CVE-2026-9081 IBM CVE debrief

Who should care

Organizations using IBM Langflow OSS 1.0.0 through 1.10.3 should be aware of this SSRF vulnerability and take steps to mitigate it. This includes reviewing and applying patches, implementing input validation and filtering for the OLLAMA_BASE_URL parameter, and monitoring for suspicious requests to prevent potential SSRF attacks. Vulnerability management and security teams should prioritize patching this vulnerability to prevent potential SSRF attacks. Operators and administrators of affected systems should also be aware of this vulnerability and take steps to mitigate it. Additionally, security teams should review compensating controls for exposed systems while remediation is scheduled and verified. They should also check relevant monitoring, detection, and logs for exposed assets that need extra review. Asset inventory and change management processes should be updated to account for this vulnerability. Finally, incident response teams should be prepared to respond to potential SSRF attacks. Security teams should track exceptions, retest remediated assets, and close the item only after evidence is documented. This vulnerability management effort should be integrated into existing security operations and incident response processes. Security teams should also consider implementing additional monitoring and detection controls to identify potential SSRF attacks. They should also review and update their incident response plans to account for this vulnerability. Furthermore, security teams should provide guidance to operators and administrators on how to mitigate this vulnerability and how to respond to potential SSRF attacks. They should also review and update their vulnerability management policies to account for this vulnerability. In addition, security teams should consider implementing compensating controls, such as web application firewalls, to detect and prevent potential SSRF attacks. They should also review and update their security information and event management systems to account for this vulnerability. Finally, security teams should provide training to operators and administrators on how to mitigate this vulnerability and how to respond to potential SSR

Technical summary

IBM Langflow OSS 1.0.0 through 1.10.3 contains a Server-Side Request Forgery (SSRF) vulnerability in the validate_model_provider_key() function for the Ollama provider. The function accepts a user-supplied OLLAMA_BASE_URL parameter and passes it directly to requests.get() without validation, scheme/host allowlisting, or filtering of private IP ranges. This vulnerability can be exploited by an attacker to make unauthorized requests, potentially leading to sensitive information disclosure or other malicious activities. Organizations using IBM Langflow OSS should prioritize patching this vulnerability to prevent potential SSRF attacks.

Defensive priority

Organizations using IBM Langflow OSS should prioritize patching this vulnerability to prevent potential SSRF attacks.

Recommended defensive actions

• Review and apply patches for IBM Langflow OSS 1.0.0 through 1.10.3
• Implement input validation and filtering for the OLLAMA_BASE_URL parameter
• Monitor for suspicious requests to prevent potential SSRF attacks
• Confirm whether affected product deployments exist in managed environments and assign an owner for follow-up
• Review compensating controls for exposed systems while remediation is scheduled and verified
• Check relevant monitoring, detection, and logs for exposed assets that need extra review
• Track exceptions, retest remediated assets, and close the item only after evidence is documented

Evidence notes

The CVE description indicates that IBM Langflow OSS 1.0.0 through 1.10.3 contains a Server-Side Request Forgery (SSRF) vulnerability in the validate_model_provider_key() function for the Ollama provider. The function accepts a user-supplied OLLAMA_BASE_URL parameter and passes it directly to requests.get() without validation, scheme/host allowlisting, or filtering of private IP ranges.

Sources and references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.