CVE-2026-104334 in Langflow OSS
Summary
by MITRE • 10/07/2026
IBM Langflow OSS 1.0.0 through 1.12.2 could allow a remote attacker to execute arbitrary code due to improper control of code generation.
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Analysis
by VulDB Data Team • 10/07/2026
The vulnerability identified in IBM Langflow versions 1.0.0 through 1.12.2 represents a critical security flaw rooted in the application's handling of dynamic content and template rendering processes. As an open-source framework designed for building large language model applications, Langflow facilitates the creation of complex workflows by allowing users to define logic that interacts with various AI models and data sources. The core issue lies in how the system generates code or executes instructions derived from user inputs without sufficient sanitization or validation mechanisms. This improper control over code generation creates a pathway for remote attackers to inject malicious payloads into the application's execution environment, effectively bypassing intended security boundaries.
From a technical perspective, this vulnerability is classified under CWE-94, which describes Improper Control of Generation of Code (Code Injection). The flaw typically manifests when user-supplied data is directly incorporated into code strings or script blocks that are subsequently executed by the underlying runtime engine. In the context of Langflow, this could occur through maliciously crafted workflow configurations, prompt templates, or component inputs that trigger unintended execution paths within the Python-based backend. An attacker can exploit this weakness to achieve arbitrary command execution on the server hosting the application, potentially leading to full system compromise if the service runs with elevated privileges or has access to sensitive internal resources.
The operational impact of such a vulnerability is severe and multifaceted. Successful exploitation allows an unauthenticated remote attacker to execute arbitrary commands on the host operating system, which can result in data exfiltration, modification of critical application files, or the establishment of persistent backdoors for further lateral movement within the network infrastructure. Since Langflow is often deployed as part of larger AI-driven ecosystems that may have access to proprietary datasets or sensitive customer information, a breach could lead to significant confidentiality and integrity losses. Furthermore, attackers might leverage this foothold to pivot into other connected systems, amplifying the scope of the incident beyond the initial application boundary.
This type of vulnerability aligns with several tactics in the MITRE ATT&CK framework, particularly those related to Initial Access via Exploitation of Remote Services and Execution through Command Line Interface or Scripting Interpreter mechanisms like T1059. The lack of strict input validation and output encoding exemplifies a failure in secure coding practices that are essential for modern web applications interacting with dynamic content generation engines. Organizations relying on Langflow must recognize that the convenience of low-code development does not negate the need for rigorous security controls around user inputs, especially when those inputs influence backend logic execution.
To mitigate this risk, immediate action is required to upgrade IBM Langflow to a version newer than 1.12.2 where these code generation flaws have been addressed by the vendor through enhanced input sanitization and stricter separation of data from executable code. In environments where upgrading is not immediately feasible, administrators should implement network-level controls such as web application firewalls configured to detect common injection patterns in request parameters related to workflow definitions or prompt inputs. Additionally, deploying Langflow within isolated containers with restricted system privileges can limit the blast radius of a potential compromise, ensuring that even if code execution occurs, it does not grant access to critical host resources or sensitive data stores. Regular security audits and static application security testing should be integrated into the development lifecycle to identify similar vulnerabilities in custom components before deployment.