CAI (Cybersecurity AI) vs Donut: Side-by-Side Comparison (2026)
Features, pricing, ratings, and pros & cons — compared head-to-head.
CAI (Cybersecurity AI) is a free red-team & adversary emulation tool by Alias Robotics. Donut is a free red-team & adversary emulation tool. Compare features, ratings, integrations, and community reviews side by side to find the best red-team & adversary emulation fit for your security stack.
CST VerdictBased on our analysis of NIST CSF 2.0 coverage, core features, company size fit, deployment model, here is our conclusion:
Security teams at startups and small consulting firms who need LLM-powered penetration testing without licensing friction should build on CAI; the framework's 500+ supported LLMs and 15+ agents let you run offensive automation in your own environment at zero cost. The GitHub community (3,641 stars) and on-premises deployment mean you control the entire supply chain, which matters when handling client data during assessments. Skip this if your organization lacks Python engineers to customize agents or needs vendor-backed SLAs; CAI prioritizes offensive capability over the detection and response coverage that enterprise security teams typically require.
Red teamers and penetration testers who need to deliver .NET and PE payloads that evade memory-scanning EDR will find Donut essential; it generates position-independent shellcode that executes directly from memory without touching disk, eliminating the most common detection vector. With 4,492 GitHub stars and active community contributions, the tool has been battle-tested across real engagements and stays current with Windows API changes. Skip this if you're looking for post-exploitation frameworks with built-in C2 capability or if your scope is limited to external reconnaissance; Donut is narrowly focused on the injection problem and assumes you already have payload delivery sorted.
