CVE-2026-0771 in Langflow
Summary
by MITRE • 01/23/2026
Langflow PythonFunction Code Injection Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Langflow. Attack vectors and exploitability will vary depending on the configuration of the product.
The specific flaw exists within the handling of Python function components. Depending upon product configuration, an attacker may be able to introduce custom Python code into a workflow. An attacker can leverage this vulnerability to execute code in the context of the application. Was ZDI-CAN-27497.
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Analysis
by VulDB Data Team • 01/25/2026
The CVE-2026-0771 vulnerability represents a critical code injection flaw within the Langflow platform that enables remote attackers to execute arbitrary code on affected systems. This vulnerability specifically targets the PythonFunction component handling mechanism, which serves as a core functionality for executing custom Python code within workflow processes. The issue stems from insufficient input validation and sanitization when processing Python function components, creating a pathway for malicious actors to inject and execute unauthorized code within the application's execution context. The vulnerability's severity is amplified by its remote exploitability, meaning attackers do not require local system access to leverage the flaw, making it particularly dangerous in networked environments where Langflow instances may be exposed to untrusted users or external networks.
The technical implementation of this vulnerability resides in the improper handling of user-supplied Python code within the workflow engine's PythonFunction components. When Langflow processes workflow definitions containing PythonFunction nodes, the system fails to adequately sanitize or validate the code provided by users, allowing for the injection of malicious Python code that can be executed within the application's runtime environment. This code injection occurs during the workflow processing phase, where the platform directly evaluates and executes the provided Python code without sufficient security controls. The vulnerability's exploitation potential varies significantly based on the application's configuration and deployment model, as different setups may provide varying levels of access control and execution restrictions. According to CWE classification, this vulnerability maps to CWE-94: Improper Control of Generation of Code ('Code Injection'), which specifically addresses situations where untrusted data is used to generate executable code without proper validation or sanitization.
The operational impact of CVE-2026-0771 extends beyond simple remote code execution, as successful exploitation can lead to complete system compromise and unauthorized access to sensitive data. Attackers can leverage this vulnerability to establish persistent backdoors, escalate privileges, or exfiltrate information from affected systems. The vulnerability's presence in the workflow processing engine means that any user with access to create or modify workflow components could potentially exploit this flaw, making it particularly dangerous in collaborative environments where multiple users have workflow editing capabilities. This vulnerability aligns with ATT&CK technique T1059.006: Command and Scripting Interpreter: Python, which describes how adversaries use Python to execute malicious code and maintain persistence. The threat landscape for this vulnerability is further complicated by the fact that Langflow is often deployed in enterprise environments where it may have elevated privileges and access to sensitive systems, making successful exploitation potentially catastrophic for organizations.
Mitigation strategies for CVE-2026-0771 should focus on immediate patching of affected systems and implementation of strict input validation controls. Organizations should ensure that all Langflow installations are updated to versions that address this vulnerability through the vendor's security advisory. In the interim, administrators should implement strict access controls to prevent unauthorized users from creating or modifying workflow components containing PythonFunction nodes. Network segmentation and firewall rules should be implemented to limit access to Langflow instances from untrusted networks. Additionally, input sanitization should be enhanced through the implementation of code validation libraries and sandboxing mechanisms that prevent execution of potentially malicious code. Security monitoring should be enhanced to detect unusual workflow creation patterns or code injection attempts. The vulnerability also highlights the importance of following secure coding practices and implementing proper input validation as outlined in OWASP Top Ten and NIST Cybersecurity Framework guidelines. Organizations should conduct comprehensive security assessments of their workflow environments and implement principle of least privilege access controls to minimize the potential impact of similar vulnerabilities in the future.