Raw vector
CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2026-41279 is a high-severity Authorization Bypass Through User-Controlled Key (CWE-639) vulnerability in Flowiseai Flowise. Its CVSS base score is 8.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 18th 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 LLM Application Platforms; in the Privacy and Disclosure risk domain.
The strongest mitigations our analysis identified map to AC-24 (Access Control Decisions) and AC-3 (Access Enforcement) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2026-41279 is a vulnerability in Flowise, an open-source drag-and-drop user interface for building customized large language model (LLM) flows, affecting versions prior to 3.1.0. The issue lies in the text-to-speech generation endpoint (POST /api/v1/text-to-speech/generate), which is whitelisted and accessible without authentication. This endpoint accepts a credentialId directly in the request body; when invoked without a chatflowId, it uses the supplied credentialId to decrypt stored credentials—such as OpenAI or ElevenLabs API keys—and generates speech accordingly. The vulnerability is classified under CWE-639 (Authorization Bypass Through User-Controlled Key) with a CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H).
Any unauthenticated attacker with network access can exploit this vulnerability by sending a POST request to the endpoint, providing a valid credentialId from the target's Flowise instance and omitting the chatflowId parameter. Successful exploitation decrypts and leverages the victim's stored API credentials to generate text-to-speech audio, enabling unauthorized consumption of third-party TTS services. This can result in high-impact availability disruption, such as API quota exhaustion, excessive compute usage, or billing overages for the Flowise administrator.
The vulnerability was addressed in Flowise version 3.1.0. Additional details on the issue, including patch information, are available in the GitHub Security Advisory at https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-5fw2-mwhh-9947.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-25298
Vulnerability Data
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the text-to-speech generation endpoint (POST /api/v1/text-to-speech/generate) is whitelisted (no auth) and accepts a credentialId directly in the request body. When called…
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without a chatflowId, the endpoint uses the provided credentialId to decrypt the stored credential (e.g., OpenAI or ElevenLabs API key) and generate speech. This vulnerability is fixed in 3.1.0.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Privacy and Disclosure
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: flowise, large language model, openai
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Enforcing approved authorizations on every access request structurally stops a user-controlled key from reaching another user's data.
Requiring explicit access-control decisions on each request blocks unauthorized key-driven access.
Least-privilege restrictions limit the scope of data reachable even if a key check is bypassed.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Enforcing authorization policy and least privilege directly blocks user-controlled key tampering that bypasses access checks.
Logical access controls prevent unauthorized data access that results from missing authorization checks on object references.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing can detect missing authorization checks but does not prevent the weakness in production.
Information access restriction explicitly enforces that users may only retrieve data they are authorized to see, directly addressing user-controlled key bypass.
Access control policy directly requires enforcement of authorization rules that prevent unauthorized access via manipulated keys.
Managing access rights includes ensuring users can only access their own records and not bypass authorization by altering identifiers.
Privileged access rights control restricts what data each user may access, mitigating direct object reference attacks.
Secure development lifecycle includes authorization design but does not itself implement runtime access checks.