CVE-2026-73556: CWE-400: Uncontrolled Resource Consumption in vllm-project vllm
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.
AI Analysis
Technical Summary
In vLLM before version 0.26.0, the structured_outputs.regex parameter in the file vllm/v1/structured_output/backend_lm_format_enforcer.py is passed to lmformatenforcer.RegexParser without applying compile_regex_with_timeout or validation in the validate_structured_output_request_lm_format_enforcer function. This lack of validation allows an unauthenticated attacker to send a specially crafted /v1/completions request that triggers catastrophic regular expression processing, consuming a CPU core and stalling the structured-output engine path. The vulnerability is classified under CWE-400 (Uncontrolled Resource Consumption) and CWE-1333. The issue is resolved in vLLM version 0.26.0.
Potential Impact
An unauthenticated attacker can cause a denial of service by sending a request that triggers excessive CPU consumption, stalling the structured-output engine. There is no impact on confidentiality or integrity, only availability is affected.
Mitigation Recommendations
Upgrade to vLLM version 0.26.0 or later, where this vulnerability is fixed. Patch status is confirmed by the vendor stating the issue is resolved in 0.26.0. No other mitigations are indicated.
CVE-2026-73556: CWE-400: Uncontrolled Resource Consumption in vllm-project vllm
Description
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.
CVSS v3.1
Score 5.3medium
Affected software
Run on your own infrastructure? Check whether these packages are installed with threat-finder — our free open-source scanner.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
In vLLM before version 0.26.0, the structured_outputs.regex parameter in the file vllm/v1/structured_output/backend_lm_format_enforcer.py is passed to lmformatenforcer.RegexParser without applying compile_regex_with_timeout or validation in the validate_structured_output_request_lm_format_enforcer function. This lack of validation allows an unauthenticated attacker to send a specially crafted /v1/completions request that triggers catastrophic regular expression processing, consuming a CPU core and stalling the structured-output engine path. The vulnerability is classified under CWE-400 (Uncontrolled Resource Consumption) and CWE-1333. The issue is resolved in vLLM version 0.26.0.
Potential Impact
An unauthenticated attacker can cause a denial of service by sending a request that triggers excessive CPU consumption, stalling the structured-output engine. There is no impact on confidentiality or integrity, only availability is affected.
Mitigation Recommendations
Upgrade to vLLM version 0.26.0 or later, where this vulnerability is fixed. Patch status is confirmed by the vendor stating the issue is resolved in 0.26.0. No other mitigations are indicated.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- GitHub_M
- Date Reserved
- 2026-08-12T20:53:46.380Z
- Cvss Version
- 3.1
- State
- PUBLISHED
- Remediation Level
- null
Threat ID: 6a7ddecdbf8831d5395d0180
Added to database: 08/13/2026, 15:12:13 UTC
Last enriched: 08/13/2026, 15:28:25 UTC
Last updated: 08/13/2026, 17:43:42 UTC
Views: 5
Community Reviews
0 reviewsCrowdsource mitigation strategies, share intel context, and vote on the most helpful responses. Sign in to add your voice and help keep defenders ahead.
Want to contribute mitigation steps or threat intel context? Sign in or create an account to join the community discussion.
Actions
Updates to AI analysis require Pro Console access. Upgrade inside Console → Billing.
Need more coverage?
Upgrade to Pro Console for AI refresh and higher limits.
For incident response and remediation, OffSeq services can help resolve threats faster.
Latest Threats
Check if your credentials are on the dark web
Instant breach scanning across billions of leaked records. Free tier available.