infiniflow CVE Vulnerabilities & Metrics

Focus on infiniflow vulnerabilities and metrics.

Last updated: 08 Mar 2025, 23:25 UTC

About infiniflow Security Exposure

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.

Global CVE Overview

Total infiniflow CVEs: 1
Earliest CVE date: 19 Oct 2024, 04:15 UTC
Latest CVE date: 19 Oct 2024, 04:15 UTC

Latest CVE reference: CVE-2024-10131

Rolling Stats

30-day Count (Rolling): 0
365-day Count (Rolling): 1

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.

Variations & Growth

Month Variation (Calendar): 0%
Year Variation (Calendar): 0%

Month Growth Rate (30-day Rolling): 0.0%
Year Growth Rate (365-day Rolling): 0.0%

Monthly CVE Trends (current vs previous Year)

Annual CVE Trends (Last 20 Years)

Critical infiniflow CVEs (CVSS ≥ 9) Over 20 Years

CVSS Stats

Average CVSS: 0.0

Max CVSS: 0

Critical CVEs (≥9): 0

CVSS Range vs. Count

Range Count
0.0-3.9 1
4.0-6.9 0
7.0-8.9 0
9.0-10.0 0

CVSS Distribution Chart

Top 5 Highest CVSS infiniflow CVEs

These are the five CVEs with the highest CVSS scores for infiniflow, sorted by severity first and recency.

All CVEs for infiniflow

CVE-2024-10131 infiniflow vulnerability CVSS: 0 19 Oct 2024, 04:15 UTC

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.