CVE-2026-41276
Published: 23 April 2026
Summary
CVE-2026-41276 is a critical-severity Improper Authentication (CWE-287) vulnerability in Flowiseai Flowise. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 38.2% of CVEs by exploit likelihood; 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.
The strongest mitigations our analysis identified are NIST 800-53 IA-5 (Authenticator Management) and SI-10 (Information Input Validation).
Threat & Defense at a Glance
Threat & Defense Details
Mitigating Controls (NIST 800-53 r5)AI
Directly mitigates the CVE by requiring timely remediation of the password reset flaw through patching to version 3.1.0 or equivalent fixes.
Requires validation of the reset token input at the /api/v1/account/reset-password endpoint to reject null or empty values that enable unauthorized password resets.
Ensures proper generation, distribution, and validation of password reset tokens as authenticators, preventing bypass via unverified null or empty tokens.
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
The vulnerability enables unauthenticated exploitation of a public-facing web application API endpoint (T1190) to bypass authentication and perform account takeover by resetting passwords, facilitating the use of valid accounts (T1078).
NVD Description
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, this vulnerability allows remote attackers to bypass authentication on affected installations of FlowiseAI Flowise. Authentication is not required to exploit this…
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vulnerability. The specific flaw exists within the resetPassword method of the AccountService class. There is no check performed to ensure that a password reset token has actually been generated for a user account. By default the value of the reset token stored in a users account is null, or an empty string if they've reset their password before. An attacker with knowledge of the user's email address can submit a request to the "/api/v1/account/reset-password" endpoint containing a null or empty string reset token value and reset that user's password to a value of their choosing. This vulnerability is fixed in 3.1.0.
Deeper analysisAI
CVE-2026-41276 is an authentication bypass vulnerability affecting FlowiseAI Flowise, an open-source drag-and-drop user interface for building customized large language model flows, in versions prior to 3.1.0. The flaw resides in the resetPassword method of the AccountService class, where no validation occurs to confirm that a password reset token has been generated for the target user account. By default, the reset token value stored in user accounts is null or an empty string, particularly if the user has previously reset their password.
Remote attackers can exploit this vulnerability without authentication by knowing only the target user's email address. They submit a request to the /api/v1/account/reset-password endpoint with a null or empty string as the reset token value, allowing them to overwrite the user's password with one of their choosing. This enables full account takeover, granting attackers high confidentiality, integrity, and availability impacts as reflected in the CVSS v3.1 base score of 9.8 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H), linked to CWE-287 (Improper Authentication).
The GitHub security advisory (GHSA-f6hc-c5jr-878p) confirms the issue is resolved in Flowise version 3.1.0, recommending that users upgrade immediately to mitigate the risk. No additional workarounds are specified in the provided references.
Flowise's role in constructing LLM-based workflows introduces AI/ML relevance, as compromised instances could potentially allow attackers to manipulate or exfiltrate custom model flows. No evidence of real-world exploitation is noted in the available details.
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: large language model