Threat hunting proactively identifies hidden threats that have bypassed existing security measures, aiming to stop attacks before they escalate to significant damage.
Key takeaways
Cyber threat hunting is a proactive security practice that focuses on detecting hidden, ongoing, or emerging threats before they cause harm.
It combines human expertise, threat intelligence, and advanced tools like SIEM, EDR, and MITRE ATT&CK mapping to uncover sophisticated attacks.
Threat hunting reduces dwell time, enhances detection capabilities, and improves an organization’s overall security posture.
Common approaches include proactive hunts, reactive investigations, continuous monitoring, intelligence-driven searches, and hypothesis-based operations.
How does threat hunting work?
Threat hunting relies on human-driven expertise, supported by advanced security tools and threat intelligence. It typically follows a structured, hypothesis-driven process, although techniques like anomaly hunting use baseline deviation without a strict starting hypothesis. Threat hunting often targets advanced techniques, such as living off the land (LOTL) attacks, where adversaries exploit legitimate system tools — known as living off the land binaries and scripts (LOLBins) — to bypass traditional defenses and remain undetected.
The threat hunting process:
Develop a hypothesis
Threat hunters develop theories about potential compromises based on threat intelligence, adversary behavior, industry trends, or unusual activity. This focused, hypothesis-driven approach prioritizes the most likely attack scenarios, making hunts more efficient than random exploration.
Collect and analyze data
Once a hypothesis is established, hunters gather data across the network.
According to CISA, operational capabilities should include:
Network traffic monitoring
Endpoint detection and response (EDR)
Host-level visibility
Advanced analytics and visualization tools
Correlation with threat intelligence
Threat hunters use specialized tools and advanced analytics, including visualization and machine learning (ML) for initial triage and pattern detection, to search for anomalies or patterns that may indicate malicious activity. While ML assists by highlighting suspicious activity or unusual patterns across large datasets, human expertise is essential for formulating hypotheses, interpreting context, and validating threats. Frameworks like MITRE ATT&CK often guide this process by mapping suspicious behaviors to known adversary tactics and techniques.
Validate threats
When suspicious activity is detected, it triggers hunters to investigate further to confirm whether it represents an actual threat or a false positive. This step requires a deep understanding of attacker tactics, techniques, and procedures (TTPs), as well as a clear understanding of normal business operations. Hunters sometimes use threat emulation or adversary simulation tools, such as Atomic Red Team or Caldera, to validate their detection capabilities after confirming threat scenarios.
Respond and remediate
Once hunters confirm a threat, they document their findings and work with incident response teams to take appropriate action.
Remediation efforts may include:
Isolating affected systems
Removing malware
Strengthening controls to prevent similar attacks in the future
Iterate and improve
Organizations use threat insights to shape their ongoing overall security strategy.
Security teams leverage findings to:
Enhance detection capabilities and guide security operations (SecOps) playbooks and incident response runbooks
Improve automation and alerting
Inform future threat-hunting hypotheses
History of threat hunting
The National Institute of Standards and Technology (NIST) formally recognized threat hunting in its Security and Privacy Controls for Information Systems and Organizations, Special Publication 800-53, updated in 2020, establishing it as an official cybersecurity control.
RA-10: Threat Hunting
Control:
a. Establish and maintain a cyber threat hunting capability to:
1. Search for indicators of compromise in organizational systems; and
2. Detect, track, and disrupt threats that evade existing controls; and
b. Employ the threat hunting capability [Assignment: organization-defined frequency].
NIST defines threat hunting as an active means for cyber defense. Unlike traditional security measures, such as firewalls, intrusion detection and prevention systems, sandboxes that quarantine malicious code, and security information and event management (SIEM) platforms, it is a proactive approach that involves searching systems, networks, and infrastructure for advanced threats. Threat hunting focuses on tracking and disrupting threat actors early in the attack sequence, improving the speed and accuracy of an organization’s threat response.
Threat hunting experts share preexisting (and sometimes newly discovered) threat intelligence with:
Peer organizations
Information sharing and analysis organizations (ISAO)
Information sharing and analysis centers (ISAC)
Relevant government departments and agencies
Even before formal recognition by NIST, elite cybersecurity teams had been informally practicing threat hunting, recognizing its critical role in proactive defense. Foundational concepts emerged from frameworks like Mandiant’s APT1 report (2013) and Lockheed Martin’s Cyber Kill Chain (2011).
Threat hunting approaches
Reactive hunt
Initiated by incidents, alerts, or anomalies detected by existing security tools
Proactive hunt
Conducted without external triggers, based on expertise and potential risk areas, through threat hunting operations aimed at identifying hidden or emerging threats
Persistent hunt (also known as continuous threat hunting)
Continuously monitors systems and networks to identify threats over time, rather than relying on periodic hunting campaigns
Intelligence-based hunt
Focused on specific indicators of compromise (IOCs) or TTPs derived from threat intelligence sources
Hypothesis-based hunt
Begins with a theory or assumption about how an adversary might target the environment and tests that theory by searching for supportive evidence
Types of threat hunting tools
As Gartner states, people are at the core of threat hunting, but beyond highly-trained IT security professionals, an array of specialized tools helps detect sophisticated threats. They include:
Security information and event management (SIEM)
SIEM platforms aggregate security data from across the organization. They provide centralized log management, real-time monitoring, and advanced analytics capabilities that form the foundation of many threat hunting frameworks. SIEMs, when enhanced with custom detection rules and threat intelligence, support threat hunting efforts.
Endpoint detection and response (EDR)
EDR tools monitor endpoint devices, including computers, servers, and mobile devices, for suspicious activity. They provide detailed visibility into processes, file system changes, memory operations, and network connections that might indicate an attack. Many EDR platforms include response capabilities to contain threats once discovered.
Network traffic analysis (NTA)
NTA tools examine network communications to identify malicious patterns. By analyzing traffic flows, packet contents, and communication patterns, these tools can detect command-and-control channels, data exfiltration attempts, and lateral movement that indicate the presence of an active attacker.
User and entity behavior analytics (UEBA)
UEBA systems establish baselines of normal behavior for users and systems, then flag deviations that might indicate compromise. These tools are particularly effective at detecting insider threats, compromised accounts, and other attacks that appear legitimate at first glance.
Threat intelligence platforms
These platforms aggregate information about known threats, adversary tactics, and indicators of compromise from multiple sources. This intelligence helps hunters focus their efforts on relevant threats and indicators associated with specific threat actors targeting their industry.
Modern extended detection and response (XDR) platforms
XDR platforms are evolving to unify SIEM, EDR, and threat intelligence functionalities, streamlining data correlation for threat hunters. However, XDR solutions are often built around vendor-specific ecosystems and may provide different coverage and integration capabilities compared to =traditional SIEM platforms.
Threat hunting vs. threat intelligence vs. threat detection
Threat hunting, intelligence, and detection often work together in a continuous cycle. The table below highlights the key differences between them.
Concept | Definition | Main goal | When it happens |
Threat hunting | A proactive, human-led search for threats that may have already bypassed security defenses but haven’t been detected yet. | Find active or hidden attackers inside the environment before significant damage occurs. | During a potential attack (even if not detected by tools yet). |
Threat intelligence | The process of collecting, analyzing, and sharing information about cyber threats (adversaries, tactics, vulnerabilities). | Understand who might attack, how, and why — to prepare defenses. | Before or outside an attack (strategic, tactical, operational). |
Threat detection | The act of automatically identifying IoCs or suspicious activity using security tools like SIEMs, EDRs, IDS/IPS. | Trigger alerts based on known patterns or behaviors to catch attacks. | When an attack occurs (based on triggers and alerts). |
Benefits of threat hunting
Implementing a threat hunting program delivers several advantages:
Reduced dwell time
Threat hunting can reduce the average time attackers remain undetected within networks, limiting their ability to move laterally, maintain persistence, and exfiltrate data.
Improved security posture
Regular hunting exercises identify gaps in existing security controls and provide actionable insights for improvement.
Enhanced detection capabilities
Threat hunting helps organizations develop more effective detection rules and improve the configuration of automated security tools.
Proactive risk reduction
Instead of waiting for attacks to trigger alerts, threat hunters actively seek out and eliminate threats before they cause damage.
A deeper understanding of the IT environment
The hunting process builds organizational knowledge about normal network behavior, helping identify anomalies more readily.
Threat hunting FAQs
What are some threat hunting techniques?
Common threat hunting techniques include behavioral analysis, stack counting, clustering analysis, hypothesis-driven investigation, and retrospective analysis.
What is threat hunting in cybersecurity?
Traditional cybersecurity relies on known signatures and alerts, while threat hunting is proactive and assumes a breach. Where traditional defenses wait for alerts to trigger, threat hunters actively search for evidence of compromise, using human expertise to detect sophisticated threats that evade automated controls.
What skills are necessary for a threat hunter?
Essential threat hunter skills include a deep knowledge of operating systems and network protocols, data analysis capabilities, familiarity with adversary tactics and techniques (MITRE ATT&CK), proficiency with security tools such as SIEM and EDR, programming and scripting abilities, and strong analytical thinking. The most effective hunters combine technical expertise with creativity and intuition to recognize abnormal patterns that automated systems miss.
Improve your security posture with Okta
The most effective threat hunting programs recognize that modern attacks increasingly target identity infrastructures and privileged access pathways, requiring hunters to correlate user behavior anomalies with traditional network and endpoint indicators. By integrating identity-centric threat hunting with comprehensive access governance, organizations can detect sophisticated attacks that exploit legitimate credentials and bypass perimeter defenses.
