CVE-2024-6040
Published: 01 August 2024
Summary
CVE-2024-6040 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 17.6th 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 Other Platforms; in the Other ATLAS/OWASP Terms risk domain; MITRE ATLAS techniques in scope: AI Supply Chain Compromise (AML.T0010), External Harms (AML.T0048).
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-47198
Vulnerability details
In parisneo/lollms-webui version v9.8, the lollms_binding_infos is missing the client_id parameter, which leads to multiple security vulnerabilities. Specifically, the endpoints /reload_binding, /install_binding, /reinstall_binding, /unInstall_binding, /set_active_binding_settings, and /update_binding_settings are susceptible to CSRF attacks and local attacks. An attacker can exploit this…
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vulnerability to perform unauthorized actions on the victim's machine.
- 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
- lollms-webui is a web user interface platform for managing and deploying Large Language Models (LLMs), including bindings for various inference backends, fitting as an 'Other Platforms' category for AI web UIs.
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Missing client_id parameter enables CSRF on web endpoints for unauthorized binding management (install/reload/update/etc.), facilitating exploitation of a public-facing web application.
MITRE ATLAS TechniquesAI
MITRE ATLAS techniques
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Awareness training educates users on avoiding untrusted links and actions that can be exploited via CSRF.
Requiring user re-entry of credentials for sensitive actions prevents automated forgery of requests without active user participation.
Security testing regimens explicitly include checks for missing or ineffective anti-CSRF protections in web applications.
Detects anomalous request patterns consistent with cross-site request forgery.