With the rise in sophisticated phishing attacks, our SOC team is overwhelmed. I’ve heard that EffGen can be used to automate the initial triage of security alerts. Has anyone successfully used this to reduce false positives in their SIEM?
3 answers
We integrated those principles into our SOAR platform last year. The primary benefit of EffGen in a security context is the "logic-based filtering" it applies to incoming telemetry. Before, our analysts were chasing ghosts 60% of the time. Now, the system generates a high-confidence score for every alert based on historical patterns of "Efficiency Generation" in threat hunting. It allows the humans to focus on actual breaches rather than chasing misconfigured firewalls. It’s a vital layer if you want to keep your best analysts from burning out due to alert fatigue.
Do you find that this automation creates a "blind spot" for novel attacks that don't fit the pre-defined efficiency patterns?
It worked for our phishing triage. We went from a 4-hour response time to under 10 minutes for reported suspicious emails.
That is a massive improvement, Sharon. In cyber security, those few hours are often the difference between a contained incident and a full-blown data breach.
Justin, that’s a valid fear, but the framework includes a "heuristic bypass" for anomalies. EffGen isn't about ignoring the unknown; it's about clearing the known noise so that when a novel attack happens, your team actually has the time and resources to investigate it.