Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2026-41267 is a high-severity Authorization Bypass Through User-Controlled Key (CWE-639) vulnerability in Flowiseai Flowise. Its CVSS base score is 8.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 26th 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 Other ATLAS/OWASP Terms 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-2026-41267 is an improper mass assignment vulnerability, also described as JSON injection, affecting the account registration endpoint in Flowise Cloud prior to version 3.1.0. Flowise is a drag-and-drop user interface for building customized large language model (LLM) flows. The issue, linked to CWE-639 (Authorization Bypass Through User-Controlled Key) and CWE-915 (Improperly Controlled Modification of Dynamically-Determined Object Attributes), stems from the failure to properly restrict client-supplied input during account creation, allowing injection of server-managed fields and nested objects. It carries a CVSS v3.1 base score of 8.1 (AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H), indicating high severity with network accessibility but high attack complexity.
Unauthenticated attackers can exploit this vulnerability remotely by submitting crafted JSON payloads during the registration process. This enables manipulation of critical server-controlled data, including ownership metadata, timestamps, organization associations, and role mappings. In Flowise Cloud's multi-tenant environment, such control breaks trust boundaries, potentially allowing attackers to escalate privileges, access or alter other users' resources, or disrupt isolation between tenants.
The vulnerability is addressed in Flowise version 3.1.0, as detailed in the GitHub Security Advisory GHSA-48m6-ch88-55mj. Security practitioners should upgrade to the patched version and review access logs for suspicious registration attempts, particularly those involving unexpected field injections.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-25284
Vulnerability Data
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, an improper mass assignment (JSON injection) vulnerability in the account registration endpoint of Flowise Cloud allows unauthenticated attackers to inject server-managed…
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fields and nested objects during account creation. This enables client-controlled manipulation of ownership metadata, timestamps, organization association, and role mappings, breaking trust boundaries in a multi-tenant environment. This vulnerability is fixed in 3.1.0.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: flowise, large language model
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.
Limits the set of modifiable attributes a subject is authorized to touch.
Validates incoming attribute names and values so that only explicitly allowed fields are accepted for update.
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.
Secure SDLC practices directly require allow-listing of mutable object attributes and input validation to block mass-assignment flaws.
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.
Secure coding standards explicitly forbid unsafe dynamic attribute assignment and require property allow-lists.
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.