What is Managed Threat Hunting?

What is managed threat hunting?

Managed threat hunting is a security service where external experts actively search for threats hiding in your network. Unlike automated security tools that wait for alerts, threat hunters proactively look for attackers who have already bypassed your defenses. They use a combination of advanced technology and human expertise to find sophisticated threats that standard security systems miss.

The service works by assuming that attackers may already be in your environment. Hunters then search for subtle signs of malicious activity, like unusual login patterns or suspicious data transfers. This proactive approach catches threats much faster than waiting for an automated alert, which can save your organization from serious damage.

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How managed threat hunting works

Managed threat hunting follows a structured process that combines investigation techniques with continuous monitoring. The process adapts to your specific environment and evolves as new threats emerge.

The threat hunting process

Threat hunters start by developing hypotheses about how attackers might operate in your environment. For example, they might theorize that an attacker could use a compromised service account to move between cloud services undetected. They then search through logs, network traffic, and system activity to find evidence supporting or disproving their theory.

This hypothesis-driven approach is more effective than random searching. Each investigation teaches hunters something new about your environment and potential attack methods. They use these insights to refine future hunts and make the process more efficient over time.

Sample cloud threat hunting hypotheses

Hunters develop testable theories about attacker behavior specific to cloud environments:

Identity and access hypotheses:

• "Compromised AWS access keys are being used from IP addresses outside our known ASN ranges"

• "Azure service principals are pivoting across subscriptions to access resources beyond their intended scope"

• "GCP workload identities are being used to access sensitive BigQuery datasets from unexpected Kubernetes namespaces"

Configuration and exposure hypotheses:

• "Attackers created new public S3 buckets or modified bucket policies in the last 24 hours to exfiltrate data"

• "Recent IAM role trust policy changes allow external accounts to assume roles with sensitive permissions"

Kubernetes-specific hypotheses:

• "New cluster role bindings grant cluster-admin privileges to service accounts in non-system namespaces"

• "Container images from untrusted registries are running with privileged security contexts"

Each hypothesis guides specific queries across CloudTrail, Kubernetes audit logs, and IAM change history to find supporting or contradicting evidence.

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What is Proactive Threat Hunting?

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Technology and human expertise blend

The hunting process relies on both automated tools and human analysis. Advanced platforms collect data from across your cloud environment and use algorithms to spot unusual patterns. However, these tools can generate false alarms or miss subtle indicators that only an experienced analyst would recognize.

Human hunters interpret the data using their knowledge of attacker tactics, techniques, and procedures. They understand frameworks like MITRE ATT&CK, which maps out how attackers typically operate. This expertise helps them distinguish between harmless anomalies and genuine threats, connect related events into a complete attack story, and adapt their strategies as attackers change their methods.

Continuous monitoring and analysis

Threat hunting isn't a one-time scan. It's an ongoing service that monitors your environment around the clock. Attackers don't work on a schedule, so continuous surveillance ensures that threats are caught quickly no matter when they occur.

The process also creates a feedback loop that strengthens your defenses. Every finding—whether it's a minor issue or a major threat—provides information that improves your security. Modern cloud threat hunting platforms use security graphs to correlate findings across identity relationships, network paths, and data access patterns. This graph-based context helps hunters understand blast radius, trace lateral movement, and prioritize threats based on actual attack paths rather than isolated alerts. Hunters use this knowledge to update detection rules, refine security policies, and give you a clearer picture of your overall security posture.

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Benefits of managed threat hunting over internal capabilities

Building your own threat hunting team requires significant investment and ongoing resources. Managed services offer several advantages that make them attractive for most organizations.

Expertise and specialization

Managed threat hunting gives you immediate access to security experts who have seen threats across many different organizations and industries. These hunters bring experience from hundreds of investigations, which helps them spot attack patterns that an internal team might not recognize. They stay current with the latest threat techniques because they encounter new attacks regularly across their client base.

External hunters also gain insights from working in diverse environments. When they discover a new attack method at one client, they can apply that knowledge to protect all their other clients. This cross-pollination of expertise is difficult to achieve with an internal team that only sees threats within a single organization.

Resource optimization

Creating an effective internal threat hunting program requires hiring rare security talent, purchasing expensive tools, and maintaining 24/7 operations. These costs add up quickly and strain security budgets. Managed services provide enterprise-level capabilities without the overhead of building and maintaining an internal team.

This model lets you redirect internal resources to other security priorities. Your existing security staff can focus on strategic initiatives while the managed service handles continuous threat hunting. You get expert coverage without the burden of recruitment, training, and retention.

Faster threat detection

The main goal of threat hunting is reducing dwell time—the period between when an attacker enters your environment and when you detect them, which averaged 10 days in 2023 according to Mandiant's M-Trends report. Managed hunters accelerate detection by applying proven investigation playbooks from day one while rapidly learning your environment's unique patterns, critical assets, and business context to focus hunts where they matter most.

This speed advantage is critical in cloud environments where attackers can move from initial access to data theft in minutes. Managed hunters can investigate suspicious activity immediately and provide clear guidance on response actions, dramatically shortening the window for attackers to cause harm.

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Managed threat hunting vs other managed security services

The security services market includes several offerings that sound similar but serve different purposes. Understanding these differences helps you choose the right service for your needs.

Managed threat hunting vs MDR

Managed Detection and Response (MDR) is a comprehensive security operations service that includes threat hunting as one component. Here's how they differ in scope and engagement:

Many organizations choose MDR services specifically to access the threat hunting capabilities included in the package, gaining both reactive monitoring and proactive hunting in one engagement.

Managed threat hunting vs MSSP

A Managed Security Service Provider (MSSP) manages your existing security tools like firewalls and intrusion detection systems. They monitor alerts from these tools, perform routine maintenance, and ensure systems are configured properly. MSSPs primarily focus on monitoring and operations—managing security tools, responding to system-generated alerts, and handling known threat patterns through established runbooks.

Threat hunting is proactive and searches for threats that your existing tools have missed. While MSSPs provide essential security management, they typically don't actively hunt for hidden attackers. The two services work well together, with threat hunting adding a proactive layer on top of the foundational monitoring that MSSPs provide.

Managed threat hunting vs incident response

Threat hunting happens before a confirmed security incident, while incident response begins after a breach is detected. Hunters work continuously to find and stop attackers before they achieve their goals. Incident responders activate when a major security event occurs to contain damage, remove threats, and restore normal operations.

Effective threat hunting reduces the number and severity of incidents that require full incident response. By catching attackers early, hunters prevent many situations from escalating into major breaches that need extensive remediation efforts.

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Key considerations for cloud-native threat hunting

Hunting for threats in cloud environments requires different skills and approaches than traditional network hunting. The cloud's unique characteristics create both challenges and opportunities for threat detection.

Cloud infrastructure complexity

Cloud resources like virtual machines and containers can be created and destroyed in minutes. This constant change makes it difficult to track activity and collect evidence. Effective cloud hunting requires agentless visibility that can discover and analyze resources across AWS, Azure, GCP, and Kubernetes without manual agent deployment. Agentless collection through cloud APIs and read-only snapshots ensures complete coverage even in highly dynamic environments where resources scale up and down automatically. Traditional hunting methods that rely on static IP addresses and fixed servers don't work in this dynamic environment.

Cloud-native hunters need expertise in cloud provider logs and services. They must understand how to navigate complex interconnected systems and think in terms of cloud-specific attack paths. This requires knowledge of cloud-native data sources including AWS CloudTrail (management and data events), VPC Flow Logs, Azure Activity Logs and Resource Logs, Microsoft Entra ID sign-in logs, GCP Audit Logs and VPC Flow Logs, Kubernetes audit logs, container registry access logs, and runtime telemetry from EDR agents or eBPF sensors.

Essential cloud data sources for threat hunting

Effective cloud threat hunting requires visibility across multiple telemetry sources. Hunters typically collect and analyze:

Identity and access patterns

In cloud environments, identity becomes the primary security boundary. Attackers focus on stealing credentials, compromising service accounts, and exploiting IAM roles to move through your environment and access sensitive resources. Hunting for these threats requires deep understanding of cloud identity systems.

Hunters must analyze permissions, identify accounts with excessive privileges, and trace how compromised identities could be used to access critical data. This is more complex than monitoring failed logins on traditional networks because cloud IAM systems involve intricate permission structures and role relationships.

Multi-cloud visibility requirements

Most organizations use multiple cloud providers, each with different logging formats (AWS CloudTrail JSON vs. Azure Activity Log schema), security controls, and APIs. This creates visibility gaps where malicious activity can hide—one survey found only 25% of organizations detect breaches in real time across hybrid cloud environments. Hunters need tools that normalize data from AWS CloudTrail, Azure Activity Logs, GCP Audit Logs, and Kubernetes audit logs into a unified view.

Effective cloud threat hunting requires tools that normalize data from all cloud providers into a unified view. Without this capability, hunters must manually switch between different consoles and correlate data across platforms, which is slow and error-prone. A unified view lets hunters track threats across your entire multi-cloud environment efficiently.

Evaluating managed threat hunting providers

Selecting the right managed threat hunting partner requires careful evaluation of their capabilities, integration approach, and reporting methods.

Essential capabilities assessment

When evaluating providers, verify their expertise in your specific cloud platforms. Ask about their threat intelligence sources and how they keep their knowledge current. Review their hunting methodologies to ensure they use proven techniques rather than just automated scanning.

Code-to-cloud traceability: Ask how the provider traces runtime detections back to source code, CI/CD pipelines, and infrastructure-as-code templates. This capability enables root-cause remediation—fixing the code or configuration that introduced the vulnerability rather than just patching individual instances. Providers should show how they connect runtime threats to code owners, Git commits, and deployment pipelines for complete remediation.

Request customer references and case studies that demonstrate real-world success. The best measure of a provider's value is their track record of detecting and stopping actual threats. Ask specific questions about the types of threats they've found and how quickly they detected them.

Integration with existing security stack

Your threat hunting service should work seamlessly with your current security tools. Check how they integrate with your SIEM, SOAR, and endpoint detection tools. This integration ensures that hunting findings can be correlated with other security data and that response actions can be coordinated efficiently.

The provider should function as an extension of your security team with clear communication channels and defined collaboration processes. Ask how they share findings, how often they provide updates, and how they coordinate with your internal team during investigations.

Metrics and reporting requirements

Effective reporting goes beyond listing threats. Reports should provide investigation details, explain potential business impact, and offer specific remediation guidance. Look for providers who prioritize findings based on actual risk to your organization rather than just technical severity.

Core detection metrics:

• Number and severity of threats detected: Shows the service's effectiveness at finding real issues (track monthly trend)

• Mean time to detect (MTTD): Measures how quickly threats are identified (target: <24 hours for critical threats)

• Dwell time reduction: Compare average dwell time before and after hunting program (benchmark: industry average is 10 days)

Coverage and scope metrics:

• Coverage percentage: Percentage of AWS accounts, Azure subscriptions, GCP projects, and Kubernetes clusters actively monitored

• Log source completeness: Percentage of critical data sources (CloudTrail, VPC Flow, K8s audit) successfully ingested

• Hunt frequency: Number of hypothesis-driven hunts completed per month

Outcome and maturity metrics:

• Validated incident rate: Percentage of hunts that uncover actual threats vs. false positives

• Identity-related findings: Percentage of threats involving compromised credentials or IAM misuse (typically 60-70% in cloud)

• Time to containment: Average time from detection to threat neutralization

• Repeat finding rate: Percentage of similar issues found in subsequent hunts (should decrease over time)

Investigation visualization:

• Attack timeline: Chronological view of attacker actions from initial access through lateral movement

• Investigation graph: Visual map showing relationships between compromised identities, accessed resources, and affected data stores

• Blast radius analysis: Clear visualization of which systems, accounts, and data were potentially impacted

These visualizations help security teams quickly understand complex attacks and communicate findings to executives. Ask providers to show sample investigation graphs from past engagements to evaluate their reporting quality.

Regular threat briefings and knowledge transfer sessions should be part of the service. These interactions help your internal team learn from the provider's expertise and improve your overall security capabilities.

Wiz Defend: Cloud-native threat detection and response

Wiz Defend provides cloud threat detection using behavioral analytics and expert-curated detection rules that significantly reduce false positives through cloud-native context and the Wiz Security Graph. The Wiz Security Graph automatically correlates cloud events, runtime data, and audit logs into attack timelines and investigation graphs. This automation reduces the manual work required for threat hunting while providing the context needed to understand complex attacks.

The platform includes a lightweight runtime sensor that monitors VMs, containers, and serverless functions with minimal performance overhead—typically under 2% CPU utilization. This sensor captures forensic evidence that hunters need to investigate threats thoroughly. Attack path analysis identifies chains of risk before attackers can exploit them, letting you fix vulnerabilities proactively.

Wiz Incident Response provides expert-led investigation, containment, and recovery during active security incidents, including targeted threat hunts to scope attack impact and identify persistence mechanisms across your cloud environment. The platform's code-to-cloud traceability lets hunters trace threats from runtime back to source code, enabling complete root cause remediation.

Ready to reduce dwell time and cut through alert noise with cloud-native detection and investigation? See how Wiz Defend combines agentless visibility, the Security Graph, and runtime threat detection. Book a demo!

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