Cyber: Latest From Triage To Threat Hunts: How AI Accelerates Secops
If you work in security operations, the concept of the AI SOC agent is likely familiar. Early narratives promised total autonomy. Vendors seized on the idea of the "Autonomous SOC" and suggested a future where algorithms replaced analysts.
That future has not arrived. We have not seen mass layoffs or empty security operations centers. We have instead seen the emergence of a practical reality. The deployment of AI in the SOC has not removed the human element. It has instead redefined how they are spending their time.
We now understand that the value of AI is not in replacing the operator. It is in solving the math problem of defense. Infrastructure complexity scales exponentially while headcount scales linearly. This mismatch previously forced teams to make statistical compromises and sample alerts rather than solving them. Agentic AI corrects this imbalance. It decouples investigation capacity from human availability and fundamentally alters the daily workflow of the security operations team.
Alert triage currently functions as a filter. SOC analysts review basic telemetry to decide if an alert warrants a full investigation. This manual gatekeeping creates a bottleneck where low-fidelity signals are ignored to preserve bandwidth. Now imagine if an alert that comes in as low severity and is pushed down the priority queue ends up being a real threat. This is where missed alerts lead to breaches.
Agentic AI changes triage by adding a machine layer that investigates every alert, regardless of severity, with human-level accuracy before it reaches the analyst. It pulls disjointed telemetry from EDR, identity, email, cloud, SaaS, and network tools into a unified context. The system performs the initial analysis and correlation and redetermines the severity, instantly pushing that low-severity alert to the top. This enables the analyst to concentrate on detecting malicious actors concealed within the noise.
The human operator no longer spends time gathering IP reputation or verifying user locations. Their role shifts to reviewing the verdict provided by the system. This ensures that 100% of alerts receive a full investigation as soon as they arrive. Zero dwell time for every alert. The forced tradeoff of ignoring low-fidelity signals disappears because the cost of investigation is significantly lower with AI SOC agents.
Effective detection engineering requires feedback loops that manual SOCs struggle to provide. Analysts often close false positives without d
Source: The Hacker News
