CVE-2024-6959
CSRF in Lollms Web Ui 9.8
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:HSummary
CVE-2024-6959 is a high-severity CSRF (CWE-352) vulnerability in Lollms Lollms Web Ui. Its CVSS base score is 7.1 (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; 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-2024-47945
Vulnerability Data
A vulnerability in parisneo/lollms-webui version 9.8 allows for a Denial of Service (DOS) attack when uploading an audio file. If an attacker appends a large number of characters to the end of a multipart boundary, the system will continuously process…
more
each character, rendering lollms-webui inaccessible. This issue is exacerbated by the lack of Cross-Site Request Forgery (CSRF) protection, enabling remote exploitation. The vulnerability leads to service disruption, resource exhaustion, and extended downtime.
- 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
- lollms-webui is an open-source web user interface for running, managing, and interacting with large language models (LLMs) and multimodal AI systems locally, fitting as an other AI platform.
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
—
—
—
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.