CVE-2026-21808 in BigFix Quantum Risk Analyzer
Summary
by MITRE • 08/27/2026
HCL BigFix Quantum Risk Analyzer generates highly detailed logging information by default which increases the risk of sensitive data leakage and can provide an attacker with internal application logic and architectural details.
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Analysis
by VulDB Data Team • 08/27/2026
The vulnerability identified in HCL BigFix Quantum Risk Analyzer stems from a misconfiguration regarding its default logging verbosity settings, specifically categorized under CWE-209 as Information Exposure Through an Error Message or through excessive diagnostic information. By design, the software generates highly detailed logs that capture granular operational data without sufficient filtering of sensitive content. This behavior creates a significant security gap where internal application logic, architectural details, and potentially confidential user data are persisted in log files accessible to users with read permissions on the system hosting the analyzer. The presence of such verbose output allows an attacker who gains access to these logs to reconstruct the underlying structure of the application, identify specific implementation patterns, and locate potential entry points for further exploitation.
From a technical perspective, this issue aligns with ATT&CK technique T1083, which involves File and Directory Discovery, as well as T1592, Gather Victim Host Information, because the logs serve as a rich source of intelligence about the target environment. The excessive logging does not merely expose configuration details but can inadvertently record authentication tokens, session identifiers, or personally identifiable information if such data is passed through the application's processing pipeline during normal operation. This exposure facilitates reconnaissance activities by reducing the effort required for an attacker to understand the system's behavior and dependencies, thereby lowering the barrier for subsequent attacks such as privilege escalation or remote code execution attempts that rely on specific knowledge of the software stack.
The operational impact of this vulnerability is primarily centered around information disclosure and increased attack surface area. While BigFix Quantum Risk Analyzer itself may not be directly exploitable through a buffer overflow or injection flaw, the leakage of internal logic provides attackers with critical context needed to craft targeted exploits against associated components or integrated systems. For organizations relying on this tool for risk assessment, the unintended exposure of sensitive data within logs poses a compliance risk under regulations such as GDPR or HIPAA if personal health information or private user details are captured in plain text. Furthermore, architectural insights gained from these logs can aid adversaries in mapping network topology and identifying critical assets that require prioritized defense strategies.
To mitigate this vulnerability, administrators must immediately adjust the logging configuration to adhere to the principle of least privilege regarding data retention and visibility. This involves disabling verbose or debug-level logging in production environments and ensuring that only essential operational metrics are recorded. It is crucial to implement log sanitization mechanisms that automatically strip sensitive fields such as passwords, tokens, and personal identifiers before they are written to disk. Additionally, access controls on the log directories should be strictly enforced so that only authorized security personnel can view these files, preventing unauthorized users from harvesting intelligence. Regular audits of log content should also be conducted to verify that no new data types have begun appearing in logs due to software updates or configuration drifts, ensuring continuous compliance with secure logging standards like CWE-532 regarding information exposure through log files.