GCD AI RADAR
incidents/AIR-2025-0315

CVE-2025-6211: LlamaIndex vulnerable to data loss via MD5 hash collisions

Attack on AI2 Disclosed vulnerabilityInfrastructure vulnerability

The DocugamiReader class in LlamaIndex uses MD5 hashing for document chunks, causing collisions and data overwrites. The issue has been addressed in updated releases.

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 vulnerability
    CVEs and advisories in AI frameworks, inference servers, MCP servers, AI developer tools and hosting stacks.
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
LlamaIndex
incident date
10 Jul 2025
first reported
10 Jul 2025
origin
GitHub Advisory Database
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-2025-6211 · hash-collision
record
created 2026-10-18 07:00Z · updated 2026-10-18 07:00Z · json

Sources · 1

  1. 2025-07-10
    CVE-2025-6211: LlamaIndex vulnerable to data loss through hash collisions in its DocugamiReader class
    GitHub Advisory Database · github.com/advisories/GHSA-5hq9-5r78-2gjh

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