CVE-2025-30714 Overview
CVE-2025-30714 is an Improper Access Control vulnerability in the MySQL Connectors product of Oracle MySQL, specifically affecting the Connector/Python component. This vulnerability allows a low-privileged attacker with network access to potentially gain unauthorized access to critical data or complete access to all MySQL Connectors accessible data.
The vulnerability is classified as difficult to exploit due to high attack complexity requirements and the necessity for human interaction from a person other than the attacker. However, successful exploitation could lead to significant confidentiality impacts, enabling attackers to access sensitive database connection information and credentials managed by the Python connector.
Critical Impact
Successful exploitation can result in unauthorized access to critical data or complete access to all MySQL Connectors accessible data, potentially exposing database credentials and sensitive connection information.
Affected Products
- Oracle MySQL Connectors (Connector/Python) versions 9.0.0 through 9.2.0
Discovery Timeline
- 2025-04-15 - CVE-2025-30714 published to NVD
- 2025-04-21 - Last updated in NVD database
Technical Details for CVE-2025-30714
Vulnerability Analysis
This vulnerability is classified under CWE-284 (Improper Access Control), indicating that the MySQL Connector/Python component fails to properly restrict access to sensitive resources or functionality. The attack requires network access via multiple protocols and specifically targets the Python database connector library used by applications to communicate with MySQL databases.
The nature of this vulnerability suggests that under specific circumstances, an attacker with low-level privileges could manipulate or intercept connector operations to gain unauthorized access to data. The requirement for human interaction indicates that social engineering or user-initiated actions may be necessary to trigger the vulnerable code path.
Root Cause
The root cause stems from improper access control mechanisms within the Connector/Python component. CWE-284 vulnerabilities typically occur when software does not properly enforce restrictions on which actors can perform certain operations, access certain data, or call certain functions. In this case, the connector fails to adequately validate or restrict access under certain conditions, potentially exposing sensitive database connection data.
Attack Vector
The attack is network-based and can be conducted via multiple protocols. An attacker would need:
- Low-level privileges on the target system or network
- Network access to the vulnerable MySQL Connector/Python instance
- A victim to perform specific actions (human interaction required)
The difficulty of exploitation is high due to the complex conditions required for successful attack execution. The attacker must position themselves appropriately in the network and engineer a scenario where the victim triggers the vulnerable functionality.
The vulnerability mechanism involves improper validation of access control policies within the connector's data handling routines. When certain conditions are met, particularly those requiring human interaction, the connector may expose sensitive data to unauthorized actors. Technical implementation details are available in the Oracle Security Alert April 2025.
Detection Methods for CVE-2025-30714
Indicators of Compromise
- Unusual network traffic patterns to MySQL database servers from connector instances
- Unexpected authentication attempts or access to database connection configurations
- Anomalous data access patterns from applications using MySQL Connector/Python
- Log entries showing access attempts from unauthorized or unexpected sources
Detection Strategies
- Monitor MySQL Connector/Python version deployments across your infrastructure using software inventory tools
- Implement network traffic analysis to detect unusual communication patterns between application servers and MySQL databases
- Review application logs for unexpected connector behavior or authentication anomalies
- Deploy endpoint detection and response (EDR) solutions to identify suspicious process activity related to Python MySQL connections
Monitoring Recommendations
- Enable verbose logging for MySQL Connector/Python in staging environments to understand baseline behavior
- Configure SIEM alerts for unusual database access patterns originating from Python applications
- Monitor for unexpected changes to connector configuration files or connection strings
- Track authentication events and access control failures in database audit logs
How to Mitigate CVE-2025-30714
Immediate Actions Required
- Identify all systems running Oracle MySQL Connector/Python versions 9.0.0 through 9.2.0
- Plan and schedule upgrades to a patched version as soon as available from Oracle
- Review and restrict network access to systems using the vulnerable connector
- Implement additional access controls and monitoring for database connections
Patch Information
Oracle has released security updates to address this vulnerability as part of the April 2025 Critical Patch Update. Organizations should upgrade to a patched version of MySQL Connector/Python as specified in the Oracle security advisory. Review the official Oracle documentation for the specific patched version number and upgrade procedures.
Workarounds
- Restrict network access to systems running vulnerable Connector/Python versions using firewall rules
- Implement network segmentation to isolate database connector traffic
- Apply the principle of least privilege to accounts using the MySQL connector
- Monitor and audit all database connection activities until patches can be applied
# Configuration example: Restrict network access to MySQL connector instances
# Add firewall rules to limit connector communication to known database servers only
iptables -A OUTPUT -p tcp --dport 3306 -d trusted_mysql_server_ip -j ACCEPT
iptables -A OUTPUT -p tcp --dport 3306 -j DROP
# Verify installed connector version
pip show mysql-connector-python | grep Version
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.


