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APT Detection
and Hunting

Advanced persistent threat actors do not announce themselves. We find them anyway. Detection capability built specifically for the patient, sophisticated adversary that signature-based tools were never designed to catch.

Framework
MITRE ATT&CK
Focus
Pre-Compromise

Most tools wait for
the adversary to act

Signature-based detection is reactive by definition. It identifies what has already been seen. APT actors, by design, operate with techniques, tooling, and infrastructure that have not been catalogued. They move slowly, blend into legitimate traffic patterns, and operate below the detection thresholds of tools not built to find them.

Our APT detection capability approaches the problem from the adversary's perspective. We ask the question every defender should be asking: if a nation-state actor were operating in this environment right now, what would their presence look like? Then we build the capability to answer that question.

Detection logic engineered for sophisticated adversary tradecraft, not commodity threats
Coverage of the dimensions where APT activity is detectable, validated against real adversary techniques
Lateral movement reconstruction across authentication, network, and host data
DNS anomaly coverage for the protocols adversaries most consistently abuse
Full MITRE ATT&CK TTP mapping on every detection output

How we find what
others miss

01
Network Behavior Analysis
Detection logic targeting the network signatures sophisticated adversaries leave behind, surfaced from sensor data your existing tools are not built to interpret.
02
Lateral Movement Detection
Cross-system correlation that exposes adversary movement across authentication, network, and host data, reconstructing the full campaign scope, not just the entry point.
03
Protocol Anomaly Coverage
Coverage of the protocols adversaries most consistently abuse for covert channels. Detection logic anchored in adversary tradecraft, not generic anomaly thresholds.
04
Host and Network Correlation
Full kill chain visibility achieved through correlated host and network telemetry, surfacing activity that any single data source would miss in isolation.
05
Adversary Tradecraft Detection
Detection rules engineered against how sophisticated actors actually operate, not against compliance checklists or vendor default rulesets.
06
Intelligence-Driven Correlation
Live threat intelligence correlated against your traffic in real time, enriched with actor attribution where the intelligence picture supports it.

How an APT hunting
engagement runs

01
Hypothesis Development

We develop threat-specific hypotheses based on your industry, known adversary targeting patterns, and the intelligence picture relevant to your environment. Hunting without a hypothesis is just searching. We know what we are looking for before we start.

02
Data Collection and Baselining

Sensor data is collected and baselined against your environment's normal patterns. What looks like anomalous activity in one organization is normal automated traffic in another. The baseline gets established before any determinations are made.

03
Hunt Execution

Structured queries against your sensor data test each hypothesis systematically. Every finding is documented with the supporting evidence chain. Negative results are as important as positive ones. They establish what is clean and bound the investigation scope.

04
Findings and Detection Hardening

Every hunt produces two outputs regardless of whether active compromise is found: a findings report grounded in evidence, and a set of detection rules that permanently harden your posture against the techniques that were tested. The hunt makes you harder to compromise going forward, not just right now.

Are they already inside?

Most organizations do not know. A hypothesis-driven hunt is the only way to find out. Let us start with your highest-risk segments.

Start a Hunt