Focus on infiniflow vulnerabilities and metrics.
Last updated: 16 Apr 2025, 22:25 UTC
This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with infiniflow. We track both calendar-based metrics (using fixed periods) and rolling metrics (using gliding windows) to give you a comprehensive view of security trends and risk evolution. Use these insights to assess risk and plan your patching strategy.
For a broader perspective on cybersecurity threats, explore the comprehensive list of CVEs by vendor and product. Stay updated on critical vulnerabilities affecting major software and hardware providers.
Total infiniflow CVEs: 5
Earliest CVE date: 19 Oct 2024, 04:15 UTC
Latest CVE date: 20 Mar 2025, 10:15 UTC
Latest CVE reference: CVE-2024-12871
30-day Count (Rolling): 4
365-day Count (Rolling): 5
Calendar-based Variation
Calendar-based Variation compares a fixed calendar period (e.g., this month versus the same month last year), while Rolling Growth Rate uses a continuous window (e.g., last 30 days versus the previous 30 days) to capture trends independent of calendar boundaries.
Month Variation (Calendar): 0%
Year Variation (Calendar): 0%
Month Growth Rate (30-day Rolling): 0.0%
Year Growth Rate (365-day Rolling): 0.0%
Average CVSS: 0.0
Max CVSS: 0
Critical CVEs (≥9): 0
| Range | Count |
|---|---|
| 0.0-3.9 | 5 |
| 4.0-6.9 | 0 |
| 7.0-8.9 | 0 |
| 9.0-10.0 | 0 |
These are the five CVEs with the highest CVSS scores for infiniflow, sorted by severity first and recency.
An XSS vulnerability in infiniflow/ragflow version 0.12.0 allows an attacker to upload a malicious PDF file to the knowledge base. When the file is viewed within Ragflow, the payload is executed in the context of the user's browser. This can lead to session hijacking, data exfiltration, or unauthorized actions performed on behalf of the victim, compromising sensitive user data and affecting the integrity of the entire application.
In infiniflow/ragflow version v0.12.0, there is an improper authentication vulnerability that allows a user to view another user's invite list. This can lead to a privacy breach where users' personal or private information, such as email addresses or usernames in the invite list, could be exposed without their consent. This data leakage can facilitate further attacks, such as phishing or spam, and result in loss of trust and potential regulatory issues.
A Server-Side Request Forgery (SSRF) vulnerability exists in infiniflow/ragflow version 0.12.0. The vulnerability is present in the `POST /v1/llm/add_llm` and `POST /v1/conversation/tts` endpoints. Attackers can specify an arbitrary URL as the `api_base` when adding an `OPENAITTS` model, and subsequently access the `tts` REST API endpoint to read contents from the specified URL. This can lead to unauthorized access to internal web resources.
In infiniflow/ragflow versions 0.12.0, the `web_crawl` function in `document_app.py` contains multiple vulnerabilities. The function does not filter URL parameters, allowing attackers to exploit Full Read SSRF by accessing internal network addresses and viewing their content through the generated PDF files. Additionally, the lack of restrictions on the file protocol enables Arbitrary File Read, allowing attackers to read server files. Furthermore, the use of an outdated Chromium headless version with --no-sandbox mode enabled makes the application susceptible to Remote Code Execution (RCE) via known Chromium v8 vulnerabilities. These issues are resolved in version 0.14.0.
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.