CVE-2026-73556

Published: Ago 13, 2026 Last Modified: Ago 13, 2026
ExploitDB:
Other exploit source:
Google Dorks:
MEDIUM 5,3
Attack Vector: network
Attack Complexity: low
Privileges Required: none
User Interaction: none
Scope: unchanged
Confidentiality: none
Integrity: none
Availability: low

Description

AI Translation Available

vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the structured_outputs.regex parameter in vllm/v1/structured_output/backend_lm_format_enforcer.py is passed to lmformatenforcer.RegexParser without compile_regex_with_timeout or validation in validate_structured_output_request_lm_format_enforcer, allowing an unauthenticated /v1/completions request against the lm-format-enforcer backend to consume a CPU core and stall the structured-output engine path with a catastrophic regular expression. This issue is fixed in version 0.26.0.

400

Uncontrolled Resource Consumption

Draft
Common Consequences
Security Scopes Affected:
Availability Access Control Other
Potential Impacts:
Dos: Crash, Exit, Or Restart Dos: Resource Consumption (Cpu) Dos: Resource Consumption (Memory) Dos: Resource Consumption (Other) Bypass Protection Mechanism Other
Applicable Platforms
Technologies: Not Technology-Specific, AI/ML
View CWE Details
1333

Inefficient Regular Expression Complexity

Draft
Common Consequences
Security Scopes Affected:
Availability
Potential Impacts:
Dos: Resource Consumption (Cpu)
Applicable Platforms
All platforms may be affected
View CWE Details
https://github.com/vllm-project/vllm/commit/c9a788eedc412acceaa5112e0d44624b498…
https://github.com/vllm-project/vllm/pull/47595
https://github.com/vllm-project/vllm/releases/tag/v0.26.0
https://github.com/vllm-project/vllm/security/advisories/GHSA-48jh-3gj7-fg8v