Adversa AI Launches Security Platform to Protect AI Coding Agents from Real-Time Threats

03 November 2026 | Tuesday | News

The platform provides real-time threat detection, policy enforcement and agent behaviour monitoring across coding tools such as Claude Code and Codex, helping enterprises prevent malicious agent activity and secure AI-driven development workflows.
Picture Courtesy | Public Domain

Picture Courtesy | Public Domain

 

Adversa AI, an AI security pioneer with five years of offensive research, launched the Adversa AI Coding Agent Security Platform for Developer Endpoints.

The platform covers 4 essential components of Agentic Development Security

  • Observability and Provenance via Agent behavior graph and Semantic threat layer. In-memory engines evaluate each action against that graph and over 300 default policies in Security, Reliability and Privacy categories covering every known coding agent attack technique, CVE, public incident and threat.

  • Agent Policy enforcement and Context Guardrails for real-time prevention of attack chains. An ensemble of in-memory engines making sub-millisecond blocking decisions, our Context Guard detects attacks at a 0.1% false positive rate — outperforming Claude-as-a-judge, Azure Guardrails, AWS Bedrock and opensource guardrails on benchmarks from Microsoft, ETH Zurich, and NVIDIA at 100× lower latency.

  • Universal agent runtime surface coverage via LLM proxy, MCP gateway, harness hooks, endpoint runtime, and agent vendors' compliance APIs mapped into one universal agent behavior graph. It follows the AARM standard by CSA for agentic runtime security.

  • Agentic supply chain security and Shadow AI discovery by detecting and managing all MCP servers, skills, hooks, plugins, instruction files, dependencies and generated artifacts.

At a financial institution that deployed the platform to secure Codex, Claude Code, and Copilot, blocking decisions took a median 0.2 ms, with no reported change in developer experience. From day one, the security teams from AppSec, Product Security, DevSecOps saw every agent action, and correlation cut noise to one confirmed incident per 2,000 raw signals. In week one, the platform stopped an attack: an agent loaded a malicious skill, followed its hidden instructions, read internal API secrets, and attempted to exfiltrate them. Other security tools missed the chain; the platform blocked the outbound exfiltration request.

"Coding agents deliver enterprise AI's quickest wins and biggest provable efficiency gains yet rank among the riskiest agentic AI systems according to AIRQ," said Alex Polyakov, co-founder and CTO of Adversa AI. "So we focused all our offensive experience on the immediate coding agent security challenge: control for security and risk teams, productivity and operational safety for engineering with minimal noise rate set as our slogan - cut the noise, deliver value."

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