Autonomous System Safe-State
Produces the attested safe-state decision the control system executes when drift is detected in autonomous operations. Designed for systems where failure modes must be predictable and auditable.
Target System.
Autonomous vehicles (UAV, UGV, USV), robotic systems, AI-driven defense platforms, and any system operating with delegated authority where safe degradation is mandatory. Applicable to both fully autonomous and human-on-the-loop configurations.
Threat Model.
- AI model drift during autonomous operations
- Unauthorized mission parameter changes
- Sensor spoofing or manipulation attacks
- Communication link compromise or jamming
- Adversarial inputs triggering unsafe behavior
Integration Points.
Mission Policy Binding
Cryptographically bound operational envelope
Continuous Attestation
Runtime measurement at configurable intervals
Safe-State Profiles
Attested decisions the control system executes (RTB, hover, shutdown)
Evidence Chain
Tamper-evident audit trail for post-mission analysis
Safe-State Profiles.
RETURN_TO_BASE
Trigger: Link loss > thresholdAttests the decision to navigate to predetermined safe coordinates
HOLD_POSITION
Trigger: Mission parameter driftAttests the decision to maintain current position and altitude
CONTROLLED_DESCENT
Trigger: Critical system anomalyAttests the decision to execute a safe landing sequence
EMERGENCY_SHUTDOWN
Trigger: Integrity failureAttests the decision to power down with state preservation
Decision Properties.
Deterministic Decisions
Policy maps each safe-state decision before runtime
Continuous Monitoring
Attestation intervals set in the sealed artifact
Outcomes.
Sample bundle
Autonomous safe-state variant with mission simulation