Skip to main content
CVE-2025-61784VulnerabilityPublished

CVE-2025-61784: hiyouga LLaMA-Factory · Path Traversal

Affects hiyouga LLaMA-FactorySource CVE Database V5

0

Not known to be exploited · CVSS 7.6 High : upgrade to 0.9.4 soon.

Data as of 26 Oct 2026, 06:26 UTC

CVSS 3.1 base score
7.6High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.3% chance of exploitation in 30 days – higher than 31% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 0.9.4
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:L

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 7 Oct 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq 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 2026-10-25.

What to do

Upgrade hiyouga LLaMA-Factory to 0.9.4.

Affected software

ProductAffectedFixed in
hiyouga LLaMA-FactoryAffected
  • <0.9.4
Fixed in
  • 0.9.4

AI-suggested

European organizations should immediately upgrade all instances of LLaMA-Factory to version 0.9.4 or later, where the vulnerability is patched. Until upgrades are complete, restrict access to the chat API to trusted users only and enforce strong authentication and authorization controls. Implement network-level segmentation and firewall rules to limit the server's ability to make outbound HTTP requests to internal services, reducing SSRF impact. Employ application-layer filtering or web application firewalls (WAFs) to detect and block suspicious URL patterns or unexpected requests. Conduct thorough audits of server file permissions to minimize sensitive file exposure in case of LFI exploitation. Monitor logs for unusual access patterns or unexpected file reads. Additionally, consider deploying runtime application self-protection (RASP) solutions to detect and block exploitation attempts in real time. Educate developers and DevOps teams on secure coding practices, especially validating and sanitizing all user-supplied inputs that influence network requests or file access.

Description

LLaMA-Factory is a tuning library for large language models. Prior to version 0.9.4, a Server-Side Request Forgery (SSRF) vulnerability in the chat API allows any authenticated user to force the server to make arbitrary HTTP requests to internal and external networks. This can lead to the exposure of sensitive internal services, reconnaissance of the internal network, or interaction with third-party services. The same mechanism also allows for a Local File Inclusion (LFI) vulnerability, enabling users to read arbitrary files from the server's filesystem. The vulnerability exists in the `_process_request` function within `src/llamafactory/api/chat.py.` This function is responsible for processing incoming multimodal content, including images, videos, and audio provided via URLs. The function checks if the provided URL is a base64 data URI or a local file path (`os.path.isfile`). If neither is true, it falls back to treating the URL as a web URI and makes a direct HTTP GET request using `requests.get(url, stream=True).raw` without any validation or sanitization of the URL. Version 0.9.4 fixes the underlying issue.

References

Community reviews

Loading reviews…