Proactive Attacker Discovery in Your Environment
Detections catch what they’re configured to catch. Threat hunting finds what detections miss. Our threat hunters use the Nexus platform’s Security Graph and behavioral analytics to systematically search for attackers already present in your environment — using the same TTPs our TDU researchers document from real-world adversary campaigns.
Threat Hunting Coverage
Even the best detection libraries have gaps. Threat hunting closes them by proactively looking for attacker behavior that isn’t yet covered by a detection rule.
We offer structured threat hunt packages targeting the attack surfaces where adversaries are most active. Each hunt is built around documented TDU adversary TTPs and uses Atlas’s Security Graph for context that generic hunting tools miss.
Systematically searches for evidence of credential compromise, token theft, OAuth abuse, anomalous privilege usage, impossible travel, and identity-based lateral movement across your identity infrastructure. Uses Atlas’s identity graph to identify behavioral patterns that generic SIEM queries miss entirely.
Hunts for attacker presence in your AWS, Azure, or GCP environments — including IAM permission abuse, unusual resource provisioning, cross-account role assumption, anomalous API call sequences, and evidence of cloud-native persistence mechanisms established by attackers.
Searches for evidence of SaaS-based intrusion including unauthorized OAuth application grants, abnormal data access patterns, cross-SaaS lateral movement indicators, mass download events, and evidence of attacker presence in Microsoft 365, Google Workspace, Salesforce, or Okta environments.
Hunts for established attacker persistence on endpoints including living-off-the-land binary abuse, scheduled task manipulation, registry persistence mechanisms, WMI subscriptions, and evidence of staged tooling or pre-ransomware reconnaissance activity across your endpoint fleet.
Proactively searches for evidence of AI agent compromise, prompt injection execution, MCP server abuse, anomalous agent tool usage, and unauthorized AI agent activity across your enterprise AI infrastructure. Uses AgentShield data for behavioral context unavailable to generic hunting tools.
Investigates third-party and supply chain access to your environment for signs of compromise or abuse — including vendor remote access anomalies, third-party integration exploitation, software update mechanism abuse, and evidence of supply chain compromise in your software development environment.
Every hunt follows a structured, hypothesis-driven process grounded in real adversary TTPs. No generic anomaly queries. No fishing expeditions. Systematic, documented attacker simulation.
Before any data is queried, our hunt team develops specific hypotheses based on the adversary TTPs most relevant to your industry, technology stack, and known risk profile. Hypotheses are drawn from TDU threat intelligence, current campaign tracking, and Atlas’s assessment of your specific attack surface. Every query run during the hunt is tied to a documented adversary behavior, not generic anomaly detection.
Hunters begin with Atlas’s Security Graph — reviewing your identity relationships, trust paths, privilege structures, and attack path modeling to identify the areas of highest exploitation likelihood. This context shapes where we hunt and what we look for, giving our team visibility that is fundamentally unavailable to hunters using only SIEM and EDR data.
With hypotheses defined and Atlas context established, our hunters systematically work through the telemetry — querying identity logs, cloud audit events, endpoint data, SaaS activity, network flows, and AI agent behavioral data against each hypothesis. We document every query, every finding, and every artifact examined to maintain a complete evidence trail regardless of outcome.
Every anomalous finding is triaged for attacker relevance — distinguishing between legitimate unusual activity, misconfiguration, and genuine attacker presence. When active threats are discovered, our hunt team escalates immediately to incident response, engaging Vanguard for containment while the full investigation continues. Customers are notified within 30 minutes of any confirmed active threat finding.
Within 48 hours of hunt completion, customers receive a comprehensive hunt report covering methodology, hypotheses tested, queries executed, findings (positive and negative), evidence documentation, and recommendations. Critically, every hunt produces new detection logic — translating hunt findings into Nexus detections that continuously monitor for the TTPs we searched for manually.
Every LogicBounce threat hunt produces a complete set of deliverables — regardless of whether active threats are found. A clean hunt is as valuable as a positive one, because it produces the detections that prevent future gaps.
A full technical report documenting everything found during the hunt — positive findings, negative findings, anomalies investigated, and evidence reviewed.
Every hunt produces new detection rules that monitor for the TTPs we searched for manually — so future attacker activity using the same techniques is caught automatically.
Specific, prioritized recommendations for reducing the attack surface areas explored during the hunt — whether or not active threats were found.
When active threats are discovered, our team transitions immediately from hunting to incident response — no handoff delay, no separate engagement required.
Threat Hunting works alongside MDR to find attackers between incidents, and integrates with SOC as a Service for customers who want continuous proactive discovery as part of their managed operations.
30% of our threat hunts discover active threats that existing detections missed. Schedule a hunt and find out what’s in your environment right now.
