CVE-2024-4897
Lollms Web Ui ≤ 9.8
Raw vector
CVSS:3.0/AV:L/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2024-4897 is a high-severity Improper Neutralization of Equivalent Special Elements (CWE-76) vulnerability in Lollms Lollms Web Ui. Its CVSS base score is 8.4 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); 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 Supply Chain and Deployment 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.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-44465
Vulnerability Data
parisneo/lollms-webui, in its latest version, is vulnerable to remote code execution due to an insecure dependency on llama-cpp-python version llama_cpp_python-0.2.61+cpuavx2-cp311-cp311-manylinux_2_31_x86_64. The vulnerability arises from the application's 'binding_zoo' feature, which allows attackers to upload and interact with a malicious model file…
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hosted on hugging-face, leading to remote code execution. The issue is linked to a known vulnerability in llama-cpp-python, CVE-2024-34359, which has not been patched in lollms-webui as of commit b454f40a. The vulnerability is exploitable through the application's handling of model files in the 'bindings_zoo' feature, specifically when processing gguf format model files.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- lollms-webui is a web UI platform for running and interacting with large language models (LLMs) like those using llama-cpp-python, fitting as an 'Other Platforms' category for AI/ML web interfaces and deployment tools.
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
SA-11 requires developer testing and evaluation that can discover failures to neutralize equivalent special elements.
SI-10 requires validation of information inputs, directly stopping incomplete neutralization of equivalent special elements.
SA-8 mandates security engineering principles such as complete input validation and sanitization that cover equivalent special-element forms.
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 consistent neutralization of all equivalent special elements during input validation and sanitization.
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 can detect incomplete neutralization but does not prevent the weakness itself.
Secure development life cycle mandates input validation and neutralization of all equivalent special elements.
Application security requirements include rules for handling special characters and equivalent encodings.
Secure system architecture principles require consistent canonicalization and neutralization of equivalent inputs.
Secure coding standards directly address proper neutralization of all equivalent special elements.