Database memory forensics: Identifying cache patterns for log verification

Cyberattacks continue to evolve and adapt to state-of-the-art security mechanisms. Therefore, it is critical for security experts to routinely inspect audit logs to detect complex security breaches. However, if a system was compromised during a cyberattack, the validity of the audit logs themselves cannot necessarily be trusted. Specifically, for a database management system (DBMS), an attacker with elevated privileges may temporarily disable the audit logs, bypassing logging altogether along with any tamper-proof logging mechanisms. Thus, security experts need techniques to validate logs independent of a potentially compromised system to detect security breaches.

This paper demonstrates that SQL query operations produce a repeatable set of patterns within DBMS process memory. Operations such as full table scans, index accesses, or joins each produce their own set of distinct forensic artifacts in memory. Given these known patterns, we propose that collecting forensic artifacts from a trusted memory snapshot allows one to reverse-engineer query activity and validate audit logs independent of the DBMS itself and outside the scope of a database administrator’s privileges. We rely on the fact the queries must ultimately be processed in memory regardless of any security mechanisms they may have bypassed. This work is generalized to all relational DBMSes by using two representative DBMSes, Oracle and MySQL.