Cyber Resilience

CVE-2024-3149

HighPublic PoC

Published: 06 June 2024

Published
06 June 2024
Modified
21 November 2024
KEV Added
—
Patch
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CVSS Score v3.1 8.8 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
EPSS Score 0.0013 32.4th percentile
Risk Priority 18 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2024-3149 is a high-severity SSRF (CWE-918) vulnerability in Mintplexlabs Anythingllm. Its CVSS base score is 8.8 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Data from Local System (T1005); ranked at the 32.4th 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 Other ATLAS/OWASP Terms risk domain; MITRE ATLAS techniques in scope: Discover AI Model Ontology (AML.T0013), AML.T0038, AI Model Inference API Access (AML.T0040).

EU & UK References

Vulnerability details

A Server-Side Request Forgery (SSRF) vulnerability exists in the upload link feature of mintplex-labs/anything-llm. This feature, intended for users with manager or admin roles, processes uploaded links through an internal Collector API using a headless browser. An attacker can exploit…

more

this by hosting a malicious website and using it to perform actions such as internal port scanning, accessing internal web applications not exposed externally, and interacting with the Collector API. This interaction can lead to unauthorized actions such as arbitrary file deletion and limited Local File Inclusion (LFI), including accessing NGINX access logs which may contain sensitive information.

CWE(s)
CWE-918

AI Security AnalysisAI

AI Category
Enterprise AI Assistants
Risk Domain
Other ATLAS/OWASP Terms
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
mintplex-labs/anything-llm is an open-source full-stack LLM application for document chatting and AI workflows, classified as an Enterprise AI Assistant platform. The vulnerability is in its upload link feature using a Collector API.

Related Threats

MITRE ATT&CK Enterprise TechniquesAI

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.
attack.mitre.org →
T1046 Network Service Discovery Discovery
Adversaries may attempt to get a listing of services running on remote hosts and local network infrastructure devices, including those that may be vulnerable to remote software exploitation.
attack.mitre.org →
T1070.004 File Deletion Stealth
Adversaries may delete files left behind by the actions of their intrusion activity.
attack.mitre.org →
Why these techniques?

SSRF allows internal port scanning (T1046), LFI for accessing local files like NGINX logs (T1005), and arbitrary file deletion via Collector API (T1070.004).

MITRE ATLAS TechniquesAI

MITRE ATLAS techniques

AML.T0013: Discover AI Model OntologyAML.T0038AML.T0040: AI Model Inference API AccessAML.T0048: External Harms

Affected Assets

mintplexlabs
anythingllm
≤ 1.0.0

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.

CA-8 Penetration Testing
addresses: CWE-918

Penetration testing attempts server-side requests to internal resources, identifying SSRF weaknesses for remediation.

SC-7 Boundary Protection
addresses: CWE-918

Outbound connections to external resources can be monitored and limited at the boundary, reducing SSRF impact.

SI-10 Information Input Validation
addresses: CWE-918

Validates server-side URLs and resource references to block SSRF attempts.

SI-4 System Monitoring
addresses: CWE-918

Detects server-side request forgery through monitoring of unexpected outbound connections.

References