Threat hunting foundations are shifting from reactive to proactive defense

At a glance

What this is: This is a threat hunting primer that argues proactive hunting only works when monitoring, intelligence, and collaboration are already in place.

Why it matters: It matters to IAM and security teams because the same visibility and investigation gaps that undermine hunting also hide credential abuse, privilege misuse, and compromised NHI activity.

By the numbers:

• Only 5.7% of organisations have full visibility into their service accounts.
• 80% of identity breaches involved compromised non-human identities such as service accounts and API keys.
• 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools.

👉 Read Expel's threat hunting guide for the operational foundation behind the framework

Context

Threat hunting is the practice of actively looking for malicious behaviour before alerting or response workflows catch it. That model depends on reliable telemetry, known-good baselines, and a security programme that can separate ordinary activity from abuse, which is why identity visibility and credential governance matter even when the article is framed as a general cyber operations guide.

For IAM, NHI, and PAM teams, the same conditions that make hunting effective also determine whether suspicious service account use, stolen API keys, or privileged access abuse can be detected quickly. A hunting programme that cannot see identity activity end to end will miss much of the behaviour it is meant to surface.

That makes this article typical of mature security guidance: it focuses on operational foundations rather than a specific product or incident. The underlying message is that proactive defence is only as strong as the telemetry and governance already in place.

Key questions

Q: Why do NHIs complicate threat hunting in SOC environments?

A: NHIs complicate hunting because service accounts, tokens, and workload credentials do not behave like human users and often have standing or excessive privilege. That means the same behaviour can look normal in one log source and risky in another. Effective hunts have to correlate identity, endpoint, and cloud telemetry to see the full abuse pattern.

Q: What problem does ownership attribution solve for service accounts and API keys?

A: It closes the gap between exposure detection and accountable remediation. Many organisations can find the secret, but not the human who introduced it, maintains it, or can safely replace it. Ownership attribution gives security teams a practical way to assign action without relying on informal knowledge that disappears during staff changes.

Q: What do security teams get wrong about threat hunting at scale?

A: They often treat hunting as a query-writing problem instead of a workflow design problem. Skilled analysts still matter, but scale depends on how easily teams can ask questions, enrich results, and validate findings without relying on a small group of platform experts.

Q: How do IAM and SOC teams work together during identity-focused threat hunting?

A: SOC should surface the anomaly, while IAM and PAM teams explain whether the account, role, or session should have existed in the first place. That division of labour reduces false positives and speeds containment. The key is a shared investigation path that preserves identity context from first alert to decision.

Technical breakdown

Continuous monitoring and behavioural baselines

Continuous monitoring is the collection and correlation of activity across endpoints, networks, cloud services, and identity systems in near real time. In threat hunting, the important step is not simply recording logs, but establishing what normal looks like so deviations can be tested as hypotheses. SIEM systems, endpoint telemetry, and network monitoring all contribute to that baseline. Without it, hunters chase noise instead of evidence, and identity abuse can hide inside ordinary authentication and authorisation patterns.

Practical implication: build baselines for service accounts, API keys, and privileged sessions before you expect hunting to find anomalous identity behaviour.

Intelligence-driven hunting and hypothesis testing

Threat hunting works best when it combines internal evidence with external intelligence. Internal sources include prior incidents, authentication patterns, and historical anomalies. External sources include threat feeds, peer reporting, and industry intelligence. The hunting process then turns that information into a testable hypothesis, such as whether a particular account is being used outside its normal hours or from an unexpected location. This is what makes hunting proactive rather than purely reactive.

Practical implication: give hunters both context and query access so they can validate identity-driven hypotheses instead of relying on static alert rules.

Collaboration across SOC, IR, and identity teams

Hunting is a cross-functional activity because no single telemetry source tells the full story. SOC analysts may see unusual behaviour, incident responders can validate scope, and IAM teams can explain whether the access path was legitimate. That shared context matters when the suspected activity involves service accounts, delegated access, or privileged sessions. The technical problem is not only detection, but stitching together identity context fast enough to decide whether the behaviour is malicious.

Practical implication: predefine escalation paths between SOC and IAM teams so identity anomalies can be triaged before attackers move deeper.

Threat narrative

Attacker objective: The attacker objective is to convert a single point of access into broader visibility, privilege, and control before defenders can detect the anomaly.

1. Entry begins when attackers gain foothold through compromised credentials, exposed secrets, or another initial access path that bypasses normal trust checks.
2. Escalation follows when the attacker uses that access to move through systems, probe for privileged sessions, and blend malicious activity into routine identity and application traffic.
3. Impact occurs when the attacker reaches data, administrative functions, or operational systems and uses the compromised access to steal, disrupt, or persist.

NHI Mgmt Group analysis

Threat hunting is only as effective as identity visibility. The article frames monitoring as a general security foundation, but the same logic applies directly to IAM and NHI governance. If teams cannot see service accounts, API keys, and privileged sessions with enough fidelity, hunting becomes retrospective guesswork rather than timely detection. The practitioner conclusion is simple: identity telemetry is not optional input to hunting, it is part of the hunting control itself.

Hypothesis-based hunting exposes a named control gap: behavioural blind spots in non-human access. In environments where machine identities outnumber people, anomalous use often looks like normal automation unless it is modelled against baseline behaviour. That creates a governance problem, not just a detection problem, because over-privileged or poorly scoped NHIs make suspicious activity harder to distinguish from expected service traffic. The conclusion for identity teams is to treat baseline quality as an access governance issue.

Detection-response latency: the longer it takes to connect suspicious behaviour to the owning identity, the more value attackers extract from valid access. Hunting programmes that operate without IAM, PAM, and SOC coordination tend to discover compromise after the attacker has already traversed the environment. The practical conclusion is that identity context must be available at the point of investigation, not reconstructed after the fact.

Threat hunting validates the case for Zero Trust, but only where identity evidence is operationalised. The article’s emphasis on baselines and corroboration aligns with NIST Cybersecurity Framework 2.0 and Zero Trust thinking, but those models fail if identity and access telemetry are sparse. For practitioners, the issue is not whether to hunt, but whether the environment can support evidence-driven decisions about access, trust, and containment.

What this signals

Threat hunting programmes are increasingly constrained by identity sprawl, because the visibility problem is now as much about service accounts and secrets as it is about endpoints or network traffic. When teams cannot reliably map who or what used a credential, the hunt loses evidentiary value and containment slows.

Detection-response latency: the operational gap between first suspicious use and identity attribution is becoming a measurable weakness in many environments. Teams that can tie telemetry back to the owning identity quickly will spend less time on false leads and more time on containment.

For identity programmes, the practical signal is that hunting maturity now depends on better access governance, better ownership metadata, and better correlation between SIEM data and IAM records. The same controls that reduce credential abuse also improve investigation quality.

For practitioners

• Instrument identity telemetry for hunting Collect authentication events, privilege changes, token use, and service account activity into searchable telemetry so hunters can test identity-based hypotheses, not just endpoint alerts.
• Baseline non-human account behaviour Define normal access windows, source systems, and command patterns for API keys, service accounts, and workloads so deviations are visible before they become incidents.
• Link SOC triage to IAM ownership Route anomalous identity findings to the teams that own the account, credential, or role so containment decisions can happen before lateral movement completes.
• Use intelligence to prioritise hunt hypotheses Feed prior incidents, threat feeds, and peer reporting into the hunt backlog so analysts focus on the identity abuse patterns most likely to appear in your environment.

Key takeaways

• Threat hunting only works when monitoring, intelligence, and collaboration are strong enough to turn anomalies into evidence.
• Identity visibility is now a hunting prerequisite because service accounts and credentials can mask malicious activity as routine automation.
• Teams that cannot connect telemetry to the owning identity quickly will detect abuse later and contain less effectively.

Key terms

• Threat Hunting: Threat hunting is the proactive search for signs of compromise that bypassed normal detection controls. It combines logs, telemetry, and investigator judgement to find hidden attacker behaviour before it becomes a larger incident or disrupts recovery.
• Behavior Baseline: A record of normal activity for a non-human identity, including typical consumers, resources, and actions over time. Baselines help security teams detect when an identity is being used in an unusual way and provide the context needed to enforce least privilege safely in dynamic environments.
• Identity Telemetry: Identity telemetry is the collection of signals generated by authentication, session, and access events across human and non-human identities. It becomes useful for governance when teams can baseline normal behavior and detect drift in source, privilege, or access frequency.

What's in the full article

Expel's full blog covers the operational detail this post intentionally leaves for the source:

• Practical examples of how its SOC uses cross-customer telemetry to spot threat patterns that a single environment may miss.
• The step-by-step structure of a hypothesis-based hunt, including how analysts validate or disprove an initial suspicion.
• Examples of the monitoring and log sources the article treats as foundational for an effective hunting programme.
• The collaboration model between SOC, incident response, and intelligence teams that supports faster investigation.

👉 Expel's full blog covers the monitoring, intelligence, and collaboration details behind the hunting model.

Deepen your knowledge

The NHI Foundation Level course, the industry's only accredited NHI security programme, covers NHI governance, IAM, and secrets management for practitioners who need stronger identity visibility. It helps security and identity teams connect access control decisions to operational detection and response.