Summary
Description
https://github.com/vllm-project/vllm/security/advisories/GHSA-rh4j-5rhw-hr54 reported a vulnerability where loading a malicious model could result in code execution on the vllm host. The fix applied to specify weights_only=True to calls to torch.load() did not solve the problem prior to PyTorch 2.6.0.
PyTorch has issued a new CVE about this problem: https://github.com/advisories/GHSA-53q9-r3pm-6pq6
This means that versions of vLLM using PyTorch before 2.6.0 are vulnerable to this problem.
Background Knowledge
When users install VLLM according to the official manual
But the version of PyTorch is specified in the requirements. txt file
So by default when the user install VLLM, it will install the PyTorch with version 2.5.1
In CVE-2025-24357, weights_only=True was used for patching, but we know this is not secure.
Because we found that using Weights_only=True in pyTorch before 2.5.1 was unsafe
Here, we use this interface to prove that it is not safe.
Credit
This vulnerability was found By Ji'an Zhou and Li'shuo Song
Impact
GHSA-GGPF-24JW-3FCW has a CVSS score of 9.8 (Critical). The vector is network-reachable, no privileges required, and no user interaction. A CVSS score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether this affects your application depends on whether the vulnerable code is present and reachable in your environment. A fixed version is available (0.8.0); upgrading removes the vulnerable code path.
Affected versions
Security releases
Kodem intelligence
Severity tells you how bad this could be in the worst case. It does not tell you whether you are exposed. Exploitability and impact are functions of runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A vulnerable package can sit in your dependency tree and never run.
Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter. Kodem's runtime-powered SCA identifies whether this CVE is reachable in your applications.
Remediation advice
update PyTorch version to 2.6.0
Frequently Asked Questions
- What is GHSA-GGPF-24JW-3FCW? GHSA-GGPF-24JW-3FCW is a critical-severity security vulnerability in vllm (pip), affecting versions < 0.8.0. It is fixed in 0.8.0.
- How severe is GHSA-GGPF-24JW-3FCW? GHSA-GGPF-24JW-3FCW has a CVSS score of 9.8 (Critical). This score reflects the worst-case severity of the vulnerability, not your specific exposure. Whether it represents real risk in your environment depends on whether the vulnerable code is present and reachable.
- Which versions of vllm are affected by GHSA-GGPF-24JW-3FCW? vllm (pip) versions < 0.8.0 is affected.
- Is there a fix for GHSA-GGPF-24JW-3FCW? Yes. GHSA-GGPF-24JW-3FCW is fixed in 0.8.0. Upgrade to this version or later.
- Is GHSA-GGPF-24JW-3FCW exploitable, and should I be worried? Whether GHSA-GGPF-24JW-3FCW is exploitable in your environment depends on whether the vulnerable code is present and reachable. A CVSS score is a worst-case rating; it does not account for your specific deployment, configuration, or usage patterns. Kodem, an Intelligent Application Security platform, uses runtime intelligence to show which vulnerabilities actually execute in production, so you can focus on the ones that represent real risk. Get a demo
- What actually determines whether GHSA-GGPF-24JW-3FCW is exploitable, and how bad it is? Exploitability and impact are not fixed properties of a CVE. They depend on runtime truth: whether the vulnerable code is present, reachable, and actually executes in your application. A high CVSS score on a dependency that never runs is not the same as real risk. Kodem, an Intelligent Application Security platform, uses runtime intelligence to reveal which vulnerabilities actually execute in production, so teams prioritize the ones that genuinely matter.
- How do I fix GHSA-GGPF-24JW-3FCW? Upgrade
vllmto 0.8.0 or later.