Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:L/A:HSummary
CVE-2024-2288 is a high-severity CSRF (CWE-352) vulnerability in Lollms Lollms Web Ui. Its CVSS base score is 8.3 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 17th 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-2024-27243
Vulnerability Data
A Cross-Site Request Forgery (CSRF) vulnerability exists in the profile picture upload functionality of the Lollms application, specifically in the parisneo/lollms-webui repository, affecting versions up to 7.3.0. This vulnerability allows attackers to change a victim's profile picture without their consent,…
more
potentially leading to a denial of service by overloading the filesystem with files. Additionally, this flaw can be exploited to perform a stored cross-site scripting (XSS) attack, enabling attackers to execute arbitrary JavaScript in the context of the victim's browser session. The issue is resolved in version 9.3.
- 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 (parisneo/lollms-webui) is a web UI platform for running and interacting with Large Language Models (LLMs) locally, making it an AI-related platform. The vulnerability is in its profile upload feature, but the software falls under AI platforms.
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.