CVE-2026-13435 in Langflow
Summary
by MITRE • 07/30/2026
IBM Langflow OSS 1.0.0 through 1.10.1 contains an improper input validation vulnerability in the PythonREPL sandbox implementation.
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Analysis
by VulDB Data Team • 07/30/2026
The vulnerability under discussion affects IBM Langflow Open Source Software versions 1.0.0 through 1.10.1, specifically within the PythonREPL sandbox implementation where improper input validation occurs. This flaw resides in the sandboxing mechanism designed to isolate and control Python code execution, which is a critical security component for preventing unauthorized access to system resources and maintaining operational integrity. The vulnerability represents a significant risk as it undermines the fundamental security assumptions of the sandbox environment that should prevent malicious code from accessing sensitive system functions or data.
The technical flaw manifests in the validation mechanisms that process user inputs intended for execution within the PythonREPL environment. When users provide input to be executed, the system fails to properly validate or sanitize these inputs before allowing execution, potentially permitting code injection attacks. This weakness allows attackers to craft malicious inputs that bypass sandbox restrictions and execute arbitrary commands with elevated privileges. The vulnerability can be classified under CWE-20 which encompasses Improper Input Validation, a category that represents one of the most common and dangerous classes of security flaws in software applications.
Operationally, this vulnerability creates substantial risk for organizations deploying IBM Langflow as part of their AI or machine learning workflows. Attackers exploiting this weakness could potentially execute unauthorized code on systems running vulnerable versions, leading to data breaches, system compromise, or privilege escalation attacks. The impact extends beyond simple code execution as the sandbox environment is typically designed to provide isolation from critical system components and network resources. This vulnerability essentially removes that isolation layer, exposing underlying infrastructure to potential compromise.
Organizations utilizing IBM Langflow should immediately implement mitigation strategies including updating to patched versions of the software where available, applying input sanitization measures at the application level, and implementing additional network segmentation controls. The ATT&CK framework categorizes this type of vulnerability under T1059.001 for Command and Scripting Interpreter with Python, highlighting how adversaries can leverage such flaws to establish persistent access or escalate privileges. Security teams should also consider implementing runtime monitoring and anomaly detection systems to identify potential exploitation attempts, particularly focusing on unusual command execution patterns that might indicate sandbox bypass activities.
The root cause of this vulnerability demonstrates the complexity involved in creating secure sandboxing mechanisms for interpreted languages like Python where dynamic code evaluation inherently presents security challenges. Proper input validation requires not only checking for known malicious patterns but also understanding the execution context and ensuring that user inputs cannot alter the intended behavior of the sandbox environment. This particular flaw underscores the importance of comprehensive security testing including fuzzing and penetration testing specifically targeting sandbox implementations to identify such critical design flaws before they can be exploited in production environments.