Offensive Graphs leverages advanced machine learning algorithms to seamlessly ingest diverse network data sources such as firewall rules, Active Directory configurations, cloud assets, and vulnerability scanner outputs. It automatically constructs comprehensive attack graphs that reveal the most effective lateral movement and privilege escalation paths an adversary might exploit. Users can interactively explore these graphs in a user-friendly web interface, apply filters by risk level or asset criticality, and drill down into detailed risk factors. The platform also prioritizes remediation tasks based on aggregated threat scores and generates customizable reports to support compliance and incident response. By automating complex threat modeling, Offensive Graphs significantly reduces manual effort while enhancing the accuracy and coverage of security assessments.

Ostorlab 利用機器學習和自動掃描引擎，進行端對端的行動應用安全評估。開發者上傳應用二進位檔或連結程式碼庫，Ostorlab 的人工智慧會執行靜態程式碼分析、動態執行測試及網路流量檢查。該平台突出顯示關鍵、高、中風險問題，提供修復建議，並融合到開發流程中，以進行持續監控與合規管理。