Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2024-12450 is a critical-severity SSRF (CWE-918) vulnerability in Infiniflow Ragflow. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique LSASS Memory (T1003.001); ranked in the top 30% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to AC-4 (Information Flow Enforcement) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2024-12450 affects infiniflow/ragflow version 0.12.0, specifically the `web_crawl` function in `document_app.py`. This function fails to filter URL parameters, enabling Full Read Server-Side Request Forgery (SSRF) that allows access to internal network addresses, with their content viewable through generated PDF files. It also lacks restrictions on the file protocol, permitting Arbitrary File Read to access server files. Additionally, the use of an outdated Chromium headless browser in --no-sandbox mode exposes the application to Remote Code Execution (RCE) via known Chromium V8 vulnerabilities. The vulnerability is rated critical with a CVSS score of 9.8 (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H) and is associated with CWE-918 (SSRF).
Remote, unauthenticated attackers can exploit this vulnerability with low complexity and no user interaction required. By supplying malicious URLs to the `web_crawl` function, they can trigger SSRF to probe and read internal network resources, read arbitrary files on the server, or achieve RCE by leveraging Chromium V8 flaws in the sandboxless environment.
The issues are resolved in ragflow version 0.14.0, as detailed in the project's GitHub commit (3faae0b2c2f8a26233ee1442ba04874b3406f6e9). Additional details are available via the Huntr advisory (da06360c-87c3-4ba9-be67-29f6eff9d44a), which reported the vulnerabilities.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-7015
Vulnerability Data
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.…
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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.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.6V1.5.3V5.3.2V10.4.7
Mitigating Controls (NIST 800-53 r5) AI
Information flow enforcement can restrict which destinations the server is allowed to contact on behalf of users.
Input validation directly stops untrusted URLs from being accepted and fetched without destination checks.
Boundary protection limits the network reach of server-initiated requests even if SSRF occurs.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Runtime monitoring of web applications and services can detect anomalous outbound requests indicative of SSRF.
Vulnerability identification processes can discover and record SSRF flaws in web applications.
Network segmentation and egress controls can limit the damage from successful SSRF requests.
Secure development practices directly include input validation and destination allow-listing that prevent SSRF.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.