CVE-2026-17632 in Langflow OSS
Summary
by MITRE • 08/05/2026
IBM Langflow OSS 1.0.0 through 1.10.3 could allow a remote authenticated attacker to execute arbitrary code due to improper validation of Python code during AST-based security scanning.
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Analysis
by VulDB Data Team • 08/05/2026
This vulnerability exists within IBM Langflow Open Source Software versions 1.0.0 through 1.10.3, representing a critical security flaw that enables remote authenticated attackers to execute arbitrary code on affected systems. The vulnerability stems from insufficient validation mechanisms during AST-based security scanning processes where Python code is improperly evaluated and processed without adequate sanitization measures. The flaw occurs when the application performs static analysis on user-provided Python code through Abstract Syntax Tree parsing, failing to properly validate or sanitize the input before execution. This vulnerability aligns with CWE-94, which describes improper validation of code during interpretation or compilation phases, specifically within the context of AST-based security scanning mechanisms. The attack vector requires an authenticated user with sufficient privileges to submit malicious Python code through the Langflow interface, which then gets processed through the vulnerable security scanning module.
The operational impact of this vulnerability is severe as it allows attackers to escalate their privileges and potentially gain complete control over the affected system. When authenticated users submit specially crafted Python code that bypasses the AST validation checks, the system executes this malicious code with the privileges of the Langflow application itself. This creates a pathway for privilege escalation, data exfiltration, system compromise, and potential lateral movement within network environments where Langflow is deployed. The vulnerability affects organizations using Langflow in production environments where user authentication is required, making it particularly dangerous in enterprise settings where multiple users interact with the platform. Attackers could leverage this weakness to establish persistent backdoors, modify system configurations, or access sensitive data processed through the Langflow workflows.
From a cybersecurity perspective, this vulnerability demonstrates the importance of proper input validation and code sanitization within security scanning tools, particularly those performing AST-based analysis. The flaw represents a classic example of insufficient sandboxing or code isolation during static analysis processes, where the security tool itself becomes a vector for code execution attacks rather than a protective mechanism. Organizations should consider implementing additional security controls such as network segmentation, monitoring for unusual code execution patterns, and regular vulnerability assessments targeting their Langflow deployments. The ATT&CK framework categorizes this as a privilege escalation technique through malicious code injection, where the attacker leverages existing authenticated sessions to execute unauthorized commands. Security teams must also ensure that automated scanning tools do not inadvertently create attack surfaces by failing to properly isolate or validate code inputs during analysis phases.
Mitigation strategies should include immediate deployment of patches provided by IBM for affected versions, implementation of network-based restrictions to limit access to Langflow interfaces, and enhanced monitoring of code submission activities within the system. Organizations should also consider implementing additional authentication layers, such as multi-factor authentication, to reduce the attack surface available to potential adversaries. Regular security assessments should be conducted to identify similar vulnerabilities in other AST-based tools or security scanning mechanisms within the organization's infrastructure. The vulnerability highlights the necessity of maintaining up-to-date security practices and proper code validation procedures in all components that process user-provided inputs, particularly those used in security-sensitive contexts where code execution capabilities are involved.