Cyber Resilience

CVE-2024-4881

HighPublic PoC

Published: 06 June 2024

Published
06 June 2024
Modified
21 November 2024
KEV Added
Patch
CVSS Score v3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
EPSS Score 0.0021 43.8th percentile
Risk Priority 15 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2024-4881 is a high-severity Absolute Path Traversal (CWE-36) vulnerability in Lollms Lollms. Its CVSS base score is 7.5 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 43.8th 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 Enterprise AI Assistants; in the Privacy and Disclosure risk domain; MITRE ATLAS techniques in scope: Adversarial AI Attack Implementations (AML.T0016.000), Invert AI Model (AML.T0024.001), Financial Harm (AML.T0048.000).

EU & UK References

Vulnerability details

A path traversal vulnerability exists in the parisneo/lollms application, affecting version 9.4.0 and potentially earlier versions, but fixed in version 5.9.0. The vulnerability arises due to improper validation of file paths between Windows and Linux environments, allowing attackers to traverse…

more

beyond the intended directory and read any file on the Windows system. Specifically, the application fails to adequately sanitize file paths containing backslashes (`\`), which can be exploited to access the root directory and read, or even delete, sensitive files. This issue was discovered in the context of the `/user_infos` endpoint, where a crafted request using backslashes to reference a file (e.g., `\windows\win.ini`) could result in unauthorized file access. The impact of this vulnerability includes the potential for attackers to access sensitive information such as environment variables, database files, and configuration files, which could lead to further compromise of the system.

CWE(s)

AI Security AnalysisAI

AI Category
Enterprise AI Assistants
Risk Domain
Privacy and Disclosure
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
parisneo/lollms is an AI assistant platform (Lord of Large Language Models WebUI) for interacting with LLMs, fitting the Enterprise AI Assistants category as a deployed application for AI model usage and management.

Related Threats

MITRE ATT&CK Enterprise TechniquesAI

T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
T1005 Data from Local System Collection
Adversaries may search local system sources, such as file systems, configuration files, local databases, virtual machine files, or process memory, to find files of interest and sensitive data prior to Exfiltration.
T1083 File and Directory Discovery Discovery
Adversaries may enumerate files and directories or may search in specific locations of a host or network share for certain information within a file system.
T1070.004 File Deletion Stealth
Adversaries may delete files left behind by the actions of their intrusion activity.
Why these techniques?

Path traversal in public-facing web app (/user_infos endpoint) enables exploitation (T1190), arbitrary file reads for data collection and discovery (T1005, T1083), and potential deletions (T1070.004).

MITRE ATLAS TechniquesAI

MITRE ATLAS techniques

AML.T0016.000: Adversarial AI Attack ImplementationsAML.T0024.001: Invert AI ModelAML.T0048.000: Financial Harm

Affected Assets

lollms
lollms
≤ 5.9.0

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.

addresses: CWE-22

Validates pathnames and filenames to prevent traversal outside intended directories.

References