Bullish on Autonomous SOC. Realist about what gets us there.
There’s been plenty of talk lately about the Autonomous SOC — a future where machines don’t just alert but correlate, triage, investigate, and respond.
It sounds fantastic, especially if you’ve ever worked the night shift buried in alerts. But here’s the truth: you can’t automate everything unless the automation is learning from someone.
That “someone” is still the analyst. And not just to babysit the machine — but to influence it in meaningful ways.
From IOC Pain to Analyst Influence
Security veterans will remember the IOC Pyramid of Pain, which taught us that not all indicators are equal — the more abstract the IOC, the more it hurts the attacker when detected.
Now apply the same thinking internally:
Not all analyst feedback is equal either.
A comment is helpful.
A justified verdict that suppresses future alerts is transformative.
So, let’s introduce a new model: the Analyst Feedback Impact Pyramid — a framework to understand which types of human input drive real change, and which ones just decorate the interface.
Analyst Feedback Impact Pyramid
Not All TP/FP Feedback Is Equal
Here’s where nuance matters.
Clicking “False Positive” without saying why or for whom is Tier 1. It might show up in reports, but it doesn’t change the system.
Now add:
“FP because powershell.exe is used for patch automation on this host.”
Now you’ve created Tier 4 feedback. That can suppress the alert in future. Or trigger a detection exclusion. Or reweight an ML model. Now you’re training the system.
This is more than tagging — it’s teaching.
The Tesla Analogy: Nudge or Override?
- A light nudge on the wheel tells the system you’re engaged
- A firm grab takes control
Analyst feedback works the same way.
Sometimes it’s just guidance. Sometimes it’s a takeover. The trick is to make sure the machine can tell the difference — and learn from both.
The Human-Augmented SOC, Built for Feedback
At Stellar Cyber, we don’t just automate alert triage — we own the full cycle, from detection to response. That means we can do something most vendors can’t:
Let analyst feedback travel upstream to influence the detection layer itself.
So when a false positive is spotted, we don’t just auto-close it — we can suppress it at the source. Because preventing noise is always better than handling noise, no matter how efficient your triage pipeline is.
That’s what makes our platform uniquely suited for a Human-Augmented Autonomous SOC:
- One where the analyst's input has structured impact
- Where every justified click can tune a model or shape a rule
- And where feedback isn’t a dead end — it’s part of the engine
Final Thought: Feedback Is Fuel
Feedback is how trust is earned.
The Analyst Feedback Impact Pyramid helps us prioritize that feedback — and build systems that act on it with the right level of confidence.
In the end, autonomy isn’t about replacing humans — it’s about respecting their input enough to let it guide the machine.
Because the SOC doesn’t get smarter by itself.
It gets smarter by learning from its best teacher: the analyst who knows when to nudge, when to override, and when to teach the system not to make the same mistake twice.
