CVE-2026-24477: CWE-201: Insertion of Sensitive Information Into Sent Data in Mintplex-Labs anything-llm
AnythingLLM is an application that turns pieces of content into context that any LLM can use as references during chatting. If AnythingLLM prior to version 1.10.0 is configured to use Qdrant as the vector database with an API key, this QdrantApiKey could be exposed in plain text to unauthenticated users via the `/api/setup-complete` endpoint. Leakage of QdrantApiKey allows an unauthenticated attacker full read/write access to the Qdrant vector database instance used by AnythingLLM. Since Qdrant often stores the core knowledge base for RAG in AnythingLLM, this can lead to complete compromise of the semantic search / retrieval functionality and indirect leakage of confidential uploaded documents. Version 1.10.0 patches the issue.
AI Analysis
Technical Summary
CVE-2026-24477 is a vulnerability in Mintplex-Labs' AnythingLLM application prior to version 1.10.0. When configured to use Qdrant as the vector database with an API key, the QdrantApiKey is exposed in plain text to unauthenticated users via the /api/setup-complete endpoint. This exposure allows attackers to gain full read and write access to the Qdrant vector database instance, which often contains the core knowledge base for retrieval-augmented generation (RAG) in AnythingLLM. The vulnerability is classified under CWE-201 (Insertion of Sensitive Information Into Sent Data). The issue is patched in version 1.10.0.
Potential Impact
An unauthenticated attacker can obtain the Qdrant API key, enabling full read and write access to the Qdrant vector database used by AnythingLLM. This can lead to complete compromise of the semantic search and retrieval functionality and indirect leakage of confidential uploaded documents stored in the database. The vulnerability has a CVSS 4.0 score of 8.7, indicating high severity.
Mitigation Recommendations
Upgrade AnythingLLM to version 1.10.0 or later, where this vulnerability is patched. Since this is an application-level vulnerability, applying the official fix is the recommended remediation. There is no indication that temporary mitigations or workarounds are available or recommended.
CVE-2026-24477: CWE-201: Insertion of Sensitive Information Into Sent Data in Mintplex-Labs anything-llm
Description
AnythingLLM is an application that turns pieces of content into context that any LLM can use as references during chatting. If AnythingLLM prior to version 1.10.0 is configured to use Qdrant as the vector database with an API key, this QdrantApiKey could be exposed in plain text to unauthenticated users via the `/api/setup-complete` endpoint. Leakage of QdrantApiKey allows an unauthenticated attacker full read/write access to the Qdrant vector database instance used by AnythingLLM. Since Qdrant often stores the core knowledge base for RAG in AnythingLLM, this can lead to complete compromise of the semantic search / retrieval functionality and indirect leakage of confidential uploaded documents. Version 1.10.0 patches the issue.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-24477 is a vulnerability in Mintplex-Labs' AnythingLLM application prior to version 1.10.0. When configured to use Qdrant as the vector database with an API key, the QdrantApiKey is exposed in plain text to unauthenticated users via the /api/setup-complete endpoint. This exposure allows attackers to gain full read and write access to the Qdrant vector database instance, which often contains the core knowledge base for retrieval-augmented generation (RAG) in AnythingLLM. The vulnerability is classified under CWE-201 (Insertion of Sensitive Information Into Sent Data). The issue is patched in version 1.10.0.
Potential Impact
An unauthenticated attacker can obtain the Qdrant API key, enabling full read and write access to the Qdrant vector database used by AnythingLLM. This can lead to complete compromise of the semantic search and retrieval functionality and indirect leakage of confidential uploaded documents stored in the database. The vulnerability has a CVSS 4.0 score of 8.7, indicating high severity.
Mitigation Recommendations
Upgrade AnythingLLM to version 1.10.0 or later, where this vulnerability is patched. Since this is an application-level vulnerability, applying the official fix is the recommended remediation. There is no indication that temporary mitigations or workarounds are available or recommended.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- GitHub_M
- Date Reserved
- 2026-01-23T00:38:20.547Z
- Cvss Version
- 4.0
- State
- PUBLISHED
Threat ID: 6977fa5c4623b1157cc21c6c
Added to database: 1/26/2026, 11:35:56 PM
Last enriched: 4/4/2026, 5:58:00 AM
Last updated: 5/10/2026, 2:07:06 PM
Views: 364
Community Reviews
0 reviewsCrowdsource mitigation strategies, share intel context, and vote on the most helpful responses. Sign in to add your voice and help keep defenders ahead.
Want to contribute mitigation steps or threat intel context? Sign in or create an account to join the community discussion.
Actions
Updates to AI analysis require Pro Console access. Upgrade inside Console → Billing.
External Links
Need more coverage?
Upgrade to Pro Console for AI refresh and higher limits.
For incident response and remediation, OffSeq services can help resolve threats faster.
Latest Threats
Check if your credentials are on the dark web
Instant breach scanning across billions of leaked records. Free tier available.