General Analysis offers a security platform that continuously maps an organization’s AI asset graph and runs context‑aware adversarial simulations to expose multi‑step exploit paths across models, tools, permissions, and data stores. The platform provides real‑time red‑team testing, policy‑grounded blue‑team guardrails, risk scoring, and audit trails, delivering coverage metrics and compliance reporting for AI agents deployed in production across major cloud and AI service providers.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises deploying autonomous AI agents face security gaps because agents require broad tool and data access, have nonlinear attack surfaces, and cannot rely on static alignment or least‑privilege models. This creates hidden exploit paths that traditional red‑team or compliance checks miss, leading to data leakage, credential theft, and unsafe actions in production.
Solution
General Analysis provides an AI‑focused security platform that continuously maps an organization’s AI asset graph—including models, tools, permissions, and data stores—and automatically generates multi‑step adversarial attack chains targeting the seams between components. Proprietary adversarial agents simulate realistic exploit scenarios in CI/CD pipelines and live environments, exposing system‑level risks that isolated robustness tests overlook. The platform then offers blue‑team controls to enforce policy‑grounded guardrails, risk scoring, and evidence capture for each workflow, enabling security teams to remediate vulnerabilities before they are exploited. Integrated dashboards present coverage metrics, audit trails, and policy test results across cloud providers (AWS, Azure, GCP) and AI services (OpenAI, Anthropic, Hugging Face). By combining automated red‑team testing with strategic blue‑team enforcement, General Analysis turns continuous adversarial testing into a practical defense layer for production AI agents.
Target Audience
Primary customers are security and risk teams within enterprises that deploy autonomous AI agents—such as employee copilots, code assistants, customer support bots, and regulated AI assistants in finance, healthcare, legal, and media domains.
Features
- Context‑aware adversarial agents that ingest runtime environments and construct full tool‑permission graphs for automated multi‑step exploit generation
- Real‑time red‑team simulations across AI models (e.g., GPT‑4o‑mini, Claude‑3‑5‑Sonnet) and cloud assets (S3 buckets, IAM roles) with coverage reporting over 94%
- Blue‑team enforcement suite offering policy‑grounded guardrails, command risk scoring, and evidence capture for data movement, credential access, and PII handling
- Integrated dashboard displaying attack simulation status, policy test outcomes (thousands of tests), and audit trails for compliance reporting
- Support for major cloud platforms (AWS, Azure, GCP) and AI model providers (OpenAI, Anthropic, Hugging Face) with seamless asset discovery and monitoring
- Playbook library mapping real incident failure modes to specific controls for employee copilots, code agents, support bots, and regulated assistants