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.
Weakness
The product does not properly control the allocation and maintenance of a limited resource.
Potential Mitigations
Mitigation of resource exhaustion attacks requires that the target system either:
The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question.
The second solution is simply difficult to effectively institute – and even when properly done, it does not provide a full solution. It simply makes the attack require more resources on the part of the attacker.
Related Attack Patterns
- https://cwe.mitre.org/data/definitions/147.html
- https://cwe.mitre.org/data/definitions/227.html
- https://cwe.mitre.org/data/definitions/492.html
References
- https://github.com/vllm-project/vllm/commit/c9a788eedc412acceaa5112e0d44624b49841577
- 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
- https://github.com/vllm-project/vllm/security/advisories/GHSA-48jh-3gj7-fg8v