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MEDIUM severity

GHSA-j828-28rj-hfhp vllm

MEDIUMFix: vllm-project/vllm#18454

GHSA-j828-28rj-hfhp is a medium-severity (CVSS 4.3) CWE-1333 vulnerability in vllm. A fix is available for vllm — see the affected versions and patch details below.

vLLM vulnerable to Regular Expression Denial of Service

Also known asCVE-2025-71379
Published
May 28, 2025
Updated
Aug 7, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Sep 19, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

  • CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for GHSA-j828-28rj-hfhp.

EPSS Exploitation Probability

via FIRST.org ↗
0.5%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs41th percentile — riskier than 41% of all scored CVEsHighest risk

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

How urgent is this, really

GHSA-j828-28rj-hfhp plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.

Where this sits among everything scored

Of 377,166 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.

Real-World Exposure

1 pkg affected
🐍vllm

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

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/lora/utils.py Line 173

https://github.com/vllm-project/vllm/blob/2858830c39da0ae153bc1328dbba7680f5fbebe1/vllm/lora/utils.py#L173 Risk Description:

  • The regex r"\((.*?)\)\$?$" matches content inside parentheses. If input such as ((((a|)+)+)+) is passed in, it can cause catastrophic backtracking, leading to a ReDoS vulnerability.
  • Using .*? (non-greedy match) inside group parentheses can be highly sensitive to input length and nesting complexity.

Remediation Suggestions:

  • Limit the input string length.
  • Use a non-recursive matching approach, or write a regex with stricter content constraints.
  • Consider using possessive quantifiers or atomic groups (not supported in Python yet), or split and process before regex matching.

2. vllm/entrypoints/openai/tool_parsers/phi4mini_tool_parser.py Line 52

https://github.com/vllm-project/vllm/blob/2858830c39da0ae153bc1328dbba7680f5fbebe1/vllm/entrypoints/openai/tool_parsers/phi4mini_tool_parser.py#L52

Risk Description:

  • The regex r'functools\[(.*?)\]' uses .*? to match content inside brackets, together with re.DOTALL. If the input contains a large number of nested or crafted brackets, it can cause backtracking and ReDoS.

Remediation Suggestions:

  • Limit the length of model_output.
  • Use a stricter, non-greedy pattern (avoid matching across extraneous nesting).
  • Prefer re.finditer() and enforce a length constraint on each match.

3. vllm/entrypoints/openai/serving_chat.py Line 351

https://github.com/vllm-project/vllm/blob/2858830c39da0ae153bc1328dbba7680f5fbebe1/vllm/entrypoints/openai/serving_chat.py#L351

Risk Description:

  • The regex r'.*"parameters":\s*(.*)' can trigger backtracking if current_text is very long and contains repeated structures.
  • Especially when processing strings from unknown sources, .* matching any content is high risk.

Remediation Suggestions:

  • Use a more specific pattern (e.g., via JSON parsing).
  • Impose limits on current_text length.
  • Avoid using .* to capture large blocks of text; prefer structured parsing when possible.

4. benchmarks/benchmark_serving_structured_output.py Line 650

https://github.com/vllm-project/vllm/blob/2858830c39da0ae153bc1328dbba7680f5fbebe1/benchmarks/benchmark_serving_structured_output.py#L650

Risk Description:

  • The regex r'\{.*\}' is used to extract JSON inside curly braces. If the actual string is very long with unbalanced braces, it can cause backtracking, leading to a ReDoS vulnerability.
  • Although this is used for benchmark correctness checking, it should still handle abnormal inputs carefully.

Remediation Suggestions:

  • Limit the length of actual.
  • Prefer stepwise search for { and } or use a robust JSON extraction tool.
  • Recommend first locating the range with simple string search, then applying regex.

Fix


Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIvllm0.6.3&&< 0.9.00.9.0pip install --upgrade 'vllm==0.9.0'

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for vllm, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update vllm to 0.9.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-j828-28rj-hfhp is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-j828-28rj-hfhp can be triaged on real exposure rather than presence alone.

Tailored to GHSA-j828-28rj-hfhp. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### 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/lora/utils.py [Line 173](https://github.com/vllm-project/vllm/blob/2858830c39da0ae153bc1328dbba7680f5fbebe1/vllm/lora/utils.py#L173) https://github.com/vllm-project/vllm/blob/2858830c39da0ae153bc1328dbba7680f5fbebe1/vllm/lora/utils.py#L173 **Risk Description:** - The regex `r"\((.*?)\)\$
O3 Security · Impact-Aware SCA

Is GHSA-j828-28rj-hfhp in your dependencies?

O3 Security finds GHSA-j828-28rj-hfhp across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

GHSA-j828-28rj-hfhp: vllm DoS (Medium 4.3) | O3 Security