AI Security & Agent Safety
Prompt injection, agent safety, tool permission boundaries, data leakage risks, red-team testing, and secure AI deployment patterns.
AI systems introduce new security boundaries: prompts can carry instructions, agents can call tools, retrieval systems can expose sensitive context, and automations can act on behalf of users. This track focuses on AI-specific security risks, agent safety, prompt-injection resistance, tool permission design, sandboxing, data leakage prevention, red-team testing, and secure deployment patterns for AI-enabled systems.
What this track helps with
Design safety boundaries for AI systems: prompt-injection resistance, tool permissions, sandboxing, data leakage prevention, red-team scenarios, and secure deployment patterns.
Common business situations
Recurring contexts where this track typically becomes useful.
- An agent can call tools, APIs, or internal systems.
- Sensitive data may appear in prompts, retrieval, logs, or model outputs.
- The company needs to test prompt injection, data leakage, or tool misuse risks.
- AI workflows require permission boundaries, sandboxing, or red-team scenarios.
- Leadership wants to know whether an AI system is safe enough to pilot.
Risks and constraints
Failure modes and constraints this track is built to surface and address.
- prompt injection
- unsafe tool access
- data leakage
- over-permissive agents
- weak sandboxing
- untested failure modes
Typical outputs
Generic deliverables a client could receive from this track. These describe the form of the work, not past engagements.
- Agent safety risk notes
- Prompt-injection threat model
- Tool permission recommendation
- Data leakage review checklist
- Sandbox boundary pattern
- Red-team scenario set
- Safety evaluation baseline
- Secure deployment backlog
Human track owner
One human specialist owns this track end-to-end and validates every client-facing recommendation.
Each track can be supported by focused AI-agent roles for research, comparison, evaluation, risk review, documentation, and implementation planning. The detailed AI-agent organization is shown on the track lead profile.
Tools currently under observation
No public Radar tools are linked to this track yet. This area is being prepared during the private build phase as Yuauri expands track-specific evaluations.
Use-case patterns connected to this track
No public use-case patterns are linked to this track yet. Security and safety patterns will be added as the Radar and implementation playbooks expand.
This track starts with one human owner and focused AI-agent support. Over time, mature tracks can grow into larger specialist units with additional contributors, playbooks, implementation patterns, and client delivery capacity.