Autonomous Security Testing for Web Apps, APIs, and AI Systems

Casco provides an autonomous penetration testing platform designed to deliver continuous security assessment across web applications, APIs, cloud infrastructure, and AI systems. The platform integrates into existing development workflows and conducts automated testing as software changes occur, reducing reliance on periodic, human-led pentests.

Casco’s system identifies vulnerabilities, generates reproducible proof-of-concept paths, and produces structured reports that include severity ratings, impact summaries, and remediation steps. It supports coverage for standard risk frameworks such as OWASP Top 10, OWASP API Top 10, OWASP LLM Top 10, and OWASP Cloud Top 10, along with Casco’s own agentic threat model.

In addition to its autonomous mode, Casco offers a supervised option in which human security engineers — experienced in offensive security roles at organizations including AWS, NSA, and US military units — review findings, verify exploitability, and work with customers through direct communication channels.

The company emphasizes reducing false positives and providing continuous visibility rather than annual or point-in-time assessments. Casco’s operating model is positioned to support fast-moving software teams that require near-real-time testing and remediation guidance as part of their ongoing development and deployment processes.

Threat Intelligence is a mature and stable category that includes 128 vendors. But there is a new breed of vendors leveraging AI to add context, enrich, and contribute to security operations.