Critical AnythingLLM Vulnerability Exposes Systems to Remote Code Execution

A critical security flaw (CVE-2024-13059) in the open-source AI framework AnythingLLM has raised alarms across cybersecurity communities.

The vulnerability, discovered in February 2025, allows attackers with administrative privileges to execute malicious code remotely, potentially compromising entire systems.

Detail	Description
CVE ID	CVE-2024-13059
Severity	Critical (CVSS 9.1)
EPSS Score	0.04% (Low exploitation probability)
Affected Versions	AnythingLLM versions < 1.3.1
Patched Version	1.3.1 (released February 10, 2025)
Impact	Remote Code Execution (RCE) via path traversal

Vulnerability Breakdown

According to the Offsec report, the flaw originates from improper filename sanitization in the multer library, used by AnythingLLM for file uploads.

Non-ASCII filenames containing directory traversal sequences (e.g., ../../malicious.sh) are not properly validated, enabling attackers to write files to unintended locations.

The exploitation process begins when an attacker with manager or admin access to a vulnerable AnythingLLM instance crafts a malicious file containing directory traversal sequences in its filename (e.g., ../../malicious.js).

Due to improper sanitization of non-ASCII filenames in the multer library, the application fails to detect these sequences.

When the file is uploaded via AnythingLLM’s interface, the server mistakenly writes it to unintended locations outside the restricted upload directory.

For example, a file named ../../../etc/cron.d/exploit could be placed in a system directory responsible for scheduling automated tasks.

If the file is executed—either through scheduled jobs, startup scripts, or other mechanisms—it enables full remote code execution (RCE), granting the attacker control over the compromised system.

This attack vector highlights how elevated privileges and insufficient input validation combine to turn a simple file upload into a critical system breach.

Organizations using AnythingLLM for AI-driven workflows, such as customer support automation or internal data analysis—are urged to act swiftly.

Delayed patching could lead to data breaches, service disruptions, or unauthorized access to sensitive infrastructure.

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