CVE-2026-41271
Published: 23 April 2026
Summary
CVE-2026-41271 is a high-severity SSRF (CWE-918) vulnerability in Flowiseai Flowise. Its CVSS base score is 8.3 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 27.2th 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; in the Privacy and Disclosure risk domain.
The strongest mitigations our analysis identified are NIST 800-53 AC-4 (Information Flow Enforcement) and SI-10 (Information Input Validation).
Threat & Defense at a Glance
Threat & Defense Details
Mitigating Controls (NIST 800-53 r5)AI
Validates information inputs to POST/GET API Chain components to block malicious prompt templates that trigger SSRF requests.
Enforces approved information flow control policies to restrict server-initiated HTTP requests to only authorized internal and external destinations, preventing SSRF exploitation.
Monitors and controls communications at system boundaries to block or detect unauthorized outbound HTTP requests to internal services induced by SSRF.
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
SSRF vulnerability in public-facing web application (Flowise) directly enables T1190 for initial exploitation; facilitates internal reconnaissance via T1018 (Remote System Discovery) and T1046 (Network Service Discovery) by allowing arbitrary HTTP requests to internal systems.
NVD Description
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, a Server-Side Request Forgery (SSRF) vulnerability exists in FlowiseAI's POST/GET API Chain components that allows unauthenticated attackers to force the server…
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to make arbitrary HTTP requests to internal and external systems. By injecting malicious prompt templates, attackers can bypass the intended API documentation constraints and redirect requests to sensitive internal services, potentially leading to internal network reconnaissance and data exfiltration. This vulnerability is fixed in 3.1.0.
Deeper analysisAI
CVE-2026-41271 is a Server-Side Request Forgery (SSRF) vulnerability (CWE-918) affecting Flowise, an open-source drag-and-drop user interface for building customized large language model (LLM) flows. The issue resides in the POST/GET API Chain components in versions prior to 3.1.0, allowing attackers to force the server to initiate unintended HTTP requests. Published on 2026-04-23, it carries a CVSS v3.1 base score of 8.3 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:L), rated High severity due to its potential for high confidentiality and integrity impact.
Unauthenticated attackers can exploit the vulnerability by injecting malicious prompt templates into the API Chain components, bypassing intended API documentation constraints. This enables redirection of server requests to arbitrary internal and external systems, facilitating internal network reconnaissance and potential data exfiltration from sensitive services.
The vulnerability is addressed in Flowise version 3.1.0. Advisories recommend upgrading to this patched release to mitigate the SSRF risk. Additional details are available in the GitHub security advisory at https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-6r77-hqx7-7vw8.
Details
- CWE(s)
Affected Products
AI Security AnalysisAI
- AI Category
- Other AI Platforms
- Risk Domain
- Privacy and Disclosure
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: large language model