CVE-2026-78571 in Langflow
Summary
by MITRE • 09/11/2026
IBM Langflow OSS 1.0.0 through 1.11.5 could allow a remote authenticated attacker to execute arbitrary code due to an unguarded eval() call on attacker-controlled input.
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Analysis
by VulDB Data Team • 09/11/2026
The vulnerability identified in IBM Langflow versions 1.0.0 through 1.11.5 represents a critical security flaw stemming from the improper handling of user-supplied data within the application's core processing logic. Specifically, the software utilizes an unguarded eval() function to interpret strings that are derived directly or indirectly from attacker-controlled inputs. In many web-based frameworks and low-code platforms like Langflow, which facilitate the construction of AI-driven applications through visual interfaces, there is often a mechanism for users to define custom expressions, scripts, or dynamic configurations. When these mechanisms fail to adequately sanitize or restrict the input before passing it to an execution engine such as Python's eval(), they create a direct pathway for Remote Code Execution (RCE). This flaw allows any authenticated user who has access to the application interface to inject malicious code snippets that are then executed with the privileges of the underlying server process.
From a technical perspective, this vulnerability is classified under CWE-95, commonly known as Improper Neutralization of Directives in Dynamically Evaluated Code or eval(). The root cause lies in the architectural decision to allow dynamic evaluation of user-provided strings without sufficient validation against dangerous function calls or attribute access. In Python, the eval() function parses and evaluates a string as if it were a valid Python expression. If an attacker can control this input, they are not limited to simple data manipulation but can invoke system-level commands, read sensitive files from the server's filesystem, exfiltrate database credentials, or establish reverse shells back to their own infrastructure. The severity of this issue is compounded by the fact that it requires authentication, which might lead administrators to underestimate its risk compared to unauthenticated vulnerabilities, yet authenticated RCE remains a high-severity threat in enterprise environments where insider threats or compromised accounts are plausible vectors for exploitation.
The operational impact of this vulnerability extends beyond immediate system compromise to include significant risks related to data integrity and confidentiality. An attacker leveraging this flaw could potentially gain full control over the host environment running Langflow, depending on the permissions assigned to the application process. This could lead to the theft of sensitive AI models, training datasets, or proprietary logic embedded within the flows created by users. Furthermore, because Langflow is often used in development and testing environments that may be connected to production databases or internal networks, a compromised instance can serve as a pivot point for lateral movement within an organization's infrastructure. The attacker could also modify existing flows to introduce backdoors or alter AI model outputs, thereby undermining the trustworthiness of any downstream applications relying on Langflow-generated insights.
To mitigate this risk, organizations running IBM Langflow must immediately upgrade to version 1.12.0 or later, where the vendor has addressed the unsafe evaluation practices by implementing stricter input validation and potentially replacing dynamic execution with safer alternatives such as restricted AST (Abstract Syntax Tree) parsing or sandboxed environments that limit access to dangerous modules like os, subprocess, and sys. In addition to patching, administrators should enforce strict role-based access controls to ensure that only trusted personnel can create flows involving custom code blocks. Network segmentation strategies should also be reviewed to isolate Langflow instances from critical production assets, limiting the blast radius in case of a successful exploitation attempt. Monitoring for unusual outbound network connections or high CPU usage indicative of cryptomining or data exfiltration scripts is recommended as an interim defensive measure until patches are applied. This vulnerability aligns with MITRE ATT&CK technique T1059, Command and Scripting Interpreter, specifically highlighting the danger of allowing user input to influence script execution contexts without adequate safeguards.