Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:NSummary
CVE-2024-11822 is a high-severity SSRF (CWE-918) vulnerability in Dify Dify. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 44th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as LLM Application Platforms; in the Supply Chain and Deployment risk domain.
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-2024-11822 is a Server-Side Request Forgery (SSRF) vulnerability, classified as CWE-918, affecting langgenius/dify version 0.9.1. The issue arises from improper handling of the api_endpoint parameter, which allows attackers to make direct requests to internal network services from the vulnerable application.
Unauthenticated remote attackers can exploit this vulnerability over the network with low complexity and no user interaction required (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N, score 7.5). Exploitation enables unauthorized access to internal servers and potential exposure of sensitive information, including the AWS metadata endpoint.
The primary advisory is available on Huntr.com at https://huntr.com/bounties/f3042029-5d4e-41c6-850d-bbe02fae6592, which details the vulnerability report but does not specify patches or mitigations in the provided information.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-7035
Vulnerability Data
langgenius/dify version 0.9.1 contains a Server-Side Request Forgery (SSRF) vulnerability. The vulnerability exists due to improper handling of the api_endpoint parameter, allowing an attacker to make direct requests to internal network services. This can lead to unauthorized access to internal…
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servers and potentially expose sensitive information, including access to the AWS metadata endpoint.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: dify
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.
Secure development practices directly include input validation and destination allow-listing that prevent SSRF.
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.
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.
Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.