The era of stopping attacks with EDR alone is over

79% of detected attacks are malwareless, leaving traces outside the endpoints. The era of defending with EDR alone is over; expanding to SIEM to correlate logs across multiple systems has become unavoidable. However, log aggregation comes with operational hurdles, namely alert fatigue and detection rule maintenance. On average, only 21% of the attack techniques that could be detected with the ingested data actually have rules in place. This document examines the statistical hurdles faced during the transition from EDR to SIEM, and explains why an AI SOC operational model—where AI processes and humans decide—makes this transition successful.

Key Findings
01 — 79% of attacks are malwareless. Attacks using compromised legitimate credentials are difficult to distinguish from legitimate use on the endpoint, leaving fragmented traces across logs outside the device.
02 — Average detection rule coverage is only 21%. Real-world SIEM measurements show that while ingested data covers over 90% of MITRE ATT&CK techniques, configured rules sit at an average of just 21%.
03 — 4,484 alerts per day, with 67% left uninvestigated. SOC teams receive an average of 4,484 alerts daily, with 67% remaining uninvestigated.
04 — AI adoption reduces response times by 80 days. Organizations leveraging security AI and automation reduced breach response times by 80 days and saved an average of $1.9 million in breach costs.

Related Articles

For details on platforms that aggregate logs, see SIEM Architecture, Functions, and Selection.

To learn how to handle the initial triage of increasing alerts, read Automating Alert Triage.

For the approach to combining automated investigation with human judgment, see How AI SOC Works and Differences from Traditional SOCs.