CVE-2026-31829
Published: 10 March 2026
Summary
CVE-2026-31829 is a high-severity SSRF (CWE-918) vulnerability in Flowiseai Flowise. Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 18.9% 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 Supply Chain and Deployment risk domain.
The strongest mitigations our analysis identified are NIST 800-53 AC-4 (Information Flow Enforcement) and SC-7 (Boundary Protection).
Deeper analysis
CVE-2026-31829 is a Server-Side Request Forgery (SSRF) vulnerability, classified under CWE-918, affecting Flowise versions prior to 3.0.13. Flowise is a drag-and-drop user interface for building customized large language model (LLM) flows. The issue stems from an HTTP Node exposed in AgentFlow and Chatflow components, which performs server-side HTTP requests to user-controlled URLs without restrictions on target hosts. This includes private/internal IP ranges (RFC 1918), localhost, and cloud metadata endpoints, enabling attackers to trick the server into accessing resources not reachable from the public internet. The vulnerability carries a CVSS v3.1 base score of 7.1 (AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:L).
Any user interacting with a publicly exposed chatflow can exploit this vulnerability by supplying malicious URLs, requiring low privileges (PR:L) but high attack complexity (AC:H) with no user interaction needed beyond normal usage. Successful exploitation allows attackers to force the Flowise server to make unauthorized requests to internal network resources, potentially leading to high confidentiality and integrity impacts (C:H/I:H) such as data exfiltration from internal services, along with low availability impact (A:L).
The official advisory on GitHub (GHSA-fvcw-9w9r-pxc7) confirms the vulnerability is fixed in Flowise version 3.0.13, recommending immediate upgrades to mitigate the SSRF risk. No additional workarounds are specified in the provided details.
Flowise's focus on LLM flows introduces AI/ML relevance, as exploited instances could compromise internal data used in model training or inference pipelines. No real-world exploitation has been reported in the available information.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-10930
Vulnerability details
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.0.13, Flowise exposes an HTTP Node in AgentFlow and Chatflow that performs server-side HTTP requests using user-controlled URLs. By default, there are…
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no restrictions on target hosts, including private/internal IP ranges (RFC 1918), localhost, or cloud metadata endpoints. This enables Server-Side Request Forgery (SSRF), allowing any user interacting with a publicly exposed chatflow to force the Flowise server to make requests to internal network resources that are inaccessible from the public internet. This vulnerability is fixed in 3.0.13.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: flowise, large language model
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
SSRF in public-facing Flowise chatflow/AgentFlow directly matches T1190 Exploit Public-Facing Application; explicit support for cloud metadata endpoints enables T1552.005 credential theft via instance metadata API.
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Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces policy-based restrictions on server-initiated outbound flows to user-supplied URLs, blocking SSRF to RFC 1918, localhost, and metadata endpoints.
Implements boundary protection mechanisms that deny the Flowise HTTP Node from reaching internal/private IP ranges from externally reachable chatflows.
Requires validation of URL inputs to the HTTP Node so that only explicitly allowed external hosts are accepted, mitigating the uncontrolled SSRF vector.