CVE-2025-0185 in dify
Summary
by MITRE • 03/20/2025
A vulnerability in the Dify Tools' Vanna module of the langgenius/dify repository allows for a Pandas Query Injection in the latest version. The vulnerability occurs in the function `vn.get_training_plan_generic(df_information_schema)`, which does not properly sanitize user inputs before executing queries using the Pandas library. This can potentially lead to Remote Code Execution (RCE) if exploited.
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Analysis
by VulDB Data Team • 03/21/2025
The vulnerability identified as CVE-2025-0185 resides within the Dify Tools' Vanna module of the langgenius/dify repository, representing a critical security flaw that could enable attackers to execute arbitrary code on affected systems. This issue specifically manifests in the `vn.get_training_plan_generic(df_information_schema)` function where user-provided inputs are inadequately sanitized before being processed within Pandas query operations. The affected component operates as part of a larger language generation platform that leverages database schema information to construct training plans, making it a potential entry point for sophisticated attacks targeting the underlying data processing infrastructure.
The technical exploitation of this vulnerability stems from improper input validation mechanisms within the Vanna module's query processing pipeline. When the `get_training_plan_generic` function receives database information schema data, it directly incorporates user-supplied parameters into Pandas query constructs without adequate sanitization or parameterization. This design flaw creates a classic query injection vulnerability that can be leveraged to manipulate the underlying data processing operations. The Pandas library's query execution capabilities, when combined with unsanitized inputs, provide attackers with pathways to execute malicious code within the application's runtime environment, potentially leading to complete system compromise.
The operational impact of this vulnerability extends beyond simple data manipulation to encompass full system compromise through remote code execution capabilities. An attacker who successfully exploits this vulnerability could gain unauthorized access to the application server, potentially accessing sensitive data, modifying database contents, or establishing persistent backdoors within the system. The implications are particularly severe given that this vulnerability exists in a module designed for processing database schema information, which typically contains sensitive structural data about the underlying database systems. This makes the attack surface particularly attractive to threat actors seeking to escalate privileges or extract valuable information from the target environment.
Mitigation strategies for CVE-2025-0185 should prioritize immediate input sanitization and parameterization of all database queries within the Vanna module. Security teams should implement strict input validation mechanisms that prevent malicious payloads from being processed through the `get_training_plan_generic` function, ensuring that all user inputs are properly escaped or parameterized before being incorporated into Pandas operations. Additionally, the implementation of principle of least privilege access controls should be enforced to limit the potential damage from successful exploitation attempts. The vulnerability aligns with CWE-94, which describes improper control of generation of code, and represents a clear violation of secure coding practices that should be addressed through comprehensive code review processes and automated security testing protocols. Organizations should also consider implementing network segmentation and monitoring solutions to detect potential exploitation attempts and establish incident response procedures to address any successful breach attempts. This vulnerability demonstrates the critical importance of secure data processing practices in AI and machine learning platforms where database interactions are common and potentially dangerous if not properly secured.