A newly discovered critical security vulnerability tracked as CVE-2025-3248 has been found in Langflow, an open-source platform employed by developers to visually compose AI-driven agents and workflows.
With a formidable CVSS score of 9.8, this remote code execution (RCE) flaw poses significant risks to organizations leveraging Langflow in production environments, particularly those exposing the platform to public or internal networks without adequate protections.
Unrestricted Code Execution Rooted in Insecure Endpoint Design
The flaw resides within the /api/v1/validate/code endpoint, where Langflow’s implementation dangerously invokes Python’s built-in exec() function on untrusted, user-supplied code without any authentication or sandboxing measures.
Specifically, prior to version 1.3.0, the endpoint is designed to validate code by parsing submitted Python function definitions into an abstract syntax tree (AST), importing modules, and then using exec() to process function definitions.
The fundamental risk emerges from Python’s behavior: both decorators and default argument values within function definitions are evaluated immediately during AST processing.
According to the Report, this enables malicious actors to embed harmful payloads directly in decorators or as default arguments, guaranteeing their execution as soon as the endpoint validates the supplied code.
A proof-of-concept attack demonstrates the severity of this vulnerability. An adversary can craft Python source code with a decorator such as @exec("import os; os.system('id > /tmp/pwned')") or inject malicious instructions in default arguments both of which are executed instantly by the vulnerable endpoint.
By sending such code in a POST request to the exposed /api/v1/validate/code API, attackers can achieve unauthenticated remote code execution, resulting in actions such as writing files to the server, deploying backdoors, or retrieving sensitive data.
Immediate Upgrade and Hardened Defenses Recommended
CVE-2025-3248 affects all Langflow versions prior to 1.3.0. The Langflow maintainers have addressed the issue in version 1.3.0 by requiring authentication for access to the /api/v1/validate/code endpoint, thereby significantly reducing the risk of abuse.
Security experts strongly advise immediate upgrades to the latest version.
In addition, organizations are urged to restrict access to internal development tools such as Langflow by deploying architectures like Zero Trust Network Access (ZTNA), for example, through solutions such as Zscaler Private Access, and implementing robust input validation or sandboxing if custom code validation is necessary.
Furthermore, the lack of any visible errors or warnings in the server’s response makes detection of exploitation attempts challenging.
It is crucial for defenders to implement monitoring and anomaly detection around code validation endpoints and to scrutinize outgoing connections from affected servers for signs of compromise.
The disclosure of CVE-2025-3248 underscores the risks inherent in features that execute or validate user-submitted code, especially in cloud- or internet-facing AI development platforms.
The case serves as a stark reminder of the importance of strong authentication, comprehensive input validation, and the avoidance of unsafe dynamic code execution practices.
As organizations continue to embrace platforms like Langflow, adopting secure development and deployment standards becomes vital to defending against such critical vulnerabilities.
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