CISO • ZERO TRUST

    Zero Trust Health

    A health check across identity verification, device posture, and segmentation policy enforcement—measured continuously.

    What it shows

    This view answers: “Are we actually operating as Zero Trust today?” It surfaces verification failures, posture drift, and segmentation gaps before they become incidents.

    How it’s calculated

    • Identity verification success (passwordless/MFA, hardware-bound identity, session assurance).
    • Device posture signals (secure boot, OS baseline, certificate validity, key lifecycle).
    • Policy enforcement coverage (least privilege, micro-segmentation, conditional access rules).
    • Exception handling (temporary waivers are tracked and time-bounded).

    What to do next

    1. 1
      Fix the biggest failing category first
      (e.g., expired certificates in a SCADA zone).
    2. 2
      Close MFA gaps
      for contractors and privileged accounts; remove “shadow admin” access.
    3. 3
      Review over-privileged service accounts
      and rotate secrets/keys on schedule.
    4. 4
      Automate renewals
      (certs/keys) and enforce “deny by default” for unmanaged devices.

    KPIs to watch

    Health %
    Verified
    Failing sessions
    count
    Top gap
    MFA / cert / policy

    Why this matters to a CISO

    AI only works if it’s trustworthy
    If models drift or confidence drops, you’re flying blind. This keeps the AI layer honest.
    Drift is normal in OT
    New firmware, new shifts, new processes—all cause drift. You need to detect it early before it erodes detection quality.
    Confidence drives automation
    You can’t let AI auto-contain based on shaky confidence. This metric ensures automation stays aligned with risk appetite.
    Feedback loops improve accuracy
    Every analyst decision sharpens the models. This closes the loop between human intelligence and machine learning.
    Reference UI Screenshot
    Zero Trust Health screenshot