GCD AI RADAR
incidents/AIR-2024-0217

CVE-2024-0765: AnythingLLM Data Exfiltration Vulnerability

Attack on AI2 Disclosed vulnerabilityInfrastructure vulnerabilityData leak

An unauthorized data exfiltration vulnerability was discovered in AnythingLLM affecting the system's export endpoint. Patches or mitigations require reviewing access permissions for multi-user instances.

disclosed CVENo confirmed exploitation, so this record is tracked as a disclosed vulnerability and not counted as an incident. It moves into the counts if CISA or the vendor confirms exploitation. Why

Details

type
Attack on AI
An AI model, agent or AI-powered product was the thing exploited, abused or leaked.
categories
  • Infrastructure vulnerabilityprimary
    CVEs and advisories in AI frameworks, inference servers, MCP servers, AI developer tools and hosting stacks.
  • Data leak
    Training data, chat logs, system prompts, model weights or other AI-system data exposed.
owasp llm top 10
mitre atlas
no technique for these categories
Both rows are derived from the type and categories (OWASP 2025 edition, ATLAS release 2026.09), not classified per record. How
severity
2 · Disclosed vulnerability
CVE or vendor advisory, patched or patchable, no confirmed exploitation.
targets
Framework / tooling
products
AnythingLLM
incident date
3 Mar 2024
first reported
3 Mar 2024
origin
NVD
Vulnerability record from NVD / the GitHub Advisory Database. This product uses the NVD API but is not endorsed or certified by the NVD.
classifier confidence
0.95 · published at or above 0.80; see the methodology
tags
CVE-2024-0765 · data-exfiltration
record
created 2026-10-18 10:04Z · updated 2026-10-18 10:04Z · json

Sources · 1

  1. 2024-03-03
    CVE-2024-0765: As a default user on a multi-user instance of AnythingLLM, you could execute a call to the `/export-data` endpoint of the system…
    NVD · nvd.nist.gov/vuln/detail/CVE-2024-0765

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