CVE-2026-7700: Langflow: Prompt injection in Langflow Smart Transform can lead to code execution
Langflow versions 1.3.0 through 1.10.2 contain a code-injection vulnerability in the Smart Transform (LambdaFilterComponent) component.
Smart Transform places flow-author instructions and a preview of its input data into a prompt asking an LLM to generate a Python lambda. It then extracts a one-line lambda from the model response, applies only syntactic format checks, evaluates it with Python’s full builtins, and invokes the resulting function inside the Langflow process.
A malicious flow author can exploit this directly through the Instructions field. In deployments where an exposed flow passes attacker-controlled content into Smart Transform, an attacker may also exploit it indirectly through prompt injection, subject to the configured model following the injected instruction.
References
- github.com/advisories/GHSA-9fpm-3445-2vx4
- github.com/langflow-ai/langflow/commit/1641b28f33e2c47b9a0c6855922d44d1b8418b9d
- github.com/langflow-ai/langflow/commit/94859df33acd70b2a1f816e26d68f5e89a7e5639
- github.com/langflow-ai/langflow/pull/13530
- github.com/langflow-ai/langflow/releases/tag/v1.10.3
- github.com/langflow-ai/langflow/security/advisories/GHSA-9fpm-3445-2vx4
- nvd.nist.gov/vuln/detail/CVE-2026-7700
- vuldb.com/submit/804305
- vuldb.com/vuln/360869
- www.yuque.com/mengnanbulalei/ognlsk/hte2a98ro5gf8tp9?singleDoc
Code Behaviors & Features
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