Stop Rebuilding the Same Timeline in Five Consoles
Investigation is the process of reconstructing what happened, end to end, to determine the scope and impact of a potential threat. Anomali normalizes endpoint, identity, network, and cloud data into one schema and fuses it with intelligence, so a full kill-chain reconstruction happens on one surface instead of requiring analysts to pull data from four or five separate consoles by hand.
Key Takeaways
The classic failure mode is the swivel chair: pulling data from multiple consoles and assembling a timeline manually
Case data, telemetry, and intelligence all live in the same normalized layer, so a case never has to leave the platform to move from detection to closure
Why This Is Different
Some vendors take a unification-first approach: unify the data first, worry about everything else later. That’s real progress over treating the SIEM as the aggregation point, but a clean data lake on its own is not an intelligence graph. Data being in one place doesn’t mean an analyst knows what any of it means without still doing the correlation work by hand.
Anomali offers more than just ingestion: a unified, intelligence-enabled dataset built specifically to power investigation, hunting, and automation, not just store data more efficiently. And because everything normalizes to one schema (OCSF), a detection or a correlation rule written once runs against every source, instead of needing custom logic rebuilt for every new telemetry type an investigation touches.
Investigation Use Cases
Detection-scoped endpoint context
Pain: When a detection fires, analysts need surrounding context to scope it quickly.
Today: Pulling raw EDR console data for the box in question, an unscoped and time-consuming process for routine triage.
With Anomali: The events surrounding a detection surface immediately, enough to scope and triage.
Data-access breach scoping
Pain: When a breach might involve sensitive data, the first question regulators and executives ask is what was accessed and by whom, and that’s often the hardest thing to answer quickly.
Today: Database administrators and app teams pull access logs manually on request, often taking days. Content-level determination usually needs a separate deep-dive on top of that.
With Anomali: Access and attribution for breach scoping establish from database audit and PHI/PII access metadata already ingested. Worth saying plainly: exact content review may still need the source system, this shortens the scoping step, not every step.
Deep host and application forensics
Pain: Targeted intrusions require forensic depth beyond EDR verdicts. Raw OS and application logs matter for reconstructing exactly what a sophisticated actor did on a host.
Today: Deep forensics is usually an incident-response engagement with an outside firm, pulling raw logs manually after the fact.
With Anomali: Full-stack forensic depth for targeted intrusions comes from app logs and OS security logs already ingested, in-platform, without waiting on an outside IR firm.
Full-fidelity case management
Pain: Detection, investigation, response, and case management usually live in different tools, forcing analysts to re-enter and re-explain findings at every handoff.
Today: Analysts copy findings between the SIEM, a ticketing system, and a separate case-management tool, losing context and time at each handoff.
With Anomali: A case runs through detection, investigation, response, and case management without ever leaving the platform.
Proof
“We leverage market-leading tools to give our company a competitive advantage and our 24/7 SOC a leg up on bad actors. With Anomali, we improve both goals. By adding intelligence, we achieve a high level of certainty that enhances prioritization of the most serious threats our customers face, while improving our mitigation decisions.”
- Grant Leonard, Co-Founder, Castra
FAQ
What named frameworks does Anomali map to for the Threat Intelligence use case?
Every indicator maps to MITRE ATT&CK and normalizes through STIX/TAXII for interoperability, so intelligence is portable in the vocabulary your whole security organization already uses.
What’s the difference between alert triage and investigation?
Triage decides whether an alert deserves attention. Investigation determines the full scope, root cause, and impact once it does. Context carries forward automatically between the two instead of resetting at the handoff.
Does this replace our existing XDR for investigation?
No. It enhances your existing XDR stack with intelligence-led context and unified telemetry, turning siloed data into one coordinated investigation instead of replacing the stack you already have.
How fast can we reconstruct a cloud or SaaS breach timeline?
Because cloud and SaaS audit data is already ingested and normalized, reconstruction starts from data you already have rather than a fresh export request to a vendor or an outside consultant.
Can identity data be part of the same investigation as endpoint and network data?
Yes. IdP events normalize into the same schema as endpoint, network, and cloud data, so an investigation can pull all four into one timeline without a separate identity-specific tool.
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