CVE-2026-8446 in Langflow OSS
Summary
by MITRE • 08/05/2026
IBM Langflow OSS 1.0.0 through 1.10.3 contain an authentication bypass vulnerability in the Model Context Protocol (MCP) composer endpoint when mcp_composer_enabled=true (default) and projects are configured with auth_type=oauth .
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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 where an authentication bypass occurs in the Model Context Protocol MCP composer endpoint. The flaw manifests when the mcp_composer_enabled parameter is set to true, which represents the default configuration setting, combined with projects that utilize auth_type=oauth for authentication mechanisms. The vulnerability stems from insufficient authorization checks within the MCP composer endpoint that fails to properly validate user credentials before granting access to sensitive functionality. This authentication bypass allows unauthorized actors to potentially access and manipulate model composition features without proper authentication, undermining the security controls designed to protect these resources.
The technical implementation of this vulnerability can be categorized under CWE-287 which addresses improper authentication issues in software systems. The root cause lies in the failure to properly enforce authentication requirements within the MCP composer endpoint when specific configuration parameters are present. Attackers exploiting this vulnerability could potentially access project configurations, modify model compositions, and execute unauthorized operations through the compromised endpoint. This represents a critical security flaw that directly impacts the integrity and confidentiality of the system's model composition capabilities.
The operational impact of this vulnerability extends beyond simple unauthorized access as it enables potential attackers to manipulate the core model composition functionality within the Langflow platform. When projects are configured with oauth authentication, the expectation is that proper authorization controls would prevent unauthorized modifications to the model context protocol composer. However, the flaw allows attackers to bypass these controls entirely, potentially leading to data manipulation, model poisoning, or unauthorized access to sensitive AI model configurations. The default enablement of mcp_composer_enabled creates a widespread exposure surface across installations where administrators may not be aware of this specific vulnerability.
Organizations using IBM Langflow OSS within this affected version range should immediately implement mitigations to address this authentication bypass vulnerability. The primary recommendation involves disabling the MCP composer endpoint when it is not actively required for operations, which can be achieved by setting mcp_composer_enabled=false in configuration files. Additionally, administrators should review all project configurations to ensure that oauth authentication is properly enforced and consider implementing additional network-level access controls to restrict exposure of the affected endpoint. Security teams should monitor for unusual activity patterns in model composition endpoints and implement proper logging and alerting mechanisms to detect potential exploitation attempts.
This vulnerability aligns with several tactics described in the MITRE ATT&CK framework, particularly those related to credential access and privilege escalation. The authentication bypass represents a technique that allows adversaries to gain unauthorized access to system resources without proper credentials, potentially enabling further exploitation through lateral movement or data exfiltration activities. Organizations should consider implementing network segmentation strategies to isolate critical AI model composition endpoints and apply principle of least privilege configurations to minimize the potential impact of successful exploitation attempts. The vulnerability also highlights the importance of proper configuration management within open source software deployments where default settings may create unintended security exposure points that require careful monitoring and control.