So everyone's posting their shiny 4.8-star reviews. Let's talk about what happens when the alert volume goes from "concerning" to "oh, we have a real problem." We had a major incident last quarter—lateral movement from a compromised service account, leading to data exfiltration attempts. We run Cybereason.
Here's the breakdown of how it actually played out.
**Where it helped:**
* The MalOp (Malicious Operation) narrative was genuinely useful once we were in the thick of it. It connected processes across endpoints in a way that saved manual timeline stitching.
* The query tools for hunting are decent. Being able to pivot from a weird parent process to all other instances across the estate let us gauge scope faster than I expected.
* Their EDR component held up. No crashes, no agent drops during the incident response.
**Where it hindered:**
* The noise before the incident was deafening. We had a "critical" MalOp rating for something benign at least twice a week. By the time the real attack started, the SOC was dangerously desensitized. Tuning is a constant battle, and their default policies seem geared for maximum alerting.
* The scale question: They claim to handle "millions of endpoints." Our environment is ~15,000 endpoints. During peak investigation, the query performance degraded noticeably. I want to see proof of those "million endpoint" environments, because I'm skeptical.
* Integration friction. Getting our existing vuln scan data and IAM context (SSO/RBAC events) to meaningfully inform their MalOps was a multi-week project. Out-of-the-box? Not really.
Bottom line: It gave us the forensic capability to clean up, but it arguably contributed to the conditions that let the incident escalate in the first place due to alert fatigue. The tool is powerful, but it feels like a sports car that needs its own full-time pit crew to keep it running on the road.
The noise fatigue is real. We had a similar desensitization curve - their "critical" rating lost all meaning after a few months. We ended up creating a separate dashboard just for truly critical infrastructure alerts, bypassing their default severity.
I'm curious, did you find their support useful during the incident, or was it mostly you working with the tool directly? That's where we felt a gap.
K8s enthusiast
That pre-incident desensitization curve you described is critical. We observed the same pattern where the "critical" label became functionally meaningless for triage.
Our team attempted to quantify it. We pulled MalOp severity ratings for a 90-day period and compared them to our manual verdicts post-investigation. The false positive rate for "critical" was over 70%, mostly from their default policies on script interpreters and living-off-the-land binaries. This meant analysts were conditioned to treat "critical" as a medium-priority investigation queue.
The support question is an interesting one. We found their support useful for platform issues, but not for investigative help during the incident itself. The burden of evidence collection and scope determination remained entirely on our team, using the tools you mentioned. Did you implement a formal tuning cycle after the incident, or was the alert fatigue too ingrained to fix?
Data > opinions
That 70% false positive rate for "critical" is a sobering number, and it tracks with our own experience. It's not just fatigue, it actively trains analysts to distrust the system's primary urgency signal, which is dangerous muscle memory.
We did try a formal tuning cycle, but it felt like pushing a boulder uphill. Every time we'd suppress a noisy rule on, say, cscript.exe, we'd get a new batch of "critical" alerts from a slightly different living-off-the-land vector we hadn't blocked yet. The core issue seemed to be their default policy library treats so many common admin and scripting tools as inherently high-severity, with no real sense of baseline or context.
The real fix, for us, wasn't just tuning Cybereason. We had to feed its alerts into a separate SIEM and use that to apply our own contextual scoring - things like "is this endpoint in a sensitive segment?", "has this user done this before at 3 AM?", etc. That extra layer let us retrain the team to trust a *different* severity score, while Cybereason's own "critical" just became a raw data point. It's a clunky workflow, but it beat the fatigue.
That pre-incident noise is such a crucial point. We saw the same desensitization with our security team, but from a different angle - we run a lot of automated marketing tools that use scripting. Cybereason would flag the legit automation as "critical" constantly. The team started ignoring alerts from entire server groups, which is obviously a terrible habit.
It sounds like you found some good workarounds with the MalOp narrative and pivoting. Did the noise issue make it harder to initially spot the lateral movement, or was the signal clear enough once you started digging?
Keep it simple.