CVE-2026-7700 in langflow
Summary
by MITRE • 05/03/2026
A weakness has been identified in langflow-ai langflow up to 1.8.4. This affects the function eval of the file src/lfx/src/lfx/components/llm_operations/lambda_filter.p of the component LambdaFilterComponent. Executing a manipulation can lead to code injection. The attack may be performed from remote. The exploit has been made available to the public and could be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way.
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Analysis
by VulDB Data Team • 10/06/2026
The vulnerability identified in langflow-ai langflow version 1.8.4 and earlier represents a critical code injection flaw within the LambdaFilterComponent functionality. This weakness exists in the eval function implementation located at src/lfx/src/lfx/components/llm_operations/lambda_filter.p, where user-supplied input is processed without proper sanitization or validation mechanisms. The vulnerability stems from the dangerous use of the eval() function which directly executes arbitrary code passed as string arguments, creating an inherent risk that allows attackers to manipulate the execution flow of the application.
The technical nature of this flaw aligns with common software security vulnerabilities categorized under CWE-94, which describes "Improper Control of Generation of Code ('Code Injection')" and specifically relates to CWE-74, "Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection')." The vulnerability operates at the application layer where legitimate input is transformed into executable code, creating a pathway for malicious actors to inject arbitrary commands or code that will be executed within the context of the running application. This particular implementation flaw allows for remote exploitation since the vulnerable function can be accessed through network interfaces without requiring local system access.
The operational impact of this vulnerability is severe and potentially devastating for any organization utilizing affected versions of langflow-ai. Attackers who successfully exploit this code injection vulnerability could gain full control over the affected system, execute arbitrary commands, access sensitive data, modify system configurations, or establish persistent backdoors. The public availability of exploits significantly increases the risk profile since it removes the need for advanced technical skills to perform attacks, making this vulnerability particularly dangerous in environments where the application is exposed to untrusted inputs or external networks. The lack of vendor response to early disclosure attempts further compounds the risk as organizations have no assurance of receiving timely patches or mitigations.
Organizations using affected versions of langflow-ai should immediately implement comprehensive mitigations including immediate patching to version 1.8.5 or later, which presumably addresses this vulnerability through proper input validation and sanitization mechanisms. Network segmentation and firewall rules should be implemented to restrict access to the vulnerable components, while input validation should be enforced at all entry points to prevent malicious payloads from reaching the eval function. Additionally, monitoring and logging of all lambda filter operations should be enabled to detect potential exploitation attempts. The ATT&CK framework categorizes this type of vulnerability under T1059 "Command and Scripting Interpreter" and T1203 "Exploitation for Client Execution," with the specific technique of code injection being a primary method for attackers to achieve initial access and privilege escalation within compromised environments. Regular security assessments should include verification of input handling mechanisms and testing of code evaluation functions to prevent similar vulnerabilities from being introduced in future development cycles.