Raw vector
CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:HSummary
CVE-2024-1522 is a high-severity CSRF (CWE-352) vulnerability in Lollms Lollms Web Ui. 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 37th 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 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.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-17270
Vulnerability Data
A Cross-Site Request Forgery (CSRF) vulnerability in the parisneo/lollms-webui project allows remote attackers to execute arbitrary code on a victim's system. The vulnerability stems from the `/execute_code` API endpoint, which does not properly validate requests, enabling an attacker to craft…
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a malicious webpage that, when visited by a victim, submits a form to the victim's local lollms-webui instance to execute arbitrary OS commands. This issue allows attackers to take full control of the victim's system without requiring direct network access to the vulnerable application.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- The parisneo/lollms-webui is a web user interface for interacting with large language models (LLMs), functioning as an AI assistant platform, which aligns with Enterprise AI Assistants category. The vulnerability is a CSRF in its API endpoint, confirmed AI-related via AI/ML bug bounty platform.
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.