CVE-2026-7700 langflow-ai CVE debrief

Who should care

Defenders and security teams responsible for systems using langflow-ai langflow up to 1.10.2 should assess their exposure and monitor for potential code injection attempts. This includes reviewing inventory, tracking potential attacks, and applying remediation when available. Security teams should prioritize verifying exposure in their inventory, especially for systems using langflow-ai langflow up to 1.10.2, and monitor for potential code injection. They

Why it matters

CVE-2026-7700 is a code injection vulnerability in langflow-ai langflow up to 1.10.2 that can be exploited remotely. Defenders should verify exposure, monitor for attacks, and apply remediation when available.

• Verify exposure in inventory for langflow-ai langflow up to 1.10.2
• Monitor for potential code injection attempts
• Apply vendor remediation when available

Technical summary

The CVE-2026-7700 vulnerability affects langflow-ai langflow up to 1.10.2, specifically in the LambdaFilterComponent's eval function. This weakness allows for code injection and can be exploited remotely. The exploit has been made public, which could facilitate attacks. The vulnerability is identified in the lambda_filter.py file, and defenders should focus on verifying exposure and monitoring for potential code injection attempts. Official advisories and CVE records should be reviewed for detailed remediation guidance.

Defensive priority

Defenders should prioritize verifying exposure in their inventory, especially for systems using langflow-ai langflow up to 1.10.2, and monitor for potential code injection attempts.

Recommended defensive actions

• Verify inventory for systems using langflow-ai langflow up to 1.10.2
• Monitor for potential code injection attempts
• Review and apply vendor remediation when available
• Track exceptions and retest remediated assets
• Check relevant monitoring, detection, and logs for exposed assets
• Review compensating controls for exposed systems
• Plan vendor-supported updates or mitigations through normal change control

Evidence notes

The CVE record and NVD entry provide initial details on the vulnerability. However, the vendor did not respond to early disclosure, and additional information from other sources is needed for a comprehensive understanding. Further verification is required to understand the full scope of affected versions, exploitation methods, and potential remediation steps.

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.