A common point of confusion when evaluating Cybereason's pricing and operational model, particularly for large enterprises, is the mechanism and implication of their "rolling 30-day forensic data retention." Having analyzed this through the lens of data lifecycle management and cost structures in other SIEM/XDR platforms, I will attempt to demystify the architecture behind this feature. The key is to understand that "forensic data" here refers to the high-fidelity, granular evidence collected from endpoints, not merely the processed alerts or metadata.
Fundamentally, Cybereason's platform operates on a principle of **infinite retention for detection analytics, but finite retention for raw forensic data.** The distinction is critical:
* **Detection Data (Retained Indefinitely):** This includes the behavioral facts, entity relationships, and malicious linkages derived from the raw data. These analytical results, which power the MalOp™ stories and your historical hunting queries, are stored for the life of your contract. This allows you to search for past attacker behaviors across your entire deployment timeline.
* **Raw Forensic Data (Rolling 30-Day Window):** This is the unprocessed, voluminous telemetry—full process trees, registry changes, file system modifications, network connection details, and memory captures. This data resides in a high-performance, presumably more costly, storage layer optimized for rapid querying and investigation.
The "rolling 30-day" mechanism means that on any given day, the platform automatically purges the raw forensic data that is now 31 days old. A practical example:
- An incident investigation on Day 45 that requires inspecting a process execution chain from Day 10 will be impossible at the raw data level.
- However, if that Day 10 activity was flagged as malicious, all derived insights about it (process names, hashes, relationships) remain searchable in the analytics layer.
From an infrastructure perspective, this design is a direct cost-optimization strategy. Storing petabytes of raw, indexed forensic data in a hot queryable state is prohibitively expensive. By implementing this rolling window, Cybereason can:
1. Keep storage costs predictable and scalable.
2. Maintain high query performance on the most relevant, recent data.
3. Avoid the massive data egress and rehydration costs associated with cold storage solutions used by some SIEMs for long-term log retention.
The operational implication is that your incident response and evidence collection workflows **must be completed within the 30-day window**. Any required raw evidence for legal hold or deep historical analysis must be explicitly exported before its auto-expiry. This contrasts with platforms where all raw logs are kept for years, albeit often in cheaper, slower archival storage. The trade-off is clear: superior performance and cost profile for recent data, at the expense of requiring proactive evidence management for long-term retention needs.
Wow, thanks for breaking that down! That distinction between "detection data" and "raw forensic data" makes so much sense now.
So if I'm understanding right, you can hunt for an attacker's past behavior forever, but if you need the actual raw file or process memory from a specific endpoint six weeks ago, that's gone? That seems like a big trade-off for the cost model.
For a beginner like me, does this mean an investigator needs to be really prompt to capture those raw forensic artifacts before the 30-day window closes?
Exactly right! You've nailed the core trade-off.
> does this mean an investigator needs to be really prompt
Yes, absolutely. It forces a proactive triage workflow. If you get a weird alert on day 29, you can't sit on it. You'd need to trigger a manual evidence collection package from that endpoint ASAP before it rolls off. Some teams even script this to auto-capture artifacts for high-severity alerts.
The flipside is that indefinite detection data is super powerful for linking campaigns over time. You might lose the original malware binary from months ago, but you can still trace the attacker's every move across your network from the behavioral breadcrumbs. It's a different style of investigation.
Prompt engineering is the new debugging