Automating CMMC Level 5 Threat Hunting Evidence

CMMC Level 5 represents a demanding security posture for organisations that handle Controlled Unclassified Information (CUI) in the US defence supply chain. It expects mature, continuously improving protection against advanced persistent threats, with proactive threat hunting and rapid remediation forming part of the operating model. For an Australian supplier, the challenge is rarely a single audit exercise. It is the ability to prove that security decisions, investigations and corrective actions happen consistently across people, platforms and suppliers.

Manual screenshots and retrospective evidence do not provide a reliable picture of this activity. They may show that a control existed on the day a document was created, but they cannot easily demonstrate how a team identified suspicious behaviour, investigated it, contained the risk and verified that the weakness stayed fixed. Automated evidence collection connects technical activity to accountable processes and creates an audit trail that can be reviewed as the environment changes.

A practical programme combines security information and event management, endpoint telemetry, cloud configuration data, ticketing, identity records and software delivery pipelines. The aim is to produce trustworthy evidence with minimal disruption to engineering teams. When the evidence is collected continuously, security leaders can see whether threat hunting is effective long before a CMMC assessment or a customer due-diligence request arrives.

What Level 5 Evidence Needs To Prove

At the highest CMMC maturity level, evidence should show an active capability rather than a collection of policies. The organisation needs to demonstrate that it understands relevant adversary behaviours, searches for indicators of compromise, analyses unusual activity and improves its defences as new intelligence emerges. A written threat-hunting procedure is useful, but it is stronger when linked to hunt schedules, query histories, case records, analyst decisions and resulting changes to controls.

Evidence also needs context. A log entry alone may confirm that an event occurred, while an investigation record explains its significance. Automated systems should associate the event with the affected asset, user, data classification, time zone, severity, analyst, response action and closure criteria. This creates a defensible chain from detection through remediation, which is important when an assessor tests whether practices operate consistently across the environment.

The same principle applies to vulnerability management. A scan report may identify a critical issue, but mature evidence shows when it was prioritised, who owned it, which compensating control applied, when it was fixed and how the fix was validated. For Level 5, the record should also capture lessons learned and whether the organisation adjusted its detection logic, architecture or operating procedures.

Build A Continuous Hunting Evidence Pipeline

The evidence pipeline should begin with authoritative sources rather than documents copied into an audit folder. Useful sources include endpoint detection and response platforms, identity providers, firewall and DNS logs, cloud control planes, vulnerability scanners, source control systems and service management tools. Each source should have a defined owner, retention period, collection method and integrity safeguard.

Normalisation is essential when a business operates across Sydney, Melbourne, Brisbane or overseas regions. Systems often record time differently, use inconsistent asset names or assign different severity labels to similar incidents. A central evidence model can standardise timestamps to UTC while retaining local time for operational teams, map assets to business services and connect identities to approved roles. This reduces the risk of an assessor receiving contradictory records from separate systems.

Automation should preserve the original record and maintain an immutable or access-controlled history of changes. Hashing, signed exports, restricted permissions and retention policies can help establish that evidence was not casually altered. Collection failures should generate alerts too. A missing log source or expired API token can create a material evidence gap, and the platform should treat that gap as a security issue rather than silently continuing.

A useful workflow might run a scheduled hunt for suspicious PowerShell activity, unusual authentication patterns or unexpected access to CUI repositories. The results can automatically create a case, assign an analyst, attach relevant telemetry and track the decision to close, escalate or remediate. The audit record then reflects the real investigative process instead of requiring staff to recreate it months later.

Connect Cloud Security With Engineering Workflows

Australian companies frequently operate hybrid environments, with workloads in public cloud regions, private data centres and SaaS platforms. This makes cloud configuration drift a central concern. A storage policy, identity permission or security group can change within minutes, so a quarterly review may miss the period in which CUI was exposed. Continuous checks should compare the live state with approved baselines and retain evidence of both exceptions and corrective action.

A cloud protection approach can bring infrastructure configuration, workload posture and compliance signals into the same operating view. This is particularly valuable when a development team deploys services through infrastructure as code, because the system can associate a change with its commit, approval, pipeline result and subsequent runtime state.

Threat hunting should reach into the software delivery lifecycle. A suspicious dependency, exposed secret or risky container setting can become an entry point for an attacker before a production alert appears. Security gates can evaluate pull requests and build artefacts, while post-deployment monitoring checks whether the running service matches its approved configuration. Exceptions need an owner, an expiry date and a documented business reason rather than a permanent bypass.

The objective is not to make every developer act as a security analyst. It is to place evidence capture where work already occurs. A linked ticket, pull request, deployment record and verification result can prove that a weakness was handled through an approved process. This reduces duplicate reporting and gives security teams a more complete view of remediation performance.

Make Hunting And Remediation Accountable

Automation is most effective when responsibilities are explicit. A hunt should define the hypothesis, data sources, search period, expected result and escalation path. A remediation record should state the affected system, risk rating, accountable owner, target date, interim safeguard and validation method. These fields allow dashboards and assessment packages to be generated from operational records rather than assembled manually.

Teams can use a small set of repeatable evidence categories to keep the process consistent:

• Hunt hypothesis, query, analyst and review date
• Affected asset, identity, data set and event timeline
• Escalation decision, containment action and incident reference
• Lessons learned, control update and validation result

The evidence should show that remediation was completed effectively, not simply that a ticket was marked closed. Verification might include a rescanned host, a retested identity permission, a replayed detection rule or a review of fresh logs. Where a vulnerability cannot be fixed immediately, the record should show the compensating control and the date on which the exception will be reconsidered.

A second set of operational measures can help leaders identify weaknesses in the programme:

• Mean time from hunt signal to analyst triage
• Percentage of high-risk findings with an accountable owner
• Age and recurrence rate of accepted exceptions
• Percentage of fixes validated by independent evidence

These measures should be interpreted carefully. A high number of alerts may indicate noisy detection rather than strong hunting, while a short closure time may hide weak validation. Trends, sampling and analyst review provide the context needed for a credible CMMC assessment.

Adapt The Programme To Australian Operations

CMMC applies to organisations in the US defence industrial base, yet Australian suppliers and technology partners may encounter its requirements when contracts involve US defence information. They may need to align CMMC obligations with the Australian Government Information Security Manual, the Essential Eight and requirements connected to the Defence Industry Security Program. Mapping should identify where frameworks overlap and where a US contract demands more specific evidence.

Privacy and data-handling obligations also matter. The Privacy Act 1988 and Australian Privacy Principles can affect how security telemetry, employee identifiers and investigation records are collected, accessed and retained. A threat-hunting platform should apply role-based access, minimise unnecessary personal information and document the purpose of monitoring. If evidence is stored outside Australia, procurement and privacy teams may need to assess cross-border disclosure, contractual safeguards and customer requirements.

Local operating patterns influence the workflow. A Sydney-based security team may hand over investigations to engineers in Melbourne or Perth, while a supplier in Adelaide may coordinate with US stakeholders across a large time difference. Automated timestamps, clear ownership and escalation rules reduce ambiguity during these handovers. The same records support an assessor in the US and an internal team working during Australian business hours.

Data residency is a commercial concern as well as a legal one. Australian customers in defence, healthcare and critical infrastructure may ask where logs are processed, who can access them and how long they remain available. Evidence architecture should therefore document hosting locations, subprocessors, encryption, retention and deletion. These details can strengthen customer trust while supporting the broader compliance case.

Compare Evidence Collection Approaches

Organisations often begin with spreadsheets, shared drives and manually exported screenshots because these tools are familiar. They can support a small, stable environment, but they become fragile when evidence comes from multiple clouds, frequent deployments and distributed teams. Manual methods also make it harder to identify gaps before an assessment, especially when an investigation occurred but its supporting records were not preserved.

A continuous assurance platform can connect control requirements with live evidence and workflow activity. It should still allow human judgement: analysts decide whether a signal is malicious, system owners approve risk acceptance and security leaders review trends. Automation handles repeatable collection, correlation, reminders and reporting, giving specialists more time for analysis and threat-led improvement.

Evidence approach	Strength	Main weakness	Fit for Level 5
Manual screenshots and spreadsheets	Quick to start and easy to understand	Stale, fragmented and difficult to validate	Limited for continuous hunting
Periodic exports from security tools	More technical detail and better repeatability	Gaps can remain between collection periods	Useful for selected controls
SIEM and ticketing integration	Connects events, investigations and actions	Requires careful tuning and ownership	Strong foundation
Continuous assurance with DevSecOps integration	Links live controls, code changes and remediation proof	Needs sound data governance and configuration	Best fit for ongoing readiness

The operating model should include regular evidence reviews, access checks and tests of collection failures. Security teams can sample closed cases, confirm that retained data is readable and verify that a remediation record points to independent validation. Using DevSecOps assurance helps connect governance with build and deployment activity, so the evidence reflects how systems are actually changed.

For an Australian organisation supporting US defence work, the strongest result is a repeatable record of proactive defence: a relevant hunt was planned, reliable data was collected, a qualified person assessed the findings, remediation was assigned and the outcome was verified. That record supports CMMC Level 5 readiness while improving everyday resilience across cloud, identity, endpoint and engineering environments.