Your SIEM Is Drowning You in Alerts. Fix the Signal.

Nearly every security team I’ve walked into has the same quiet crisis: the SIEM generates so many alerts that the humans have stopped believing any of them. Ten thousand alerts a day isn’t security. It’s an expensive way to guarantee you’ll miss the one that matters, buried under 9,999 that don’t. And the cruel part is that it doesn’t look like a failure — the dashboards are full, the tools are working, the budget was spent. It looks like diligence. It’s actually the opposite.

More data isn’t more security

The instinct when something gets missed is to log more, alert on more, tune the threshold tighter. It feels responsible — nobody ever got criticized in a post-mortem for collecting too much. But it’s actually how you build alert fatigue: the state where analysts reflexively close alerts without reading them, because hard experience taught them it’s almost always noise. And here’s the thing — they’re not being lazy. They’re being rational. When 999 out of 1,000 alerts are false, ignoring them is the statistically correct move most of the time. The problem isn’t the analyst’s discipline. It’s that you built a system that made ignoring alerts the smart bet.

Every real alert has a real cost

People treat alerts as free because generating one is cheap. It isn’t free — it’s just that the cost lands on a human somewhere downstream, one investigation at a time. Every alert that fires spends a slice of your team’s finite attention, and attention is the scarcest thing in a SOC. So the right question for any detection rule isn’t “could this ever catch something bad?” — almost anything could, in theory. The question is “is what this catches worth what it costs to look at every time it fires?” That reframe kills a huge share of the rules people keep out of a vague sense that more coverage is always safer.

If nobody acts on it, it isn’t telling you anything

My test for a detection rule is brutally simple: when this fires, will a human do something about it? If the honest answer is “no, we just close it,” then the rule isn’t telling you about the world — it’s training your team to ignore it, and worse, it’s teaching them the reflex of closing alerts unread, which they’ll carry right over to the alert that actually mattered. A rule that never leads to action isn’t neutral. It’s actively corrosive, because it degrades the one thing your whole detection program depends on: that when an alert fires, someone believes it enough to look.

Tune ruthlessly, or drown

The best SOCs I’ve seen aren’t the ones with the most rules. They’re the ones brave enough to turn rules off. That takes a kind of courage, because deleting a detection feels like lowering your guard — there’s always a story about the one time it might catch something. But keeping a rule that fires a hundred false alarms for every real hit doesn’t make you safer; it makes you slower and number to the alerts that count. Every alert that fires should be something a human would actually act on. If nobody ever does anything about a particular alert, cut it. Signal is what’s left after you’ve had the discipline to delete the noise.

Design detections around what actually hurts you

The way out of the noise trap isn’t tuning individual rules forever — it’s starting from the other end. What are the handful of things that would genuinely hurt this business, and what would they actually look like in the logs? Build your best, highest-fidelity detections around those, accept that you won’t catch everything, and stop pretending that a wall of low-value alerts is buying you the coverage the vendor promised. A dozen detections you trust and act on beats ten thousand you’ve learned to ignore, every single time. Coverage that nobody looks at is not coverage. It’s theater with a subscription fee.

The goal was never to see everything. That’s impossible, and chasing it is what drowned you in the first place. The goal is to see the things that matter clearly enough that a tired human at the end of a long shift will still stop and look. Get there by cutting, not adding — and you’ll have built something rarer than a full dashboard: a team that still believes its own alarms.