CVE-2019-11292 in Ops Manager
Summary
by MITRE
Pivotal Ops Manager, versions 2.4.x prior to 2.4.27, 2.5.x prior to 2.5.24, 2.6.x prior to 2.6.16, and 2.7.x prior to 2.7.5, logs all query parameters to tomcat’s access file. If the query parameters are used to provide authentication, ie. credentials, then they will be logged as well.
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Analysis
by VulDB Data Team • 03/20/2024
The vulnerability identified as CVE-2019-11292 affects Pivotal Ops Manager, a platform used for managing and deploying cloud applications through the Cloud Foundry ecosystem. This issue specifically impacts versions prior to the mentioned patched releases, creating a significant security risk through improper logging practices. The flaw stems from the application's handling of HTTP query parameters within the Tomcat web server component, where all query parameters are automatically logged to the access log files without proper sanitization or filtering mechanisms.
The technical implementation of this vulnerability involves the Tomcat web server's default logging behavior which captures all incoming HTTP request parameters including those that may contain sensitive information such as authentication credentials, session tokens, or other privileged data. When users authenticate through query parameters rather than standard form-based authentication methods, these credentials become permanently stored in plain text within the Tomcat access logs. This represents a fundamental failure in secure logging practices and violates several security principles including the principle of least privilege and the protection of sensitive data at rest.
The operational impact of this vulnerability is severe and multifaceted, as it creates persistent exposure of authentication credentials and sensitive information that can be accessed by any entity with read access to the Tomcat log files. Attackers who gain access to these log files can extract usernames, passwords, API keys, and other authentication tokens that were passed through query parameters during application usage. This vulnerability directly enables credential theft and account takeover scenarios, particularly in environments where authentication occurs via URL parameters rather than secure header-based authentication. The risk is amplified in cloud environments where log files may be stored in shared or accessible locations, potentially exposing data to unauthorized parties within the organization or external attackers who have gained access to system resources.
This vulnerability aligns with CWE-532, which addresses information exposure through log files, and represents a classic case of insecure logging practices that violates the principle of least privilege. The flaw also maps to ATT&CK technique T1070.001, which covers indicator removal on host through deletion of log files, though in this case the issue is not deletion but rather the creation of sensitive data in logs. Organizations using affected versions of Pivotal Ops Manager face significant risk of credential compromise and unauthorized access to their cloud infrastructure. The vulnerability demonstrates poor input validation and output encoding practices in web application security, where query parameters should never be logged without proper sanitization or filtering.
The recommended mitigations include immediate upgrade to the patched versions of Pivotal Ops Manager as specified in the advisory, implementation of proper log sanitization procedures, and configuration changes to prevent query parameters from being logged in access files. Organizations should also review their logging configurations to ensure that sensitive data is not being captured in any application logs, and implement proper access controls and monitoring for log file access. Additionally, security teams should conduct thorough audits of their authentication mechanisms to identify and eliminate any usage of query parameter-based authentication methods that could expose credentials in log files. The remediation process should include configuration changes to Tomcat's logging behavior and potentially the implementation of custom logging filters that strip sensitive parameters before logging occurs.