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Assessing a Program

Put it into practice › Assessing a program

A program that adopts the framework will want to know how far it has come, and stakeholders such as auditors, regulators and leadership may ask the same question. This chapter describes the conformance model used to answer it: three cumulative levels, the evidence each requirement needs, and the rules for what a program may claim.

The levels are designed so that the first is achievable by a small team with no tooling budget. Level 1 asks whether a program knows what detections it has and why. Level 2 asks whether they are engineered and governed. Level 3 asks whether the program measures, validates and corrects itself.

Running example. The consent phishing detection's record in the reference implementation passes every automated check the framework defines. Conformance, however, is assessed for a program as a whole: a single well-documented detection does not make a conforming program.


The three levels

Levels are cumulative. L3 includes everything in L2, which includes everything in L1.

L1 Foundational L2 Managed L3 Optimised
Question it answers Do we know what we have and why? Is it engineered and governed? Is it measured, validated and self-correcting?
Typical team 1-3 people wearing several hats Dedicated detection function Detection function with platform support
Typical duration to reach One quarter Two to four quarters from L1 Two to four quarters from L2
Detection logic lives in Version control Version control, reviewed Version control, reviewed, deployed by pipeline
Testing Manual, documented Fixtures in CI Fixtures plus continuous adversary emulation
Metrics Precision reported Precision drives a real backlog Full metric set; health monitored automatically
Improvement Reactive, tracked Scheduled reviews enforced Drift detected automatically; deprecation routine

L1 Foundational

The claim: we know what detections we have, why each exists, and who owns it.

L1 is deliberately achievable by a two-person team with no budget. It requires no CI, no pipeline and no commercial tooling. It requires discipline.

An L1 program has:

  • Every detection in version control with conforming metadata (GOV-9, DAC-1)
  • Every detection traced to a business driver and its telemetry (GOV-1, GOV-2)
  • A named accountable owner per detection (GOV-5)
  • An anchored prioritization rubric in use (PLN-1)
  • Scope and success criteria on every request (PLN-6, PLN-7)
  • Telemetry confirmed before build (FEA-1)
  • A hypothesis, severity, confidence and benign causes recorded per detection (DET-1, DET-4, DET-6)
  • A response playbook per production detection (RSP-1)
  • A generated catalog (DEL-5)
  • Exceptions that are time-bound (IMP-5) and review dates that exist (IMP-8)
  • Precision reported, and the classical FPR not reported (MET-1)
  • False negatives reported as enumerated gaps (MET-5)

The single most common L1 failure is metadata held in the SIEM console rather than in version control. It feels equivalent. It is not: it cannot be diffed, reviewed, restored, or read when the platform is unavailable.

L2 Managed

The claim: our detections are engineered, reviewed and governed, and the feedback loop actually closes.

L2 adds, beyond L1:

  • Machine-readable traceability answerable in both directions (GOV-3, GOV-4)
  • A functioning detection council (GOV-6) and a documented RACI (GOV-8)
  • A defined expedited path with a Minimum Viable Detection definition (GOV-12, GOV-13, GOV-14)
  • Peer-reviewed changes with automated validation gating merge (DAC-2, DAC-3, DAC-4)
  • VAL recorded per detection (DET-2); alert disposition declared (DET-5)
  • Exceptions under version control (DET-8)
  • Positive and negative fixtures per production detection (DET-9)
  • Mandatory disposition on alert closure, auto-creating backlog items (IMP-2, IMP-3)
  • Change classification before work begins (IMP-4)
  • Reviews that cover all seven required dimensions (IMP-11)
  • Regression testing before deployment (IMP-13); controlled deployment (IMP-14)
  • Alert forecasting before activation (DEL-2); defined rollback (DEL-4)
  • A deprecation path that is actually used (IMP-16, IMP-18, IMP-19)
  • Precision thresholds that trigger backlog entry (MET-2)

The single most common L2 failure is the feedback loop. Teams implement everything else and leave alert disposition optional. It then does not happen, and IMP-3 cannot function because there is no input.

L3 Optimised

The claim: we know when our detections stop working, and we find out from instrumentation rather than from an incident.

L3 adds, beyond L2:

  • Fixture tests and automated deployment from reviewed source (DAC-5, DAC-6)
  • Drift reconciliation against the platform (DAC-7) and executable rollback (DAC-8)
  • Telemetry cost assessed at the feasibility gate (FEA-3); emulation before logic (FEA-4)
  • Robustness tiering actively managed (DET-7); exception boundary fixtures (DET-10)
  • Adversary emulation before production, recorded (DET-11); non-functional testing at production scale (DET-12)
  • Playbooks exercised jointly (RSP-4); automation with defined failure modes (RSP-5)
  • Staged rollout with canary observation (DEL-3)
  • Automated drift detection (IMP-12); protected improvement capacity (IMP-10)
  • Detection debt below 15% and reported monthly (IMP-9)
  • Change advisory integration as an improvement trigger (IMP-20)
  • Confidence-weighted coverage reporting (MET-3); automated health monitoring (MET-4)

The single most common L3 failure is validation freshness. Programs build the emulation capability, run it once at deployment, and never schedule it. Detection drift then accumulates invisibly, which is precisely the failure L3 exists to prevent.


What may be claimed

CNF-1. A conformance claim MUST state all four of: the level, the specification version, the assessment date, and the scope of the assessed environment.

A valid claim:

Conforms to Detection Engineering Framework v2.1.1 at Level 2, assessed 2026-09-01, scope: corporate IT estate and Microsoft 365 tenant. Excludes OT networks and the acquired subsidiary environment.

An invalid claim:

DEF compliant.

CNF-2. A program MUST NOT claim a level unless every requirement at that level and below is met. There is no partial credit at a level. Partial progress is reported as "L1 conformant, L2 in progress (34 of 41 requirements met)".

CNF-3. Scope exclusions MUST be stated explicitly. A claim that silently excludes half the estate is a false claim.

CNF-4. A conformance claim MUST be reassessed at least annually, and MUST be reassessed after any material change in platform, team structure or scope.


Assessment

Self-assessment

The instrument is in assessment/. Each requirement is scored:

Score Meaning
met Implemented, and evidence exists
partial Implemented for some detections or some environments only
not-met Not implemented
n/a Not applicable; a written justification is REQUIRED

CNF-5. A requirement scored met MUST have identifiable evidence. "We do that" is not evidence. The instrument names acceptable evidence for each requirement.

CNF-6. n/a MUST carry a written justification and MUST be approved by the detection council. Unjustified n/a scoring is the most common way self-assessment becomes theatre.

Evidence types

Evidence type Example
Artifact A conforming metadata file in the repository
Execution A CI run showing the validation gate passing
Record A council minute approving a deprecation
Query A traceability query returning detections for a given driver
Observation An assessor watching an analyst disposition an alert

Artifact and execution evidence are strongest because they are hard to fake and cheap to re-verify. A conforming program should be able to satisfy most of the instrument by pointing at its repository and its pipeline.

Independent assessment

CNF-7. An L3 claim SHOULD be validated by an assessor independent of the detection engineering function. Self-assessment at L3 is acceptable but weaker, because the requirements that matter most at L3 are the ones a team is most likely to rate generously.


Trajectory, not destination

Level is a snapshot. A program at L2 with detection debt falling and coverage rising is healthier than a program at L3 with debt rising and validation stale.

CNF-8. Conformance reporting SHOULD include trend, not only level. The minimum useful trend set is: detection debt percentage, validation freshness, median precision, and count of detections deployed via the expedited path that have not been brought to full conformance.


On not skipping L1

The most frequent adoption failure is a team at L1 maturity attempting to implement L3 controls, because L3 is what conference talks describe. They build a CI pipeline before they have consistent metadata, and the pipeline has nothing meaningful to validate.

Build the metadata first. A repository of conforming detection records with no automation at all is more valuable than an automated pipeline operating on inconsistent data, because the former can be automated later and the latter must be redone.


In brief

  • There are three cumulative levels: L1 Foundational, L2 Managed and L3 Optimised. A level is reached only when every requirement at that level and below is met.
  • Every requirement scored as met needs identifiable evidence, and anything scored as not applicable needs a written justification.
  • A valid claim states the level, the specification version, the assessment date and the scope.
  • Trend matters as much as level. A program improving at L2 may be healthier than one declining at L3.

Requirements in this chapter

The rules for claims and assessment, CNF-1 to CNF-8, appear in the sections above. The requirements being assessed are listed by level in the specification.

What comes next

Assessment is easier with the right starting material. Tools and templates lists the intake forms, schemas, reference implementation and self-assessment instrument that accompany the framework.