CVE-2026-37009 in CrewAI
Summary
by MITRE • 08/27/2026
A SQL injection vulnerability in NL2SQLTool in crewai-tools v1.10.2rc1 allows a remote attacker to execute arbitrary SQL commands via an unsanitized sql_query argument.
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Analysis
by VulDB Data Team • 08/27/2026
The identified security flaw resides within the NL2SQLTool component of the crewai-tools library, specifically affecting version 1.10.2rc1 and potentially subsequent releases if not patched. This vulnerability is classified as a SQL injection attack, which corresponds to CWE-89 in the Common Weakness Enumeration standard. The core technical issue stems from the improper neutralization of special elements used in SQL commands within the sql_query argument. When user-supplied input or data derived from natural language processing tasks is passed directly into database queries without adequate sanitization or parameterization, it creates an opening for malicious actors to inject arbitrary SQL code. This lack of proper validation allows attackers to manipulate the intended logic of the query, effectively bypassing security controls and gaining unauthorized access to underlying data structures.
From a technical perspective, the vulnerability exploits the dynamic nature of how natural language processing tools generate database queries. In this context, NL2SQLTool translates human-readable text into SQL statements for execution against a connected database. If the tool fails to properly escape or parameterize inputs before constructing these SQL strings, an attacker can craft specific input sequences that terminate the original query and append new commands. This could involve using standard SQL injection techniques such as appending comments, utilizing UNION-based attacks to extract data from other tables, or employing blind injection methods to infer database structure through boolean-based responses. The severity of this flaw is heightened by its potential for remote exploitation, meaning an attacker does not need local access to the system but can trigger the vulnerability over a network connection if the service exposing NL2SQLTool is accessible externally.
The operational impact of this SQL injection vulnerability is severe and multifaceted. Successful exploitation could lead to unauthorized data disclosure, allowing attackers to read sensitive information stored in the database such as user credentials, personal identifiable information, or proprietary business logic. Beyond data theft, an attacker with sufficient privileges within the database context might modify existing records, leading to data integrity issues that can disrupt business operations and erode trust in system outputs. In more extreme scenarios, depending on the configuration of the underlying Database Management System, SQL injection could potentially lead to remote code execution or denial-of-service conditions by executing commands that consume excessive resources or halt service availability. This aligns with several tactics within the MITRE ATT&CK framework, particularly T1059 Command and Scripting Interpreter for executing injected commands and T1213 Data from Information Repositories for exfiltrating stored data.
To mitigate this vulnerability, immediate action is required to update crewai-tools to a version where the sql_query argument handling has been corrected. Developers should ensure that all dynamic SQL queries are constructed using parameterized statements or prepared statements rather than string concatenation. This approach ensures that user input is treated strictly as data and not as executable code by the database engine. Additionally, implementing strict input validation on both client-side and server-side can help filter out potentially malicious characters before they reach the query construction logic. Principle of least privilege should also be applied to the database account used by the application, ensuring it has only the minimum permissions necessary for its function, thereby limiting the potential damage if an injection attempt is partially successful. Regular security audits and static code analysis tools configured to detect SQL injection patterns can further aid in preventing similar issues in future development cycles.