Trent AI
Corgea
Semgrep
Adeptiv.AI
AgentShield.net
Snyk
AI Agents Control Tower
NeuralTrust.ai
React Engine
Trent AI is an agentic AI security platform that threat-models and assesses AI agents and LLM applications. It analyzes your codebase and architecture, produces a prioritized threat model with vulnerabilities and remediation controls, and delivers fix guidance directly into developer workflows. Built for teams shipping AI agents who need security review that understands agentic behavior, not just static code.
Trent AI React EngineTrent AI's answer
Trent is a multi-agent system: multiple specialized AI agents built on frontier language models, each owning one stage of the loop (threat scanning, analysis, remediation, and security posture). It connects to development environments over the Model Context Protocol (MCP), with integrations for Claude Code and Lovable, and ships a security assessment skill (trentclaw) for the OpenClaw agent runtime. Its analysis is grounded in OWASP (LLM Top 10 and the Agentic Security Initiative Top 10), MITRE ATLAS, and the NIST AI Risk Management Framework, and its detection quality is benchmarked against CWE-Bench.
Trent AI's answer
Trent is built for agentic systems, not adapted to them. It runs as a continuous loop of multiple specialized agents: scan your code and agent definitions, judge which findings are genuinely exploitable, open fixes, and verify the fix held. It inventories every agent, tool, skill, and MCP server by what it can actually do (read, write, execute, egress), traces how they could be chained into an attack, and re-assesses whenever the system changes, because agentic systems change without a release. Each cycle compounds context about your environment, so its judgment improves over time. A person always approves changes before anything is applied.
Trent AI's answer
Traditional scanners look for static defects in an artifact that holds still, and agentic systems do not hold still. A new tool, a changed prompt, or an upgraded model changes behavior with no commit to review. Trent treats the agent's runtime decisions as the risk variable, judges exploitability in your system's real wiring instead of inheriting generic severity scores, and re-verifies continuously. It complements the scanners you already run rather than replacing them: keep them for known CVEs and code patterns, and use Trent for the agentic attack surface they cannot see.
Trent AI's answer
Trent AI was founded in 2025 in the UK by Neil Lawrence (DeepMind Professor of Machine Learning at Cambridge, former Director of Machine Learning at Amazon), Eno Thereska (20+ years building autonomous systems, Principal Engineer at AWS, early Confluent engineer), and Zhenwen Dai (15+ years in machine learning, led research at Spotify). The founding observation: AI agents now write and ship software faster than any security team can review it, and the existing security stack was built for software that holds still. Trent is the answer to that gap, an AI security engineer that is always there. The company raised $13M and is a winner of the Cybersecurity Stars Awards 2026 (The Hacker News).
Trent AI's answer
Two groups. First, security teams at companies building or deploying AI agents: mature in traditional security, new to agentic security, and outnumbered by roughly 80 developers for every security engineer before coding agents joined the developers. Second, AI-native startups shipping fast with AI coding tools such as Claude Code, Codex, Cursor and Lovable, who know their security posture is weak and want guardrails that do not slow them down.
Trent AI's answer
Based on our record, React Engine seems to be more popular. It has been mentiond 1 time since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I was wondering to use paypal's React Engine (https://github.com/paypal/react-engine), but I have some doubts:. Source: over 4 years ago
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