>Lock down a baseline for your core infrastructure and leave it alone
This is the key part that a lot of teams miss in the rush to automate tuning. The baseline isn't just a one-time setup - you have to actually treat it as immutable production logic. We started versioning those core rules separately and put a higher approval gate on them. Any change required a real change ticket and peer review, just like a firewall rule.
It cut our "noise-driven" tuning work in half, because we stopped fiddling with the stable parts. The quarterly CI/CD pipeline became for our experimental or perimeter rules only.
Latency is the enemy, but consistency is the goal.
Your team is right. Welcome to the SIEM tax.
That missed outbound connection is the perfect case study. The OOTB rules know what an outbound connection *is*, but they have zero idea what's *weird for your servers*. Building that context is your job forever.
For your web server logins, everyone's giving you the right pattern: success after failures. The first tuning step everyone misses is adding an exclusion for your own corporate IP space first. Otherwise, you'll spend your first week alerting on your own pentest team and help desk.
Trust but verify – and audit
Your focus on the 24-hour window hits the exact pain point. We landed on a similar number, but through analysis, not guesswork. Pulled a month of auth logs and plotted the time delta between a failure and the next success from the same IP.
The vast majority of legitimate "fat-finger then success" events happened within 15 minutes. The curve flattened dramatically after 8 hours. The 24-36 hour window you're discussing only captured an extra 0.2% of events, and manual review showed almost all of those were unrelated noise, not slow attacks.
The trade-off isn't about catching every possible attacker. It's about whether investigating hundreds of those long-tail correlations is a better use of time than building other detections. For us, it wasn't.
Show me the query.
Your team is correct, but the advice "you must customize everything" can lead to another common trap: perpetual reactive tuning without establishing a measurable baseline. The missed outbound connection is less about a missing rule and more about the OOTB content having no model of your specific server roles and expected network behaviors.
For your web server login example, building the "success after failures" rule is indeed step one. However, the real tuning begins after you deploy it. You must then analyze every alert it generates for a full week, categorizing each as true positive, false positive, or unknown. That analysis will show you which parts of your network generate the noise (like load balancer IPs, monitoring systems) and inform your first round of exclusions. Without that measured feedback loop, you're just trading one set of generic alerts for another slightly less generic set.
The actionable signal emerges from understanding the delta between the rule's output and your actual investigated incidents. That's what transforms a custom rule from a theoretical construct into a useful detection.
Trust but verify.
Exactly. That measured feedback loop is the only way tuning stops being a black hole of effort. I've seen teams skip that step and just endlessly add exclusions until the rule is useless.
Track the precision of each custom rule over its first month. If it's below a threshold you set, the rule itself is flawed. Scrap it and design a new one. Metrics > gut feeling.
slow pipelines make me cranky
Metrics are great in theory, but a precision threshold for a brand new rule can be too harsh. Sometimes a rule just needs a better baseline, not a full scrap-and-rebuild.
We had a rule with terrible precision in week one because it was catching our CI/CD system's deployments. The logic was fine, we just needed to build an asset group and exclude it. If we'd tossed the rule based on that first-week metric, we'd have lost a useful pattern.
The key is knowing *why* the precision is low before hitting the kill switch.