Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:HSummary
CVE-2025-31677 is a high-severity CSRF (CWE-352) vulnerability in Artificial Intelligence Project Artificial Intelligence. Its CVSS base score is 8.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 11th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Other Platforms; in the Other ATLAS/OWASP Terms risk domain.
The strongest mitigations our analysis identified map to AC-3 (Access Enforcement) and SC-23 (Session Authenticity) — 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-2025-31677 is a Cross-Site Request Forgery (CSRF) vulnerability, classified under CWE-352, in the Drupal AI (Artificial Intelligence) contributed module. This flaw affects versions of the module from 1.0.0 up to but not including 1.0.2 and has a CVSS v3.1 base score of 8.8 (AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H), indicating high severity due to its potential for significant impact on confidentiality, integrity, and availability.
The vulnerability can be exploited by unauthenticated attackers over the network with low complexity, requiring only user interaction such as a victim visiting a malicious webpage. Authenticated Drupal users with the AI module enabled are at risk; an attacker can trick them into performing unintended state-changing actions on the site via forged requests, potentially leading to high-impact compromises like unauthorized data access, modification, or denial of service.
The official Drupal security advisory SA-CONTRIB-2025-003 at https://www.drupal.org/sa-contrib-2025-003 details the issue and recommends upgrading to Drupal AI (Artificial Intelligence) version 1.0.2 or later, which resolves the CSRF protection deficiency. Site administrators should also review access controls for the module and ensure CSRF tokens are properly enforced on relevant endpoints.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-9046
Vulnerability Data
Cross-Site Request Forgery (CSRF) vulnerability in Drupal AI (Artificial Intelligence) allows Cross Site Request Forgery.This issue affects AI (Artificial Intelligence): from 1.0.0 before 1.0.2.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Other Platforms
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: ai, artificial intelligence
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V3.3.2V3.5.1V10.2.1
Mitigating Controls (NIST 800-53 r5) AI
Access enforcement requires verifying that state-changing requests originate from the authenticated user rather than a forged cross-site source.
Protecting session authenticity prevents attackers from replaying or forging authenticated requests via the victim's browser.
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 anti-CSRF controls such as tokens or SameSite attributes.
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.
By denying access to phishing or malicious sites, the control lowers the likelihood that a user will be tricked into submitting a forged request that performs an unintended action on another site.
Contextual intelligence about emerging CSRF toolkits can be translated into updated anti-CSRF token or same-site policy configurations across applications.