This vulnerability allows arbitrary file reads in the Kafka Connect BigQuery Connector, an implementation of a sink connector from Apache Kafka to Google BigQuery. The issue arises from the failure to validate externally-sourced credential configurations before they are processed by Google authentication libraries. Attackers may leverage this vulnerability to exploit crafted credential configurations, leading to arbitrary file reads or SSRF attacks.
The CVSS score for this vulnerability is 7.7, classified as high severity. This indicates a significant risk to organizations using affected versions of the connector, where the attack vector is network-based, and the attack complexity is low. Organizations should prioritize patching immediately.
The published date for this advisory is January 16, 2026, with the last modification on January 26, 2026. As the status is currently awaiting analysis, there are no confirmed exploits available in the public domain, but the potential for exploitation remains high.
Organizations utilizing the Kafka Connect BigQuery Connector should assess their configurations and ensure that credential validations are properly implemented to prevent unauthorized access.
Vulnerability Details
Kafka Connect BigQuery Connector is an implementation of a sink connector from Apache Kafka to Google BigQuery. Prior to version 2.11.0, it is susceptible to arbitrary file reads due to improper handling of credential configurations. Aiven's Google BigQuery Kafka Connect Sink connector requires Google Cloud credential configurations for authentication to BigQuery services. During the configuration, users can supply credential JSON files that are processed by Google authentication libraries.
The vulnerability is classified under CWE-73 (External Control of File Name or Path) and CWE-918 (Server-Side Request Forgery). The attack vector is network-based with a low complexity level. The required privileges are low, and no user interaction is needed.
Confidentiality impact is rated as high, indicating that sensitive data may be exposed, while integrity and availability impacts are rated as none.
Technical Analysis
The root cause of this vulnerability lies in the failure of the service to properly validate externally-sourced credential configurations before passing them to the authentication libraries. As a result, an attacker can manipulate credential_source.file paths or credential_source.url endpoints within the credential JSON files.
The attack vector is network-based, allowing attackers to exploit this vulnerability remotely. The attack complexity is low, making it easier for potential attackers to carry out. The privileges required are low, meaning that an attacker does not need elevated permissions to initiate an attack.
User interaction is not required, further increasing the risk associated with this vulnerability. The confidentiality impact is high, as sensitive data may be read without authorization, while the integrity and availability impacts are rated as none.
Risk & Impact Analysis
Organizations using the Kafka Connect BigQuery Connector are at significant risk due to the nature of this vulnerability. The arbitrary file read capabilities can expose sensitive information, leading to potential data breaches.
The blast radius for this vulnerability could be extensive, especially for organizations that handle sensitive data within their BigQuery services. Given the high CVSS score, organizations should act swiftly to mitigate this risk.
The urgency for remediation is high, and organizations should address this vulnerability in their priority patch cycle to prevent potential exploitation.
Exploitation Status
Signal | Status |
|---|---|
Known Exploit | No |
Public PoC | No |
Actively Exploited | No |
Ransomware Use | No |
Affected Versions
The affected versions are all prior to 2.11.0 of the Kafka Connect BigQuery Connector. Organizations utilizing versions below this should take immediate action.
Mitigation & Remediation
Organizations should apply the patch available in version 2.11.0 of the Kafka Connect BigQuery Connector. If the patch cannot be applied immediately, consider implementing configuration hardening by validating all credential configurations before they are processed. Monitoring for unusual access patterns and employing network controls can also help mitigate risks.
For further security assessments, organizations can utilize penetration testing services to identify and address similar vulnerabilities.
Detection Guidance
Organizations should monitor logs for any unauthorized access attempts and review the configuration of credential files regularly. Look for behavioral anomalies that indicate attempts to exploit this vulnerability, including unexpected access to sensitive files.
AppSecure Threat Intelligence Insight
The long-term significance of this vulnerability highlights the necessity for organizations to maintain rigorous validation processes for credential configurations. This incident serves as a reminder of the importance of secure coding practices and proactive security measures.
Patterns of vulnerabilities related to improper input validation underscore the need for security teams to engage in continuous security assessments. For insights into best practices in security testing, refer to the penetration testing methodology and the importance of a robust incident response strategy.
Organizations should also consider establishing a vulnerability management program to effectively manage and remediate vulnerabilities as they arise.
In conclusion, continuous awareness and adaptation to emerging threats, such as those highlighted by this vulnerability, are essential for maintaining a secure infrastructure.
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.
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