Skip to main content
VulnerabilityPublished Updated

CVE-2024-10131: infiniflow/ragflow · Code Injection

Affects infiniflow/ragflowSource CVE Database V5

0

Not known to be exploited · CVSS 8.8 High.

Data as of 26 Oct 2026, 10:12 UTC

CVSS 3.0 base score
8.8High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
1.1% chance of exploitation in 30 days – higher than 66% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 19 Oct 2024

  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 26 Oct 2026.

What to do

Affected software

ProductAffectedFixed in
GitHubinfiniflow/ragflowpkg:github/infiniflow/ragflowOther threatsAffected
  • =0.11.0
Fixed in–

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

To mitigate CVE-2024-10131, European organizations should immediately audit their use of infiniflow/ragflow, especially version 0.11.0 and earlier. Specific actions include: 1) Implement strict input validation and sanitization for all user-supplied parameters, particularly 'llm_factory' and 'llm_name', ensuring only expected and safe values are accepted. 2) Refactor the dynamic class instantiation logic to use a whitelist approach, mapping allowed factory names to classes explicitly rather than relying on direct dictionary indexing. 3) Employ runtime application self-protection (RASP) or web application firewalls (WAF) with custom rules to detect and block suspicious input patterns targeting this vulnerability. 4) Monitor logs for unusual activity related to the add_llm function or unexpected class instantiations. 5) Isolate and restrict network access to systems running infiniflow/ragflow to trusted users and networks only. 6) Stay alert for official patches or updates from the infiniflow project and apply them promptly once released. 7) Conduct penetration testing focusing on this vulnerability to verify mitigation effectiveness. 8) Educate development and security teams about the risks of dynamic code execution and the importance of secure coding practices.

Description

The `add_llm` function in `llm_app.py` in infiniflow/ragflow version 0.11.0 contains a remote code execution (RCE) vulnerability. The function uses user-supplied input `req['llm_factory']` and `req['llm_name']` to dynamically instantiate classes from various model dictionaries. This approach allows an attacker to potentially execute arbitrary code due to the lack of comprehensive input validation or sanitization. An attacker could provide a malicious value for 'llm_factory' that, when used as an index to these model dictionaries, results in the execution of arbitrary code.

References

Community reviews

Loading reviews…