CVE-2025-32444: vLLM Remote Code Execution via Mooncake Integration
Attack on AI2 Disclosed vulnerabilityInfrastructure vulnerability
vLLM instances utilizing the Mooncake integration were vulnerable to remote code execution due to insecure pickle-based serialization over ZeroMQ sockets. The sockets were bound to all interfaces, increasing exposure to network attackers.
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
- incident date
- 29 Apr 2025
- first reported
- 29 Apr 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-2025-32444 · rce · zeromq · pickle
- record
- created 2026-10-18 07:00Z · updated 2026-10-18 10:04Z · json
Sources · 2
- 2025-04-29CVE-2025-32444: vLLM Vulnerable to Remote Code Execution via Mooncake IntegrationGitHub Advisory Database · github.com/advisories/GHSA-hj4w-hm2g-p6w5
- 2025-04-30CVE-2025-32444: vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs.NVD · nvd.nist.gov/vuln/detail/CVE-2025-32444
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.
Related incidents
- 2025-05-28CVE-2025-48943: vLLM Denial of Service via Invalid Regex Output2 Disclosedon AIInfra vuln2 src
- 2025-05-28CVE-2025-48942: vLLM Denial of Service via Invalid JSON Schema2 Disclosedon AIInfra vuln2 src
- 2025-05-28CVE-2025-48887: vLLM ReDoS Vulnerability in pythonic_tool_parser2 Disclosedon AIInfra vuln2 src
- 2025-05-28vLLM Regular Expression Denial of Service2 Disclosedon AIInfra vuln1 src
- 2025-05-28CVE-2025-46722: vLLM MultiModalHasher Image Hashing Weakness2 Disclosedon AIInfra vuln2 src
- 2025-05-28CVE-2025-46570: Timing Side-Channel in vLLM Prefix Caching2 Disclosedon AIInfra vuln2 src