Ragflow
CVE-2024-10131
HIGH
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A05:2025 - Injection
ASVS 5.0
V1 - Encoding and Sanitization Code injection prevention, sandbox exec
MITRE ATT&CK
2 techniques across 2 tactics: Execution, Initial Access The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Impact | CVSS score of 8.8 (HIGH). Attack characteristics: network attack vector, low complexity, low privileges required, no user interaction not required. Public proof-of-concept exploit code is available. |
| Exploit ScenarioDerived | A remote attacker could inject and execute arbitrary code within the application by sending crafted requests to the affected application. |
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Alert meAnalysisAI
The add_llm function in llm_app.py in infiniflow/ragflow version 0.11.0 contains a remote code execution (RCE) vulnerability. Rated high severity (CVSS 8.8), this vulnerability is remotely exploitable, low attack complexity. Public exploit code available and no vendor patch available.
RemediationAI
No vendor patch is available at time of analysis. Monitor vendor advisories for updates. Never evaluate user-controlled input as code. Use sandboxing, disable dangerous functions, apply strict input validation.
Affects your stack
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Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
This vulnerability is classified as Code Injection (CWE-94), which allows attackers to inject and execute arbitrary code within the application. 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. Affected products include: Infiniflow Ragflow. Version information: version 0.11.0.
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Severity by source
AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Primary rating from NVD · only source for this CVE.
CVSS VectorNVD
DescriptionNVD
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.
Threat Intelligence Overview
NVD
CVE.org
EPSS
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Code injection occurs when an application accepts user input and passes it directly into a language interpreter or evaluator without proper sanitization.
Remote Code Execution represents the critical moment when an attacker successfully runs arbitrary code on a target system without physical access.
Affected Products (CPE)NVD
A vulnerability in infiniflow/ragflow versions v0.12.0 allows for remote code execution. Rated critical severity (CVSS 9
Path traversal vulnerability in RAGFlow RAG engine version 0.23.1 allows unauthenticated attackers to read arbitrary fil
In infiniflow/ragflow versions 0.12.0, the `web_crawl` function in `document_app.py` contains multiple vulnerabilities.
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine. Rated high severity (CVSS 8.9), this vulnerabilit
RAGFlow versions prior to 0.22.0 generate API keys and beta assistant/agent share tokens with a predictable scheme, lett
Remote code execution in RAGFlow versions prior to 0.23.0 allows a low-privileged authenticated user (a normal login acc
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. Rated high s
A Server-Side Request Forgery (SSRF) vulnerability exists in infiniflow/ragflow version 0.12.0. Rated high severity (CVS
RAGFlow 0.13.0 suffers from improper access control in document-hooks.ts, allowing unauthorized access to user documents
A vulnerability in infiniflow/ragflow version RAGFlow-0.13.0 allows for partial account takeover via insecure data query
Server-side template injection in RAGFlow 0.24.0 and earlier allows any authenticated user to execute arbitrary operatin
Unauthenticated network attackers can reach the get_dataset entry point in RAGFlow 0.24.0's evaluation_app API and, depe
GitHub PoC
Exploit-DB