Your Agents Are Shipping. Is Your Security Keeping Up?
Trent helps you find, prioritize, and fix the risks your agentic systems introduce before they become production problems.
Your AI Security Posture Has a Blind Spot
AI agents expand your attack surface faster than traditional security tools can adapt. New behavior, new tools, and constant iteration create risk your current stack was not built to see.
Traditional security tools find code-level vulnerabilities. They can’t reason about agent behavior, multi-step autonomy, or the new threat surfaces created when AI agents call APIs, chain tools, and act on behalf of users.
A single AI agent can access external data, call third-party services, modify databases, and trigger downstream agents from a single prompt. Prompt injection, tool misuse, unintended autonomous actions, data exfiltration through agent chains, privilege escalation across interconnected agents. Traditional scanners, firewalls, and SAST/DAST tools are blind to all of it.
Agentic systems don’t ship in releases. They run, learn, and adapt in real time. An agent’s behavior today may differ from its behavior tomorrow as models update, prompts change, and new tools are connected. Your AI security posture management needs to be continuous, not periodic.
Multiple Agents. One Continuous Loop. AI-SPM That Compounds.
Trent deploys specialized security agents that continuously scan, judge, mitigate, and evaluate your environment. Each cycle improves the next, so your security posture gets sharper as your systems evolve.
Continuously observe agents, code, infrastructure, and dependencies. They learn where to look for risks and what matters in each environment. Over time, Trent’s agents reduce noise, focus attention on high-risk surfaces, and flag increasingly high-signal observations.
Take findings and determine what they mean. They classify signal vs. noise, assess business impact, and prioritize based on real risk rather than static rules. As they accumulate context across environments and historical outcomes, their judgments become sharper and more predictive.
Agents act on prioritized risks. They patch vulnerabilities, open pull requests, adjust configurations, and validate that fixes actually work. Because they observe which remediations succeed, and which fail, they continuously improve their effectiveness within each customer’s stack.
Step back and assess the system as a whole. They track trends, quantify risk over time, benchmark against standards, and identify systemic weaknesses. As the system compounds data, these agents become increasingly good at forecasting where risk will emerge next, informing smarter scanning and tighter prioritization.
Three Steps. No Configuration Overhead.
Connect your code, agents, or environment so Trent can understand how your system works.
Trent builds a prioritized, always-current security assessment grounded in your real architecture.
Review the plan, execute fixes, and let Trent keep reassessing as your agents evolve.
Connects to Your Stack
Your Agents Don’t Stop Evolving. Neither Should Your Security.
Your AI application has risks your existing security stack was never designed to find.
FAQs
What is AI security posture management (AI-SPM)?
AI security posture management is the continuous process of discovering, assessing, and improving the security of AI systems and includs AI agents, LLM-powered applications, and agentic workflows. Unlike traditional application security tools that focus on known code vulnerabilities, AI-SPM addresses the unique threat surfaces created when AI systems reason, act, and interact autonomously. It covers prompt injection risks, agent-to-agent privilege escalation, tool misuse, data exfiltration through agent chains, and configuration drift in agentic environments.
How is AI-SPM different from CSPM or DSPM?
Cloud Security Posture Management (CSPM) monitors cloud infrastructure misconfigurations. Data Security Posture Management (DSPM) tracks sensitive data exposure. AI-SPM focuses specifically on AI and agentic system risks like prompt safety, model behavior, agent permissions, and the emergent threats that arise when autonomous components interact.
How does Trent AI’s approach differ from traditional security scanners?
Traditional scanners (SAST, DAST, SCA) find known code-level vulnerabilities: CVEs, insecure dependencies, flagged patterns. They don’t assess whether your application is architecturally secure for what it does. Trent AI’s four specialized agents work in a continuous loop: scanning your environment, judging risk based on business context, remediating issues, and evaluating your overall posture. Each cycle compounds intelligence from the last, reducing false positives and sharpening prioritization over time.
Do I need to give Trent AI access to my source code?
You can start with a URL-only assessment that analyzes your application’s publicly visible attack surface, no code access required. For deeper analysis, connect a source code repository. Trent AI also accepts agent definitions, design documents, and product specifications to sharpen its assessment. You control what level of access to provide.
How do I get started?
Connect your source (repositories, agent definitions, or a URL), and Trent AI begins its first assessment cycle. You can add context like design docs, compliance requirements, technical constraints at any point. Most teams see their first prioritized assessment within minutes, not weeks.