CVE-2024-9053: vllm-project/vllm · Deserialization of Untrusted Data
Affects vllm-project/vllmSource CVE Database V5
Not known to be exploited · CVSS 9.8 Critical.
Data as of 26 Oct 2026, 12:54 UTC
- EPSS
- 1.3% chance of exploitation in 30 days – higher than 71% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HExploitation evidence
Disclosed: evidence found.
CVE published 20 Mar 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.
What to do
Affected software
| Product | Affected | Fixed in |
|---|---|---|
GitHubvllm-project/vllmpkg:github/vllm-project/vllmOther threats | Affected
| Fixed in– |
Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.
AI-suggested
- Immediate mitigation should focus on restricting network access to the vllm RPC server, limiting exposure to trusted internal networks only.
- Implement strict input validation and filtering to prevent untrusted or malformed pickle data from reaching the deserialization function.
- Replace or modify the use of cloudpickle.loads() with safer deserialization alternatives or sandboxed environments that limit code execution capabilities.
- Monitor network traffic and logs for anomalous or unexpected RPC calls that could indicate exploitation attempts.
- Apply any forthcoming patches or updates from the vllm-project as soon as they become available.
- Consider deploying runtime application self-protection (RASP) or endpoint detection and response (EDR) tools that can detect and block suspicious deserialization activities.
- Educate developers and security teams about the risks of unsafe deserialization and enforce secure coding practices in AI/ML projects.
- If patching is delayed, consider isolating vllm instances in containerized or virtualized environments with minimal privileges to limit potential damage.
Description
vllm-project vllm version 0.6.0 contains a vulnerability in the AsyncEngineRPCServer() RPC server entrypoints. The core functionality run_server_loop() calls the function _make_handler_coro(), which directly uses cloudpickle.loads() on received messages without any sanitization. This can result in remote code execution by deserializing malicious pickle data.