CVE-2026-42456 (GCVE-0-2026-42456)
Vulnerability from cvelistv5 – Published: 2026-05-08 23:01 – Updated: 2026-05-11 15:54
VLAI
EPSS
VEX
Title
AnythingLLM: Cross-User TTS Audio Disclosure via Chat ID (IDOR)
Summary
AnythingLLM is an application that turns pieces of content into context that any LLM can use as references during chatting. Prior to version 1.12.1, GET /api/workspace/:slug/tts/:chatId in AnythingLLM returns the text-to-speech audio for another user's chat response within the same workspace because the route validates workspace membership but does not enforce ownership of the targeted chat row. As a result, an authenticated user can access another user's private assistant response in audio form if the chatId is known or guessed. This constitutes an insecure direct object reference (IDOR) affecting private chat response content exposed through the TTS endpoint. This issue has been patched in version 1.12.1.
Severity
4.3 (Medium)
SSVC
Exploitation: poc
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-05-11 15:54 UTC
CWE
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/Mintplex-Labs/anything-llm/sec… | x_refsource_CONFIRM |
| https://github.com/Mintplex-Labs/anything-llm/com… | x_refsource_MISC |
| https://github.com/Mintplex-Labs/anything-llm/rel… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Mintplex-Labs | anything-llm |
Affected:
< 1.12.1
|
guessed |
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
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The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.