Adversa AI has evolved from early adversarial-AI research into a coding agent security platform built for the era of autonomous developer tooling. The core premise is that once you approve an agent, you do not automatically approve every action it takes: an agent can wander past its intended scope, turn a 'clean up the test environment' instruction into a production database delete, install the wrong package, or be hijacked through prompt injection, poisoned repositories and malicious MCP servers. Because each tool logs actions one step at a time, no single vendor control sees the whole chain.
The platform captures every surface where an agent acts — LLM traffic, the agent harness, the machine it runs on and direct provider integrations — and maps all of them into one graph. Each action is read for meaning and tied into a chain so a lone suspicious step is treated as context rather than an alert, while genuinely dangerous chains are stopped before they complete. Default policies cover known coding-agent attack techniques and public incidents, and the platform is designed to work across multiple agent brands such as Claude Code, Copilot, Cursor and Codex rather than governing only one vendor's stack.
Beyond the product, Adversa maintains an active offensive-research practice: AI red teaming and agentic assessments, plus published research, reports and standards contributions (NIST AI RMF, OWASP ASI, CoSAI). It reports SOC 2 Type I and II audits and ISO 27001 certification, and is positioned for security leaders handling EU AI Act and similar regulatory obligations. Pricing is quote-based through a demo request rather than published tiers.
