CVE-2025-29770: vLLM denial of service via outlines unbounded cache
Attack on AI2 Disclosed vulnerabilityInfrastructure vulnerability
An unbounded grammar cache used for structured outputs in vLLM can lead to denial of service conditions. A vulnerability advisory was published detailing the risk.
disclosed CVENo confirmed exploitation, so this record is tracked as a disclosed vulnerability and not counted as an incident. It moves into the counts if CISA or the vendor confirms exploitation. Why
Details
- type
- Attack on AIAn AI model, agent or AI-powered product was the thing exploited, abused or leaked.
- categories
- Infrastructure vulnerabilityCVEs and advisories in AI frameworks, inference servers, MCP servers, AI developer tools and hosting stacks.
- Infrastructure vulnerability
- owasp llm top 10
- mitre atlas
- no technique for these categoriesBoth rows are derived from the type and categories (OWASP 2025 edition, ATLAS release 2026.09), not classified per record. How
- severity
- 2 · Disclosed vulnerabilityCVE or vendor advisory, patched or patchable, no confirmed exploitation.
- targets
- Framework / tooling
- products
- vLLM, outlines
- incident date
- 19 Mar 2025
- first reported
- 19 Mar 2025
- origin
- GitHub Advisory DatabaseVulnerability record from NVD / the GitHub Advisory Database. This product uses the NVD API but is not endorsed or certified by the NVD.
- classifier confidence
- 0.95 · published at or above 0.80; see the methodology
- tags
- CVE-2025-29770 · denial-of-service · cache
- record
- created 2026-10-18 07:00Z · updated 2026-10-18 10:04Z · json
Sources · 2
- 2025-03-19CVE-2025-29770: vLLM denial of service via outlines unbounded cache on diskGitHub Advisory Database · github.com/advisories/GHSA-mgrm-fgjv-mhv8
- 2025-03-19CVE-2025-29770: vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs.NVD · nvd.nist.gov/vuln/detail/CVE-2025-29770
Titles and links belong to their publishers. The summary above is written by GCD AI RADAR in its own words; data is CC BY-SA 4.0.
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