Proven in production, Adversa’s Agentic Development Security solution blocks coding agent attack chains in under 0.2 milliseconds
Adversa AI, an AI security pioneer with five years of offensive research, launched the Adversa AI Coding Agent Security Platform for Developer Endpoints.
Adversa AI Coding Agent Security Platform, generally available today at https://adversa.ai/agent-security-platform/, connects what Coding agents and agentic IDEs such as Claude Code, Codex are asked to do with what they actually do in real time. The link exposes attack chains and rogue agents whose steps look routine alone, and the platform blocks the dangerous step before it executes.
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.
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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.”
The platform’s defenses draw on the team’s published discovery of entirely new AI attack categories — including Reasoning Leakage, PromisqRoute, Cryptographic Context Injection, SymJack, and TrustFall — now part of the industry’s threat landscape.
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