Security Monitoring, SIEM, and Detection Engineering Questions

Building and operating the detection stack: the SOC and detection-engineering practice that answers 'can we see an attack happening.' Covers SIEM platform selection and architecture, use-case and detection-rule query development (for example Splunk SPL, KQL, or Sigma), alert triage and tuning to reduce false positives, detection engineering and closing coverage gaps, mapping detections to the MITRE ATT&CK framework and scoring detection coverage, log analysis and anomaly and baseline development, network and endpoint telemetry sourcing, malware and compromise-indicator recognition, and security operations center (SOC) alert escalation workflows. Distinct from the reactive work of containing, remediating, and communicating during a confirmed incident (incident response and postmortem topics own that ground; this topic stops at 'the alert fired and here is the detection logic', not 'here is how we contained and recovered from it'). Distinct from generic system-reliability monitoring and observability (SLOs, error budgets, uptime dashboards), a separate discipline even when the underlying ingestion mechanics look similar; the anomaly or signal here must be framed as adversarial or security-relevant. Distinct from hardening a software delivery pipeline against supply-chain compromise (SBOM generation, artifact signing, dependency and build-permission controls); this topic only touches the delivery pipeline from the detection side, spotting a compromised build or tainted artifact via telemetry, not the preventive-controls side. Distinct from designing security control architecture and governance (security architecture and cloud security architecture topics own the design-time question of what controls should exist); this topic is the run-time operation of the detection stack once those controls are in place.