auditing-the-lethal-trifecta
SolidFind where an AI agent becomes dangerous: the trust context in which access to private data, exposure to untrusted content, and an ability to send data out all coexist. Any two legs are usually safe; all three let planted content make the agent read secrets and exfiltrate them. Use when designing or reviewing a tool-using LLM agent, before granting it a new tool or data scope, or to judge whether a prompt injection is actually exploitable. Covers capability inventory, the three legs, kill-chain construction, and which leg to cut.
Install
Quality Score: 80/100
Skill Content
Details
- Author
- UnboundCompute
- Repository
- UnboundCompute/security-agent-skills
- Created
- 5 days ago
- Last Updated
- yesterday
- Language
- N/A
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
agent-threat-model
Threat-model an AI agent deployment against the lethal trifecta — private data, untrusted content, and an exfiltration vector — producing a per-capability matrix, a named architectural fix for every unsafe path, and a pre-launch checklist. Use before shipping an agent, when reviewing MCP server or tool permissions, when the user asks about prompt injection or data exfiltration risk, or when deciding whether an agent's capability surface is safe to expose.
auditing-ai-agent-permissions
Audit what an AI agent is actually allowed to do versus what its task needs. Covers excessive agency (tools, scopes, and autonomy beyond the job), missing human-in-the-loop gates on irreversible actions, over-broad credentials and their blast radius, sandbox and code-interpreter escape, unfiltered egress, and unbounded resource or spend (denial-of-wallet). Use when granting an agent a tool or scope, reviewing an agent's permission posture, or deciding which actions need approval. The model's restraint is not a control; permissions are.
red-teaming-multi-agent-systems
Test a system of multiple cooperating AI agents for attacks that exist only because agents message, spawn, and delegate to each other. Covers agent-to-agent injection (agent-in-the-middle), delegation abuse and recursive loops, orchestrator injection, confused-deputy across a trust boundary, identity spoofing between agents, capability collusion, and denial-of-wallet. Use when reviewing an orchestrator, a crew or swarm, agent-to-agent messaging, or any pipeline where one agent's output becomes another agent's input. Every internal edge where output becomes instruction is an injection channel.