Diagnosing Silent Device Disconnects and Security Posture

Because aggregate ingress looks normal, the investigation must be per-device, not fleet-wide:

1. Confirm the disconnect signal. Use device connection state events / lifecycle events and the device's last activity timestamps to identify when each of the 300 stopped. Look for a common timestamp cluster (suggests a shared cause such as a certificate or token event) versus scattered times (suggests local network or device faults).
2. Check credential expiry. SAS tokens generated at manufacture with 365-day expiry will fail at expiry; a cluster near the manufacture anniversary is a strong signal. Verify by checking token expiry for affected devices.
3. Check Wi-Fi/network telemetry for the affected bedsides - AP association, RSSI, roaming behavior - since hospital Wi-Fi with many devices can exhibit sticky-client or DHCP exhaustion issues.
4. Check device-side logs for TLS handshake failures, DNS failures, or 401/403 responses from the hub.
5. Check hub-side diagnostics for authorization failures and connection errors per device.

Judgement: normal aggregate ingress can mask a subset of failing devices. The method is to segment by time-of-failure and by error class, then test the leading hypothesis (token expiry vs. network) against evidence.

Plaintext long-lived SAS tokens in config files are the core weakness: anyone with the device can read and replay the token until expiry, and 365 days is a long window.

Improvements:

• Per-device identity with short-lived, renewable credentials. Use DPS with individual enrollments and either X.509 per-device certificates or TPM-backed attestation where hardware allows. Short-lived SAS tokens can be issued by a trusted service and renewed, shrinking the replay window.
• Do not store long-lived secrets in plaintext. Protect credentials with a hardware secure element or TPM, or at minimum an OS-protected keystore. Remove connection strings from config files.
• Revocation path. Ensure a stolen device can be disabled quickly - disable the device identity in the registry and revoke its certificate or enrollment so it cannot reconnect.
• Least privilege. Scope SAS policies narrowly; do not give devices registry-write or service permissions.

Judgement: replay resistance comes from short-lived, hardware-bound, revocable credentials plus a tested disable procedure - not from rotating a long-lived shared string.

Detection options:

• IoT Hub diagnostic logs and connection events routed to Log Analytics: track connection/disconnection frequency, source IPs, and authorization failures per device. A device connecting from two distant IPs in a short window, or many failed auth attempts, is anomalous.
• Microsoft Defender for IoT (where licensed) can surface anomalous behavior and recommendations, but its detections are probabilistic and should be tuned.
• Custom analytics: baseline each device's normal connection cadence and alert on deviation.

Limits to state honestly:

• IP geolocation is unreliable behind NAT and hospital egress proxies; many devices may share one egress IP, so IP-based anomaly detection has high false-positive rates.
• Replay within the token's validity may look like normal traffic if the attacker mimics cadence; detection depends on concurrency checks (same device ID connected twice) which IoT Hub supports as a signal but not as strong authentication.
• Log retention and cost constrain how far back you can investigate.

Judgement: combine identity hardening (so replay is short-lived) with detection as defense-in-depth, and acknowledge detection cannot fully compensate for long-lived plaintext credentials.