Raw vector
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2024-1520 is a critical-severity OS Command Injection (CWE-78) vulnerability in Lollms Lollms Web Ui. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); ranked in the top 1% of CVEs by exploit likelihood; 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 SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — 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.
An OS Command Injection vulnerability exists in the '/open_code_folder' endpoint of the parisneo/lollms-webui application. The flaw stems from insufficient validation of user-supplied input in the 'discussion_id' parameter and is tracked as CWE-78. It carries a CVSS 3.0 score of 9.8, reflecting network-accessible exploitation with no required authentication or user interaction.
Unauthenticated remote attackers can supply crafted values to the endpoint that inject and execute arbitrary operating-system commands. Successful exploitation grants the ability to read or modify data, escalate privileges, or achieve full control of the underlying host.
A fix addressing the input-handling issue was merged in commit 2497d1a4fe5a09f003bf7a9bc426139e9295a934 of the upstream repository. The associated huntr.dev report provides additional technical detail on the vulnerable code path. The EPSS score has remained essentially flat near 0.11 with no material post-disclosure increase.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-17268
Vulnerability Data
An OS Command Injection vulnerability exists in the '/open_code_folder' endpoint of the parisneo/lollms-webui application, due to improper validation of user-supplied input in the 'discussion_id' parameter. Attackers can exploit this vulnerability by injecting malicious OS commands, leading to unauthorized command execution…
more
on the underlying operating system. This could result in unauthorized access, data leakage, or complete system compromise.
- 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 vulnerability affects parisneo/lollms-webui, a web UI platform for large language models (LLMs) and multimodal models, enabling AI assistants and agents, categorized under Enterprise AI Assistants. Reported on an AI/ML bug bounty platform (huntr.com).
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.2.5V1.2.8V15.2.5
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect command sanitization during development.
Input validation directly neutralizes or rejects special characters that would otherwise alter OS command structure.
Least privilege reduces the permissions available to any process that could be subverted by injected commands.
Least functionality restricts available OS commands and interpreters, limiting the blast radius of injection.
Secure engineering principles require proper neutralization of untrusted input before command construction.
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.
PR.PS-06's SDLC practices directly require secure coding and input handling that blocks command-injection defects, yet the single broad outcome leaves many specific neutralization vectors and verification gaps unaddressed.
Routine patching/maintenance can remediate known command-injection CVEs in dependencies (partial forward) but does nothing to stop developers from introducing improper neutralization in custom code (none reverse).
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.
Security testing and code review target insecure use of operating-system command interfaces, catching command-injection flaws introduced during development.