Just started with Exabeam and I'm a bit stuck. The out-of-the-box use cases for things like suspicious logons or data exfiltration seem like a great starting point, but I'm finding they need a ton of tweaking to match how our SaaS tools actually behave.
For example, a "mass download" alert kept firing on normal marketing automation exports. Has anyone else spent more time customizing these than they expected? What's the best approach—should we modify the existing ones or build new custom use cases from scratch? Coming from a no-code background, the learning curve feels steep.
Thanks!
Thanks!
That's a common pattern I've seen across platforms, not just Exabeam. Out-of-the-box rules are built for the "average" environment, which rarely exists. Your marketing export example is perfect.
I'd advise against building from scratch initially. Modify the existing use cases first. Start by adding very specific exceptions or adjusting thresholds. For a "mass download" rule, you could whitelist the service account used by the marketing tool or set a higher threshold just for that user group. This teaches you the system's logic with a working template.
The learning curve is real, but think of it as tuning a new car's suspension. It's supposed to be generic.
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Absolutely, and the "average" environment concept is key here. The problem is that these default thresholds are often calibrated for worst-case, noisy enterprise environments to avoid false negatives. That creates massive false positive rates in well-behaved or specialized setups like yours.
While I agree with modifying existing use cases, I'd stress a profiling-first approach. Don't just whitelist the marketing service account immediately. First, use the platform's analytics to baseline that account's normal behavior over, say, 30 days. What's its 95th percentile download volume? Set your threshold just above that, not at some arbitrary vendor default. This moves you from generic rules to statistically-informed detection.
Building from scratch is a last resort, but sometimes necessary when the underlying logic of the OOTB rule is fundamentally misaligned with your workflow's pattern.
Oh, that marketing export example hits home. We had the same thing happen with our HubSpot daily data pulls triggering alerts. It was a real pain.
I'm also coming from more no-code marketing tools, and the adjustment to this kind of platform is significant. Do you think part of the problem is that these security tools are built by engineers, for engineers? They expect a baseline of technical comfort that just isn't there for someone from a marketing ops background.
What was your process for figuring out it was the marketing tool causing the alert? I'm still learning how to trace things back like that.
The best approach is to tweak the existing ones, but brace for some philosophical frustration. These default rules are a sales tool, not an engineering tool. They exist to let the vendor check a feature box and justify the enterprise price tag, not to work in your environment out of the box. Of course you'll spend most of your time customizing them.
A marketing export triggering a mass download alert is the classic proof. It shows the rule was built for a generic, paranoid 'insider threat' scenario, not real business operations. You'll likely have to do this for every SaaS app you own. Fun times! 😅
My advice? Don't build from scratch until you absolutely have to. But do keep a log of all the tweaks you make, because you're building the vendor's rule into *your* rule. That's your real intellectual property now.
—DW