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    SIEM Detection Engineering

    Are your SIEM rules actually validated?

    Detection engineering is only as valuable as the testing behind it. A SIEM rule that has never been fired against a real adversary technique is a hypothesis, not a control. SCYTHE turns detection engineering from a build-and-hope process into a build-test-measure program.

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    SCYTHE — Detection Engineering Validation
    Overview SIEM Validation EDR Results MITRE Coverage
    Detection Rule Validation Results
    APT29 — COZY BEAR
    Detected
    7
    of 14 rules fired
    Missed
    5
    no alert generated
    Partial
    2
    wrong severity
    Coverage Score
    50%
    ▼ 12pts vs last run

    30–50%

    avg detection coverage before SCYTHE

    90 days

    to meaningful coverage improvement

    100%

    of regressions surfaced before attackers find them

    The SIEM Problem

    The detection engineering problem no one talks about

    Security teams invest enormous effort writing and tuning SIEM detection rules. The problem is that most detection rules are never validated against actual adversary behavior in the specific environment they're supposed to protect. Three specific failure modes affect almost every detection engineering program:

    Untested assumptions

    Detection rules are written based on what adversary behavior should look like, not what it actually looks like when executed against this specific stack, in this specific configuration, at this specific point in time.

    Stale coverage

    Infrastructure changes, tool upgrades, and new data sources continuously alter the detection landscape. A SIEM rule that relied on a specific log field may silently break when the source application updates its logging format.

    No measurement

    Most detection engineering programs have no way to measure coverage density — what percentage of relevant adversary techniques the detection library actually catches. Without measurement, improvement is invisible and regression is undetected.

    WHY gaps exist

    How SCYTHE Supports Detection Engineering

    SCYTHE integrates directly into the detection engineering workflow, providing the adversary emulation infrastructure that lets teams validate, measure, and continuously improve their SIEM detection logic.

    Validate detection rules against real technique execution. Regression-test after every change. Measure MITRE coverage density. Test new CTI-driven detections before go-live. Validate detection logic, not just rule syntax.

    Ready to see what your controls actually catch?

    Book a 30-minute demo. We'll run a live emulation against a technique relevant to your industry.
     
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    The Solution

    Other platforms test whether your detections exist. SCYTHE tests whether they work.

    Most detection engineering programs end at deployment. SCYTHE starts there — continuously validating that your rules fire against real adversary behavior, in your actual environment, against your actual log sources.

    1
    Build

    Write detection rules based on threat intelligence, adversary research, and ATT&CK coverage gaps from your last SCYTHE run.

    Map rules to MITRE ATT&CK techniques
    Prioritize gaps from prior run
    Use CTI-driven threat context
    Rule Authoring
    →
    2
    Validate

    Run SCYTHE emulation of the target technique in your production environment. Confirm the rule fires with actionable field mappings.

    Execute real technique against live stack
    Confirm alert fires with correct fields
    Verify severity and routing logic
    Adversary Emulation
    →
    3
    Deploy

    Push validated rules to production with confidence they work. SCYTHE tracks each rule with its full test history attached.

    Deploy with validated test evidence
    Log rule version and test timestamp
    Tag rule as production-validated
    Confident Deployment
    →
    4
    Measure & Regress

    SCYTHE re-runs the full validation suite on schedule. Any regression, passed tests now failing, surfaces as an immediate finding.

    Scheduled continuous re-validation
    Regression alerts on rule failure
    MITRE coverage metrics over time
    Continuous Coverage

    Supported SIEM Platforms


    Don't see your SIEM? SCYTHE's flexible deployment and API-based integration supports most enterprise SIEM platforms. Contact us to discuss your environment.

    COMMON QUESTIONS

    Frequently asked questions

    How does SCYTHE differ from using Atomic Red Team for detection testing?

    Atomic Red Team provides individual technique test scripts that require manual operation and produce no structured output for measurement. SCYTHE provides automated scheduling, bidirectional SIEM integration, coverage measurement against MITRE ATT&CK, regression tracking, and an enterprise-grade reporting layer — plus managed service options for teams without dedicated detection engineering staff.

    Can SCYTHE test detection rules without alerting our SOC?

    Yes. SCYTHE integrates with SOAR and ticketing platforms to tag or suppress alerts during controlled testing windows. You define the test scope and period so your SOC team can distinguish validation activity from real detections.

    How does SCYTHE handle multi-vendor log sources?

    SCYTHE validates the full detection chain from technique execution through log generation through SIEM parsing through alert correlation. If a detection gap exists due to a log source normalization issue rather than a rule logic issue, SCYTHE identifies where in the chain the failure occurs.

    What MITRE ATT&CK coverage can we expect to measure?

    SCYTHE customers typically discover they have effective detection for 30–50% of relevant MITRE ATT&CK techniques before starting continuous validation — and improve that coverage meaningfully over the first 90 days as regressions are identified and new detections are validated.

    Build detection rules with confidence they'll actually fire.

    See how SCYTHE integrates into your detection engineering workflow and gives your team measurable, continuous coverage visibility.