CVE-2026-32617
Published: 16 March 2026
Summary
CVE-2026-32617 is a high-severity Permissive Cross-domain Security Policy with Untrusted Domains (CWE-942) vulnerability in Mintplexlabs Anythingllm. Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique External Remote Services (T1133); ranked at the 6.4th 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 Other AI Platforms.
Threat & Defense at a Glance
Threat & Defense Details
Likely Mitigating ControlsAI
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.
Requires documented secure initialization practices and avoidance of insecure defaults in configuration baselines.
Reviewing and updating baseline when components are installed or upgraded prevents initialization with insecure defaults.
Requiring explicit configuration to minimal functionality overrides insecure defaults that would otherwise enable excess capabilities.
Tailoring replaces or augments insecure default initializations with system-specific values and compensating controls before deployment.
Central configuration overrides or replaces insecure default initializations that would otherwise be left unchanged on each system.
SCRM practices during acquisition and configuration management address insecure default initializations shipped by vendors.
Scans detect resources initialized with insecure defaults that create exploitable conditions.
Instruction on secure initialization of security controls prevents leaving resources with insecure defaults after installation.
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Insecure default configuration (no auth on all HTTP/WebSocket endpoints + permissive CORS) directly enables initial access by exploiting the exposed AnythingLLM service or application without credentials.
NVD Description
AnythingLLM is an application that turns pieces of content into context that any LLM can use as references during chatting. In 1.11.1 and earlier, On default installations where no password or API key has been configured, all HTTP endpoints and…
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the agent WebSocket lack authentication, and the server's CORS policy accepts any origin. AnythingLLM Desktop binds to 127.0.0.1 (loopback) by default. Modern browsers (Chrome, Edge, Firefox) implement Private Network Access (PNA). This explicitly blocks public websites from making requests to local IP addresses. Exploitation is only viable from within the same local network (LAN) due to browser-level blocking of public-to-private requests.
Deeper analysisAI
CVE-2026-32617 is a vulnerability in AnythingLLM, an application that converts content into context for large language models (LLMs) during chats. It affects versions 1.11.1 and earlier, specifically default installations where no password or API key is configured. In these setups, all HTTP endpoints and the agent WebSocket lack authentication, while the server's CORS policy permits requests from any origin. The AnythingLLM Desktop edition binds to 127.0.0.1 (loopback) by default. The issue is classified under CWE-942 (Permissive Cross-domain Policy with Untrusted Domains) and CWE-1188 (Implementation of a web server with an insecure default configuration), with a CVSS v3.1 base score of 7.1 (AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:L).
Exploitation requires an attacker to be on the same local network (LAN), as modern browsers (Chrome, Edge, Firefox) enforce Private Network Access (PNA), blocking public websites from accessing local IP addresses. An attacker with network access but no privileges can leverage the lack of authentication and permissive CORS, though it demands high attack complexity and user interaction. Successful exploitation enables high confidentiality and integrity impacts, such as unauthorized access to or modification of LLM context data, with low availability impact.
The GitHub security advisory provides details on mitigation: https://github.com/Mintplex-Labs/anything-llm/security/advisories/GHSA-24qj-pw4h-3jmm. Published on 2026-03-16, no real-world exploitation or additional AI/ML-specific context is noted in available information.
Details
- CWE(s)
Affected Products
AI Security AnalysisAI
- AI Category
- Other AI Platforms
- Risk Domain
- N/A
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: llm