image hashing method of the MultiModalHasher class. Specifically, the method serializes PIL.Image.Image objects using only...

PT-2025-23224 · Vllm · Vllm

Name of the Vulnerable Software and Affected Versions: vLLM versions 0.6.4 through 0.9.0 Description: The issue is a Regular Expression Denial of Service ReDoS vulnerability in the file vllm/entrypoints/openai/tool parsers/pythonic tool parser.py. The root cause is the use of a highly complex and...

PT-2025-23228

Name of the Vulnerable Software and Affected Versions vLLM versions 0.8.0 through 0.9.0 Description The vLLM backend used with the "/v1/chat/completions" API endpoint fails to validate unexpected or malformed input in the pattern and type fields when the tools functionality is invoked. These inpu...

PT-2025-23226 · Vllm · Vllm

Name of the Vulnerable Software and Affected Versions: vLLM versions 0.8.0 through 0.9.0 Description: The issue arises when the /v1/completions API endpoint is hit with an invalid json schema as a Guided Param, causing the vLLM server to crash. This is similar to a previously known issue but...

PT-2025-23135 · Vllm · Vllm

Name of the Vulnerable Software and Affected Versions: vLLM versions prior to 0.9.0 Description: The issue arises from the prefix caching mechanism in vLLM, which may expose the system to a timing side-channel attack. When a new prompt is processed, if the PageAttention mechanism finds a matching...

Remote Code Execution (RCE)

vllm is vulnerable to Remote Code Execution RCE. The vulnerability is due to improper socket binding in the TCPStore and PyNcclPipe services listening on all network interfaces, potentially allowing unauthorized access to control message channels...

CVE-2025-47277

vLLM, an inference and serving engine for large language models LLMs, has an issue in versions 0.6.5 through 0.8.4 that ONLY impacts environments using the PyNcclPipe KV cache transfer integration with the V0 engine. No other configurations are affected. vLLM supports the use of...

Deserialization of Untrusted Data

Overview vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs Affected versions of this package are vulnerable to Deserialization of Untrusted Data through the PyNcclPipe service if it is in use with the V0 engine. An attacker can execute arbitrary code on the...

vLLM Allows Remote Code Execution via PyNcclPipe Communication Service

Impacted Environments This issue ONLY impacts environments using the PyNcclPipe KV cache transfer integration with the V0 engine. No other configurations are affected. Summary vLLM supports the use of the PyNcclPipe class to establish a peer-to-peer communication domain for data transmission...