Proposed capability · FailSafe HIVE

Agentic red teaming for the full robotic mission.

Assess whether authorized intent holds as a mission moves across applications, fleet management, robots, remote operators, and surrounding operational technology.

A robot can execute valid commands and still produce an unauthorized or unsafe physical outcome. HIVE examines the business logic, trust decisions, and safety boundaries that shape what the system can do in the real world.

Mission-level assurance

Follow intent across every handoff.

Security failures can emerge between independently managed systems, when a destination changes after approval, a canceled command is replayed, or an external system trusts fleet membership without checking the active mission.

HIVE assesses the complete operational workflow and tests whether the system continues to enforce the original intent at each transition, rather than examining a robot endpoint in isolation.

  1. 01Request
  2. 02Authorization
  3. 03Scheduling
  4. 04Fleet orchestration
  5. 05Endpoint execution
  6. 06Environment interaction
  7. 07Completion and audit

Coverage

Test the systems and decisions around the machine.

HIVE coverage spans the digital and physical boundaries that can change a mission's authority, state, or impact.

Mission logic & authorization

Test whether permissions stay bound to the intended robot, mission, action, place, and time.

  • Task, destination, payload, or zone changes
  • Valid credentials used for an unintended action
  • Cancellation, reassignment, and completion races

Trust boundaries & identity

Examine how identity and authority move between robots, operators, fleet services, and facilities.

  • Robot, operator, service, or facility identity substitution
  • Inherited trust and cross-robot state leakage
  • Integrations acting across security domains

Safety & operating boundaries

Validate policy enforcement between AI, people, control systems, and physical actuation.

  • Geofences, restricted zones, and human-approval gates
  • Emergency, offline, recovery, and remote-control authority
  • Perception, location, or state used at a safety boundary

Endpoints, control planes & supply chain

Assess robot interfaces and the systems that enroll, update, administer, and operate a fleet.

  • ROS 2/DDS, MQTT, APIs, and remote-operations paths
  • Enrollment, certificates, service accounts, and maintenance interfaces
  • Software, model, OTA provenance, and rollback controls

Resilience & real-world impact

Study what happens when connected systems lose, disagree about, or recover from critical state.

  • Connectivity, positioning, time, or cloud-service loss
  • Conflicting state across robots, fleet services, and facilities
  • Robot containment, attribution, and recovery

Technical approach

Model, test, and trace the outcome.

01

Model the mission

Build a machine-readable mission and trust-boundary model from architecture, source code, APIs, policies, message schemas, and observed behavior.

02

Prioritize reachable outcomes

Generate and prioritize adversarial hypotheses around the physical and operational outcomes reachable through the system.

03

Validate in stages

Progress through code and configuration analysis, protocol emulation, simulation, hardware-in-the-loop, and approved non-destructive testing where authorized.

04

Correlate evidence

Connect application, identity, fleet, endpoint, and OT events into a causal trace, then turn relevant scenarios into regression tests after system changes.

Safety envelope

Physical testing stays controlled and authorized.

Physical tests require an explicit authorization and safety envelope. It defines permitted targets and action classes, impact limits, abort conditions, and independent emergency-stop authority.

Where authorized, physical work is non-destructive and conducted on a controlled route or workcell. Destructive and uncontrolled actions remain default-deny. Testing can stop at analysis, emulation, simulation, or hardware-in-the-loop when those stages provide the agreed evidence.

Evidence & outputs

Findings tied to operational impact.

Events across applications, identity, fleet management, endpoints, and OT are correlated into a causal trace. Scenarios are classified as prevented, detected, contained, recovered, or succeeded.

  • Mission, asset, and trust-boundary model
  • Reproducible attack traces tied to physical or operational impact
  • Business-logic, authorization, endpoint, and control-plane findings
  • Validation of trust, safety, and policy boundaries
  • Degraded-mode and recovery analysis
  • Remediation, verified retests, and residual-risk analysis

Initial evaluation scope

Start with one representative mission.

A proposed starting scope covers one mission, one robot class, and one external integration, such as a door, lift, charger, workcell, or payload system. Scope and test stages are agreed with the system owner before testing begins.

Questions & answers

Frequently asked questions

Direct answers about FailSafe HIVE, embodied AI security assessment coverage, and physical testing safeguards.

HIVE is a proposed agentic red-teaming capability for robotic systems, autonomous fleets, and embodied AI. It assesses whether the authorized mission remains enforced across applications, fleet management, robots, remote operators, and connected operational technology.

Coverage can include mission authorization and business logic, robot and operator identity, trust boundaries, safety policies, endpoints, fleet control planes, software and model supply chains, external integrations, and behavior during degraded operation.

Testing can progress from architecture and configuration analysis to protocol emulation, simulation, hardware-in-the-loop, and approved non-destructive physical testing. Any physical test requires an explicit authorization and safety envelope, including permitted targets, impact limits, abort conditions, and independent emergency-stop authority. Destructive and uncontrolled actions remain default-deny.

Outputs can include a mission, asset, and trust-boundary model; reproducible attack traces tied to operational or physical impact; findings across business logic, authorization, endpoints, and control planes; degraded-mode and recovery analysis; and remediation, retest, and residual-risk evidence.

The proposed initial scope is one representative mission, one robot class, and one external integration, such as a door, lift, charger, workcell, or payload system. Final scope and any physical testing require explicit authorization and safety constraints.