General Analysis

General Analysis delivers AI security for agentic systems by combining context-aware automated red-teaming with vulnerability forecasting. The platform trains adversarial models that learn from realistic engagements with AI agents to discover exploits, while forecasting models predict vulnerabilities before code ships. This closed-loop approach enables organizations to identify and address security gaps in their AI deployments before attackers can exploit them.

• Adversarial Agents - RL-trained agents that simulate adversarial behavior against agentic systems, understanding context and finding exploits specific to each deployment rather than random fuzzing.

• Forecasting Models - Single-pass vulnerability prediction fast enough to run on every pull request, converting adversarial examples into training data for safeguards.

• Context-Aware Attacks - Models digest runtime context, map tool graphs, and target seams between components to discover multi-step exploit chains across tools, APIs, and decision points.

• CI/CD Integration - Lightweight enough to run on every commit while accurate enough to block deployments, enabling continuous security evaluation in development workflows.

• AI Threat Intelligence - Real-time threat data from attacks across all customer systems creates a network effect where defense improves as more organizations join.

• RL Training Environments - Dedicated reinforcement learning environments that reflect real agentic system architectures for training attacker models.

• Novel Exploit Discovery - Finds attack paths that pattern-matching and static analysis cannot detect by understanding how agents reason, plan, and execute.

• Open Source Tools - The Jailbreak Cookbook repository provides implementations of jailbreaks and prompt-injection techniques with unified infrastructure for researchers and red-teamers.

To get started, organizations can book a demo through the website to discuss their specific AI security needs. The platform integrates with existing development workflows and provides both offensive testing capabilities and defensive forecasting to create comprehensive protection for enterprise AI deployments.