Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:HSummary
CVE-2026-40933 is a critical-severity OS Command Injection (CWE-78) vulnerability in Flowiseai Flowise. Its CVSS base score is 9.9 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); ranked in the top 4% 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 LLM Application Platforms; in the LLM/Generative AI Risks risk domain.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — 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-2026-40933 is an OS command injection vulnerability (CWE-78) affecting Flowise, an open-source drag-and-drop user interface for building customized large language model (LLM) flows. The issue resides in the MCP adapter's unsafe serialization of stdio commands, specifically within the "Custom MCP" configuration accessible at http://localhost:3000/canvas in versions prior to 3.1.0. Despite input sanitization checks such as validateCommandInjection, validateArgsForLocalFileAccess, and a list of predefined safe commands, attackers can bypass these by combining commands like "npx" with execution arguments, such as "npx -c touch /tmp/pwn".
An authenticated attacker with low privileges (PR:L) can exploit this over the network (AV:N) with low complexity (AC:L) and no user interaction (UI:N). By adding a new MCP stdio server, they inject arbitrary commands, achieving remote code execution (RCE) on the underlying operating system. The vulnerability's CVSS v3.1 base score of 9.9 reflects its critical severity, with high impacts on confidentiality, integrity, and availability (C:H/I:H/A:H) and a changed scope (S:C).
The Flowise security advisory (GHSA-c9gw-hvqq-f33r) confirms the vulnerability is fixed in version 3.1.0. Additional context from OX Security advisories highlights this as part of broader MCP supply-chain risks across the AI ecosystem, including systemic vulnerabilities in MCP implementations.
This issue is particularly relevant to AI/ML deployments, as Flowise enables LLM workflow orchestration, potentially exposing production AI systems to supply-chain compromise. No public evidence of real-world exploitation is noted in the provided references.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-24489
Vulnerability Data
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, due to unsafe serialization of stdio commands in the MCP adapter, an authenticated attacker can add an MCP stdio server with…
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an arbitrary command, achieving command execution. The vulnerability lies in a bug in the input sanitization from the “Custom MCP” configuration in http://localhost:3000/canvas - where any user can add a new MCP, when doing so - adding a new MCP using stdio, the user can add any command, even though your code have input sanitization checks such as validateCommandInjection and validateArgsForLocalFileAccess, and a list of predefined specific safe commands - these commands, for example "npx" can be combined with code execution arguments ("-c touch /tmp/pwn") that enable direct code execution on the underlying OS. This vulnerability is fixed in 3.1.0.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- LLM/Generative AI Risks
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: flowise, large language model, mcp
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.2.5V1.2.8V15.2.5
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect command sanitization during development.
Input validation directly neutralizes or rejects special characters that would otherwise alter OS command structure.
Least privilege reduces the permissions available to any process that could be subverted by injected commands.
Least functionality restricts available OS commands and interpreters, limiting the blast radius of injection.
Secure engineering principles require proper neutralization of untrusted input before command construction.
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.
PR.PS-06's SDLC practices directly require secure coding and input handling that blocks command-injection defects, yet the single broad outcome leaves many specific neutralization vectors and verification gaps unaddressed.
Routine patching/maintenance can remediate known command-injection CVEs in dependencies (partial forward) but does nothing to stop developers from introducing improper neutralization in custom code (none reverse).
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 and code review target insecure use of operating-system command interfaces, catching command-injection flaws introduced during development.