AI Agent Security in One Continuous Loop
Most teams can’t afford a principal security engineer. The ones that have one are stretched and cover more than 79 developers. Trent is the security expert that’s always there. Continuously learning, staying current as the stack evolves, and scaling with your team without adding headcount.
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Agentic AI Security Platform Leader
One Project. Understand, Plan, Secure.
Your work lives in a single project with three parts, in the order a security engineer actually works.
Understand shows the Context Trent is working from, the Architecture it has mapped, and the Inventory of components it has found.
Plan turns that understanding into the security Requirements Trent holds your system to.
Secure connects Threats and Posture to Tasks and Reports.
Attack Chains: From a Backlog to a Plan
Findings tell you what is wrong. Attack Chains lay out a possible path through the AI-agent components Trent found: its premise, its confidence, and a numbered path mapped to MITRE ATLAS.
Blocking controls show where the path already stops. Linked tasks show which fixes break it. Your team can judge a whole path and put its effort into the fixes that break it, instead of weighing every weakness on its own.
Built to Be Corrected, Not Blindly Trusted
An AI Security Engineer who cannot be overruled is not much use. Challenge a severity and apply a regrade in place, with an explanation of how Trent graded it originally. Edit draft requirements. Make task decisions. Corrections carry into the next scan, and past runs stay as snapshots, so today’s changes never rewrite yesterday’s record.
Every finding links back to its evidence and forward to the task that closes it. After each rescan, the Report changelog shows exactly what moved.
Trent Is Beside the Work
Trent sits beside every project page and knows what you are looking at. Open a finding and ask a follow-up without explaining which one you mean. Chat is another way to use the product, not a replacement for it: Architecture, Requirements, Threats, and Tasks remain visible records your team can inspect and change directly.
Specialized Agents. One Continuous Loop.
Trent AI’s Agentic Security Solution is a single, unified offering. Rather than a patchwork of disconnected security tools, it delivers one self-reinforcing system composed of specialized agents, each doing one job exceptionally well, and every cycle through the system making the next one smarter.
Continuously observes your agents, code, infrastructure, and dependencies, learning where to look and reducing noise over time.
Classifies signal vs. noise, assesses business impact, and prioritizes by real risk rather than static rules.
Patches vulnerabilities, opens pull requests, adjusts configurations, and validates that fixes actually work.
Tracks trends, benchmarks against standards, and forecasts where risk will emerge next.
The Same Engineer. Wherever You Build.
The agent loop runs the same way everywhere. What changes is how you connect and where fixes land. Start wherever makes sense for your team.
Connect a GitHub repository, upload code, or add your agent definitions. Trent learns your architecture and keeps scanning as your project changes.
Install the trentclaw skill inside OpenClaw. Assessments run in your agent runtime and findings render right in your agent’s chat.
Trent’s MCP server runs inside Claude Code, OpenAI Codex, Cursor, and most MCP-capable editors. Scan, prioritize, and fix without leaving your coding environment.
Trent reads more than application code. Infrastructure code, configurations, scripts, and automations like GitHub Actions feed one continuously unified context layer, so they get understood and secured as parts of one system, not as separate tool outputs you are left to reconcile.
No code yet? Add design docs, product specs, compliance requirements, or agent files, or chat through your concept with Trent’s security advisor, before the first line of code is written.
Assess any live app from just its URL, no code access required. Trent finds the risks traditional AppSec tools were never designed to see in systems that reason, plan, and act.
Thanks to Our Design Partners
Build Agentic. Stay Secure.
Connect your environment. Your security compounds from day one.
FAQs
What is an AI security solution?
An AI security solution protects the AI systems your team builds and deploys, not just the code underneath them. For agentic systems specifically, that means securing agent behavior, tool permissions, data flows, and the emergent risks that arise when autonomous components interact. Trent AI delivers this through specialized agents that work in a continuous loop: scanning, judging risk, fixing issues, and evaluating your overall security posture.
How is this different from traditional application security tools?
Traditional tools (SAST, DAST, SCA) find known code-level issues, flagged patterns, insecure dependencies, known vulnerabilities. They can’t reason about agent behavior, prompt-driven logic, or the risks created when AI agents call APIs, chain tools, and act on behalf of users. Trent AI is purpose-built for agentic systems. It assesses your environment in context, not just your code in isolation.
What is the difference between “AI for Security” and “Security for AI”?
“AI for Security” uses AI to improve traditional cybersecurity: better threat detection, faster SOC triage, automated incident responses. “Security for AI” protects the AI systems themselves: the agents, models, and autonomous workflows your team builds. Trent AI is Security for AI. We secure the agents you deploy.
How do the agents work together?
Scan agents continuously observe your environment and identify risks. Judge agents determine which findings represent real threats and prioritize by business impact. Mitigate agents act on prioritized risks: patching, opening PRs, adjusting configurations. Evaluate agents step back and assess the system as a whole, tracking trends and forecasting where risk will emerge next. Each cycle feeds intelligence back into the next, so the system compounds over time.
Do I need to give Trent access to my source code?
You can start with a URL-only assessment that analyzes your application from the outside. For deeper analysis, connect a source code repository, agent definitions, or design documents. You control what level of access to provide. The agent loop runs at whatever level of access you choose.
What types of applications does Trent secure?
Trent secures traditional web applications, AI-powered applications, and agentic systems. Whether you have legacy code in CI/CD pipelines, agent workflows in OpenClaw, or codebases in Claude Code, the same agent loop runs across all of them.
How does a Trent project work?
A project has three parts. Understand shows the Context Trent is working from, the Architecture it has mapped, and the Inventory of components it has found. Plan turns that into security Requirements. Secure connects Threats and Posture to Tasks and Reports. Results arrive page by page as analysis completes, and every finding traces back to its evidence.
What are Attack Chains?
An Attack Chain lays out a possible attack path through the AI-agent components Trent found: its premise, its confidence, and a numbered path mapped to MITRE ATLAS. Blocking controls show where the path already stops, and linked tasks show which fixes break it.
Can I correct Trent when I disagree?
Yes. You can challenge a severity and apply a regrade in place, edit draft requirements, and make task decisions. Corrections are recorded and carried into the next scan. Past runs stay as snapshots, so the record is never rewritten.