CVE-2025-69286
Infiniflow Ragflow ≤ 0.22.0
Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-69286 is a high-severity Generation of Predictable Numbers or Identifiers (CWE-340) vulnerability in Infiniflow Ragflow. Its CVSS base score is 8.9 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Web Cookies (T1606.001); ranked at the 40th percentile by exploit likelihood (below the median); 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 SA-11 (Developer Testing and Evaluation) and SC-12 (Cryptographic Key Establishment and Management) — 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-2025-69286 affects RAGFlow, an open-source Retrieval-Augmented Generation (RAG) engine, in versions prior to 0.22.0. The vulnerability stems from an insecure key generation algorithm used in the API key and beta (assistant/agent share authentication) token generation process. Both tokens are generated with the same URLSafeTimedSerializer and predictable inputs, making them mutually derivable and linked to CWE-340 (Generation of Predictable Numbers or Identifiers). The issue has a CVSS v3.1 base score of 9.8 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H), indicating critical severity with high confidentiality, integrity, and availability impacts.
An attacker with access to a shared assistant or agent URL can exploit this vulnerability without authentication or privileges. By analyzing the beta token embedded in the URL, they can derive the victim's personal API key due to the predictable inputs and shared serializer. This grants full control over the assistant/agent owner's account, potentially allowing unauthorized data access, modification, or deletion within the RAGFlow instance.
The GitHub security advisory (GHSA-9j5g-g4xm-57w7) and associated commit (a3bb4aadcc3494fb27f2a9933b4c46df8eb532e6) confirm that upgrading to version 0.22.0 resolves the issue by addressing the token generation flaws, as detailed in the affected code paths in system_app.py, utils/__init__.py, and api_utils.py.
RAGFlow's role as a RAG engine highlights relevance to AI/ML deployments, where shared assistants or agents may expose sensitive LLM workflows to token derivation risks. No public evidence of real-world exploitation is available as of the CVE publication on 2025-12-31.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-206092
Vulnerability Data
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine. In versions prior to 0.22.0, the use of an insecure key generation algorithm in the API key and beta (assistant/agent share auth) token generation process allows these tokens to be mutually derivable.…
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Specifically, both tokens are generated using the same `URLSafeTimedSerializer` with predictable inputs, enabling an unauthorized user who obtains the shared assistant/agent URL to derive the personal API key. This grants them full control over the assistant/agent owner's account. Version 0.22.0 fixes the issue.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 6 hardening rules · 3 OS baselines
V11.3.4
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover predictable number generation through targeted analysis or fuzzing of identifier creation routines.
Cryptographic key establishment and management mandates proper entropy and randomness during generation, directly stopping predictable identifiers at the source.
Authenticator management requires secure initial distribution and handling of authenticators, structurally preventing predictable values from being usable.
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 SDLC practices directly require cryptographically strong RNG for identifiers and tokens, covering most of this weakness while the control addresses many additional development issues.
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.
Cryptographic controls require use of approved, sufficiently random algorithms and key-generation methods, directly mitigating predictable number/identifier weaknesses.
Security testing in development can detect predictable identifiers through static/dynamic analysis and fuzzing, reducing residual risk.
A secure SDLC incorporates threat modelling and secure-design reviews that flag predictable identifier generation early in the lifecycle.
Secure-coding standards explicitly forbid predictable random functions and mandate cryptographically secure RNGs, preventing the weakness at the source.
Secure authentication mechanisms depend on unpredictable session tokens, nonces and challenges; eliminating predictable identifiers strengthens authentication integrity.
Hardening callouts derived
Configuration rules from DISA STIG baselines that bear on weaknesses of the type cited by this CVE. Each rule is shown with the relationship its mapping actually records, against the CWE it was authored against. Derived via CVE→CWE over `controls_xwalks` (authoritative rows only; rows rated `none` are excluded).
Oracle Linux 8 (2 rules)
- V-248524 OL 8 must implement NIST FIPS-validated cryptography for the following: To provision digital signatures, to generate cryptographic hashes, and to protect data requiring data-at-rest protections in accordance with applicable federal laws, Executive Orders, directives, policies, regulations, and standards. prevents CWE-340
- V-248600 OL 8 must have the packages required to use the hardware random number generator entropy gatherer service. prevents CWE-340
RHEL 7 (1 rule)
- V-204497 The Red Hat Enterprise Linux operating system must implement NIST FIPS-validated cryptography for the following: to provision digital signatures, to generate cryptographic hashes, and to protect data requiring data-at-rest protections in accordance with applicable federal laws, Executive Orders, directives, policies, regulations, and standards. prevents CWE-340
RHEL 8 (1 rule)
- V-244527 RHEL 8 must have the packages required to use the hardware random number generator entropy gatherer service. prevents CWE-340