Agentic Threat Hunting

continuous agentic threat hunting for the AI area

Mate’s agents proactively initiate hunts across your environment, continuously uncover attacks, discover their blast radius, and write detections to close coverage gaps. The hunts are directed and prioritized based on emerging threats and your environment’s risk and architecture.

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AI attackers beat detections

Attackers fly below your detection thresholds

Detections are tuned to a threshold and a known technique. AI-powered attackers beat both. They keep each action small, below the threshold, so nothing fires, and they chain those actions into a compromise.

Adversaries change faster than you can tune

AI attackers switch techniques before you've finished tuning the last detection, continuously outpacing detection engineering.

Threat hunting is either too narrow or too slow

A hunt is an unbounded problem. Without restricting the space, there's no end to where you could look - so hunters narrow to the known attacks of the APTs they think are targeting them. That's a small, biased slice, and most malicious activity falls outside that narrow scope.

The best threat hunters build their hypotheses based on your architecture, crown jewels, exposures, and threat models, but that takes a long time.

This makes the hunt expensive and slow,
so attackers succeed

Mate hunts proactively, continuously, across your environment

Agents initiate hunts, led by your architecture and context, so they can look for threats where it matters.

The Security Context Graph powers every hunt

Mate’s Security Context Graph continuously maps your architecture, crown jewels, exposures, activity, and relationships - giving its Hunt Agents the context to understand where risk is highest.

Mate’s Security Context Graph mapping architecture, crown jewels, threat models, CTI, and relationships to identify areas of highest risk.Mate’s Security Context Graph mapping architecture, crown jewels, threat models, CTI, and relationships to identify areas of highest risk.

Turns up the resolution where it matters

Mate’s Hunt Agents zoom into targeted areas, then investigate through the noise and correlate weak signals across systems to surface activity that would otherwise stay under the radar.

Mate’s Hunt Agents zoom into targeted areas to correlate weak signals, revealing emerging threats and missing security coverage.Mate’s Hunt Agents zoom into targeted areas to correlate weak signals, revealing emerging threats and missing security coverage.

Follows the hunt wherever it leads

Mate moves through the environment, tunes detections as it goes, and immediately pulls additional logs and context when something looks wrong.

Every hunt expands your coverage

Hunts trigger investigations, investigations trigger new hunts, and what Mate learns becomes new detections - continuously closing gaps and expanding coverage.

Mate’s hunting insights become new detections, visibility decisions, automation, and intelligence to continuously expand security coverage.Mate’s hunting insights become new detections, visibility decisions, automation, and intelligence to continuously expand security coverage.

Hunts are proactive

No need to trigger a hunt, write a prompt, or drop a CTI report. Mate’s Hunt Agents build their own hypotheses and initiate hunts, triggered by changes in your environment and in the threat landscape.

Mate’s Hunting Agents proactively build hypotheses from emerging threats, coverage gaps, and architecture changes to initiate hunts automatically.Mate’s Hunting Agents proactively build hypotheses from emerging threats, coverage gaps, and architecture changes to initiate hunts automatically.
Mate’s Security Context Graph mapping architecture, crown jewels, threat models, CTI, and relationships to identify areas of highest risk.
Mate’s Hunt Agents zoom into targeted areas to correlate weak signals, revealing emerging threats and missing security coverage.
Mate’s hunting insights become new detections, visibility decisions, automation, and intelligence to continuously expand security coverage.
Mate’s Hunting Agents proactively build hypotheses from emerging threats, coverage gaps, and architecture changes to initiate hunts automatically.

Contextual Hunts Surface More Threats

Mate is the only platform running contextual, architecture-led hunts. It learns your architecture, understands potential attack paths and hunts for threats. This raises the ratio of true positives surfaced per hunt, which means that you find more threats for the same number of hunts.

Contextual Hunt vs. Flat Hunt

Contextual hunts are efficient and prioritized. They will often surface true positives that "flat" hunts don't.

Flat Hunt
Contextual Hunt
Credential Theft
Flat Hunt

"Look for the behavior across every endpoint and return the matches."

Contextual Hunt

"Understand which identities have meaningful access, which devices they use, which systems they reach, and where those paths intersect weak controls or poor visibility, and prioritize your hunt."

Identity
Flat Hunt

SIEM data shows a normal user on a managed laptop.

NO RISKs Found
Contextual Hunt

This laptop shows a privileged identity touching an unmanaged machine that still has a trust path into production.

HIGH RISK Found

Continuous risk reduction

Mate hunts across all sources, and finds anything worth fixing: threats, posture gaps, misconfigurations and more.

One hunt, every tool

Find every match across your tools, correlated into one picture and mapped to MITRE, with a detection ready to deploy.

Every hunt increases your resilience

Mate's agentic hunt finds threats and detection coverage gaps, helps you find root cause, and prevents the next attack. It also surfaces architectural gaps, posture findings, exposure gaps, configuration issues, and health issues, and provides recommended fixes.

Close coverage gaps

Hunts and investigations are used to create and tune detections, updating your Context Graph, so coverage continuously compounds and drift is minimized.

FAQs

Why are AI attacks hard to find by traditional threat hunting?

AI attacks are hard for traditional threat hunting to find because they can continuously vary techniques, keep individual actions below detection thresholds, and chain seemingly benign activity into a compromise faster than static detections and manually scoped hunts can adapt.

  • Traditional hunts often start with known IOCs, TTPs, or threat actors, narrowing the search to behaviors defenders already expect.
  • AI-driven attackers can modify techniques and distribute malicious activity across small actions that look harmless when analyzed independently.
  • Effective hunting therefore needs to connect identities, assets, exposures, access paths, and activity so weak signals can be evaluated in their broader environment.
  • Agentic threat hunting uses this context to prioritize where to hunt and follow evidence across connected tools as the investigation develops.
What is architecture-led threat hunting?
Architecture-led threat hunting uses the organization’s actual architecture, including identities, critical assets, access paths, exposures, and controls, to determine where threats are most likely to matter and prioritize hunts accordingly. Instead of searching broadly for predefined attacker behaviors, hunters start with environmental context, focus on areas where valuable systems intersect weak controls or risky trust relationships, and follow evidence across connected data sources as the hunt develops.
What are the benefits of contextual threat hunting?

Contextual threat hunting makes hunts more focused and actionable by using your environment’s architecture, identities, crown jewels, exposures, and relationships to prioritize where risk matters most.

  • Find more meaningful threats: Prioritize suspicious activity based on its potential impact in your specific environment.
  • Reduce wasted hunting effort: Focus investigation depth on risky assets, identities, trust paths, and weak controls instead of searching everything equally.
  • Connect weak signals: Correlate activity across tools to reveal attack paths that may appear benign when events are viewed individually.
  • Improve future coverage: Turn hunt findings into new or improved detections while identifying posture gaps and misconfigurations that should be fixed.
What happens when a Mate’s Hunting Agent discovers a coverage gap?

Mate turns the hunt to an actionable coverage improvement by identifying coverage gaps and translating the finding into new detections, or tuning existing detections.

  • The hunt starts in areas that are prioritized by context, and surfaces threats and security gaps across all data sources.
  • Mate determines which behavior, attack path, or telemetry gap allowed the activity to remain insufficiently covered.
  • The workflow converts that understanding into detection logic that can address the uncovered behavior.
  • Future hunts can then operate with stronger coverage while continuing to search for additional gaps.

Explore Mate’s AI SOC platform.

Why can contextual threat hunting find attacks that individual detections miss?
Contextual threat hunting connects weak signals across different sources and is led by context. As a result it surfaces threats that traditional detections, which hunt broadly across all data, will miss. By forming hypotheses, correlating activity, and adapting as new evidence emerges, it can uncover attack patterns that never trigger a single high-confidence alert.
Can contextual threat hunting find issues beyond threats?
Yes, contextual threat hunting can uncover more than active threats because it evaluates suspicious activity against the organization’s architecture, identities, exposures, controls, and relationships. As a hunt follows evidence across the environment, it can surface posture gaps, misconfigurations, risky trust paths, weak controls, and detection coverage gaps that increase future risk, even when no active compromise is found.
How does Mate’s Agentic Threat Hunting work?

Mate’s Agentic Threat Hunting uses organizational context to proactively initiate and prioritize hunts, then follows evidence across connected tools to uncover threats and security gaps.

  • Mate’s Security Context Graph maps architecture, crown jewels, exposures, activity, identities, and relationships to understand where risk is concentrated.
  • Agents use that context, alongside emerging threats and threat intelligence, to determine what to hunt and where to focus.
  • As new findings emerge, agents pivot across connected security tools and data sources rather than staying constrained to a predefined query.
  • Hunt results can expose threats, posture gaps, and misconfigurations while feeding findings back into detections to close coverage gaps.

Discover Mate’s Security Context Graph.