From Default to Detection: My First Dive Into SIEM Tuning and Threat Detection
Bridging Theory and Practice Security tools like Wazuh and Sysmon are designed to catch common malware out of the box, but they'll quickly flood log storage with useless alert noise. You don't get real visibility that way. Security teams have to actively modify policies and write custom rules just to catch threats lurking in the shadows. To make matters worse, indicators like credential dumping,…
This story recounts the author's journey into the world of Security Information and Event Management (SIEM) tuning and threat detection. They set out to streamline a three-node lab environment aimed at catching malicious activities that typically get lost in the noise of log storage.
The author encountered a few challenges along the way. One such issue was the SIEM dashboard not receiving new logs due to virtual machine idle suspensions affecting background states. To resolve this, they had to troubleshoot the pipeline by verifying active TCP socket connections for the ad01 node on port 1514, clearing the local agent cache, and manually restarting the Wazuh service.
The author described four experiments conducted within the lab setup. The first experiment involved modifying a rule to detect credential dumping activity. The initial rule, which labeled the KRShowKeyMgr command as a high-severity threat, successfully detected most instances of credential dumping. However, it missed some cases due to case-sensitivity and targeted MITRE ATT&CK tags.
After refining the rule, they introduced a more robust version that addressed these shortcomings. The revised rule employed a regular expression (PCRE2) to account for case-insensitivity and sought variations of the KRShowKeyMgr command and rundll32 process execution involving keymgr.dll. This enhanced rule aimed to capture a broader range of credential dumping techniques, including T1555 (unsecured credentials).
The author emphasized the importance of custom rule creation and tuning in SIEM systems to effectively differentiate signal from noise and uncover meaningful threats in log data. This hands-on experience provided valuable insights into overcoming common pitfalls and refining detection mechanisms for better security posture.
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