Trent AI Security Engineer

Trent is an AI Security Engineer embedded in your team that you can interact with like an engineer. It starts by mapping what you are actually running and how it fits together: application code, infrastructure code, configurations, agents and automations, and the data and trust flows between them.

What you get back is concrete, inspectable work: an inventory graph, architecture and data-flow diagrams, a threat model, and a prioritized findings list with the reasoning behind each one.

It finds what is exploitable, proposes context-aware fixes, and can map the compliance frameworks you answer to, like SOC 2 and NIST, onto the controls and tools you actually run, surfacing the gaps. It works across your entire stack, including the AI agents and automations that traditional security tools were not designed for.

For agentic workloads it reconstructs your architecture from the real code, inventories every agent, tool, skill and MCP server by what it can actually do (Read, Write, Execute, Egress), traces the attack chains between them, grades your posture, and shows which fix breaks a path. The analysis is grounded in code, not a live exploit or pen test.

The goal is not to replace your security team. Trent sits above the scanners you already own, judging each finding for real risk, and a person reviews every recommendation before anything is applied. It connects to Claude Code, OpenAI Codex, Lovable, Cursor, GitHub Copilot and other MCP-compatible clients, and to OpenClaw through the trentclaw skill.

Assessments start from a GitHub repository, a live web URL, or a code upload. It deploys in public cloud, your VPC, or on-premises.