Ostorlab leverages machine learning and automated scanning engines to perform end-to-end mobile app security assessments. Developers upload app binaries or connect repositories, and Ostorlab’s AI performs static code analysis, dynamic runtime testing, and network traffic inspection. The platform highlights critical, high, and medium-risk issues, offers remediation guidance, and integrates into development workflows for continuous monitoring and compliance management.

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.