CVE-2026-91935: Server-Side Request Forgery (SSRF) in FlowiseAI Flowise
Flowise before 3.1.4 fails to validate baseURL parameters in chat-model nodes, allowing authenticated users to redirect requests to arbitrary hosts. Attackers with chatflows:create or chatflows:update permissions can exfiltrate LLM provider API keys by redirecting requests to cloud metadata services or internal hosts.
AI Analysis
Technical Summary
FlowiseAI Flowise versions prior to 3.1.4 contain an SSRF vulnerability due to failure to validate baseURL parameters in chat-model nodes. Authenticated users who have chatflows:create or chatflows:update permissions can exploit this vulnerability to redirect requests to arbitrary hosts. This redirection can be leveraged to exfiltrate LLM provider API keys by targeting cloud metadata services or internal hosts. The vulnerability has a CVSS 3.1 score of 8.3, indicating high severity with network attack vector, low attack complexity, and requiring privileges but no user interaction.
Potential Impact
Successful exploitation allows attackers with limited authenticated permissions to perform SSRF attacks, potentially exposing sensitive API keys and internal resources. This compromises confidentiality and integrity of the system and may lead to further unauthorized access or data leakage.
Mitigation Recommendations
A fix is available in Flowise version 3.1.4. Users should upgrade to version 3.1.4 or later to remediate this vulnerability. No additional mitigations are specified in the provided data.
CVE-2026-91935: Server-Side Request Forgery (SSRF) in FlowiseAI Flowise
Description
Flowise before 3.1.4 fails to validate baseURL parameters in chat-model nodes, allowing authenticated users to redirect requests to arbitrary hosts. Attackers with chatflows:create or chatflows:update permissions can exfiltrate LLM provider API keys by redirecting requests to cloud metadata services or internal hosts.
CVSS v3.1
Score 8.3high
Affected software
FlowiseAI
Flowise
pkg:github/flowiseai/FlowiseRun on your own infrastructure? Check whether these packages are installed with threat-finder — our free open-source scanner.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
FlowiseAI Flowise versions prior to 3.1.4 contain an SSRF vulnerability due to failure to validate baseURL parameters in chat-model nodes. Authenticated users who have chatflows:create or chatflows:update permissions can exploit this vulnerability to redirect requests to arbitrary hosts. This redirection can be leveraged to exfiltrate LLM provider API keys by targeting cloud metadata services or internal hosts. The vulnerability has a CVSS 3.1 score of 8.3, indicating high severity with network attack vector, low attack complexity, and requiring privileges but no user interaction.
Potential Impact
Successful exploitation allows attackers with limited authenticated permissions to perform SSRF attacks, potentially exposing sensitive API keys and internal resources. This compromises confidentiality and integrity of the system and may lead to further unauthorized access or data leakage.
Mitigation Recommendations
A fix is available in Flowise version 3.1.4. Users should upgrade to version 3.1.4 or later to remediate this vulnerability. No additional mitigations are specified in the provided data.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- VulnCheck
- Date Reserved
- 2026-09-15T11:06:02.263Z
- Cvss Version
- 3.1
- State
- PUBLISHED
Threat ID: 6aa9651855bf5e2cf502eafd
Added to database: 09/15/2026, 15:32:40 UTC
Last enriched: 09/15/2026, 16:02:01 UTC
Last updated: 09/16/2026, 02:32:06 UTC
Views: 9
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