CVE-2026-107329 in Langflow OSS
Summary
by MITRE • 10/29/2026
IBM Langflow OSS 1.0.0 through 1.12.4 could allow a remote authenticated attacker to execute arbitrary code due to improper control of code generation.
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Analysis
by VulDB Data Team • 10/29/2026
The vulnerability identified in IBM Langflow versions 1.0.0 through 1.12.4 represents a critical security flaw rooted in the application's handling of dynamic code execution within its orchestration framework. As an open-source tool designed for building and deploying large language model applications, Langflow allows users to construct complex workflows by chaining various components together. The core issue arises from improper control over how these workflow definitions are processed and executed. Specifically, the system fails to adequately sanitize or restrict inputs that lead to code generation mechanisms, creating a pathway for remote authenticated attackers to inject malicious payloads into the execution environment. This flaw is not merely a configuration error but a fundamental architectural weakness in how user-supplied data influences internal script generation logic.
From a technical perspective, this vulnerability aligns with CWE-94 Improper Control of Generation of Code (Code Injection). The attacker leverages their authenticated status to interact with the API or interface that constructs workflow nodes. By manipulating specific parameters within these node configurations, an adversary can trick the underlying engine into generating and executing arbitrary Python code rather than standard operational logic. This is particularly dangerous because Langflow often runs in environments where it has access to system resources necessary for LLM inference and data processing. The injection does not require complex exploitation chains; instead, it relies on the application's trust of authenticated user inputs when compiling workflow scripts into executable formats.
The operational impact of this vulnerability is severe, as successful exploitation results in Remote Code Execution with the privileges of the Langflow service account. An attacker who gains access to a vulnerable instance can execute commands that compromise the integrity and confidentiality of the host system. This could lead to the exfiltration of sensitive data processed by the LLM applications, such as proprietary business logic or personal identifiable information. Furthermore, the compromised server may be used as a pivot point for further attacks within the internal network. The ability to run arbitrary code means that attackers can install backdoors, modify application configurations, or disrupt service availability through resource exhaustion techniques.
This vulnerability maps directly to MITRE ATT&CK technique T1059 Command and Scripting Interpreter, specifically sub-techniques involving Python execution such as T1059.004. The attack vector is classified under Remote Code Execution via Input Manipulation, highlighting the importance of input validation in dynamic application environments. Because Langflow is often deployed in cloud-native or containerized environments, the blast radius can extend beyond a single host if network segmentation policies are not strictly enforced between the Langflow deployment and other critical infrastructure components.
Mitigation strategies must focus on both immediate remediation and long-term architectural hardening. The primary recommendation is to upgrade IBM Langflow to version 1.12.5 or later, where these code generation controls have been strengthened to prevent unauthorized script execution. For organizations unable to patch immediately due to dependency constraints, implementing strict network segmentation is crucial. This involves isolating the Langflow instance from sensitive databases and internal services using firewalls or container networking policies that restrict outbound connections to only those absolutely necessary for operation. Additionally, running the application with minimal privileges ensures that even if code execution occurs, the attacker's ability to impact the broader system is limited. Input validation should also be enforced at the API gateway level where possible, filtering out suspicious patterns in workflow definitions before they reach the Langflow engine. Regular auditing of user permissions and enforcing principle of least privilege for all authenticated users further reduces the attack surface available to potential adversaries seeking to exploit this code injection flaw.