Alright, let's talk about the noise. Every time I look at our Enterprise Security dashboard, it's lit up like a Christmas tree with "threats" that are just background radiation of the internet. We're drowning in alerts from routine network scans, shodan probes, and whatever bot is having a bad day.
I know the theory: tune your correlation searches, adjust risk scores, modify the notable event framework. But the vendor docs read like they were written by someone who's never actually sat in a SOC watching 500 "Medium Severity" events roll in for the same external IP scanning port 443. The generic advice is to just "refine your risk rules," which is about as helpful as telling a sales rep to "just sell more."
What I'm looking for are the *actual* filters and logic you've implemented that work. Specifically:
* **Risk-based filtering adjustments:** Which risk modifiers did you change, and for which data models (Network Traffic, for instance)? Did you just drop the score for "Network Scan Detected from External Source" into the basement, or is there a smarter way?
* **Whitelisting strategies:** Do you maintain a lookup of known benign scanner IPs (like security research orgs)? How do you keep that updated without it becoming a full-time job?
* **Contextual filtering:** Anyone had success using asset or identity correlation to filter scans? If a scan hits a non-existent IP or a low-value system, can you safely deprioritize it without completely dropping the event?
I'm skeptical of any solution that claims to be "set it and forget it," but there has to be a middle ground between ignoring everything and alerting on everything. What's actually working in your environment to cut through this particular brand of hype?
Trust but verify.
I feel your pain. We run a fairly open homelab and the constant scan noise is unreal. For risk based filtering, we had to get surgical. Instead of globally dropping scores for "Network Scan Detected," we built a conditional rule. It only lowers the risk score if the scan is targeting a port we intentionally expose to the internet, like 443 or 80. Scans for closed or internal ports on our external IP still get flagged higher.
On whitelisting, I maintain a small local lookup of IPs from projects like Censys and some university research nets we've vetted. It's not perfect though, because sometimes those ranges get repurposed. How often do you update your list?
Self-host or die trying.
Conditional rules based on port exposure are a solid start, but they can create blind spots. You're assuming the threat model for a scan on an open service port is uniformly lower, which isn't statistically sound. A scan on port 443 could be benign reconnaissance, or it could be the precursor to a targeted exploit against a specific web application vulnerability. By automatically downgrading that risk, you're introducing a filter bias that assumes all scans against open ports have equivalent intent.
A more rigorous approach is to incorporate scan velocity and destination context into that conditional logic. For instance, a single source IP scanning only ports 80 and 443 across your entire netblock might be downgraded. But that same IP performing a high-frequency scan of *only* port 443 across 50 of your IPs in five minutes should retain, or even increase, its risk score, as it indicates target selection beyond simple discovery.
Your point on the whitelist maintenance is the key flaw in any static list approach. The update frequency question is a trap - it's never frequent enough. We moved to a dynamic lookup that checks IPs against a reputation feed and only applies the whitelist discount if the IP has a high reputation score *and* the activity matches known research patterns, like full IPv4 scans.
p-value < 0.05 or bust