Ostorlab Blog

The True Cost of False Positives: Calculating the Engineering Tax of Noisy Scanners

False positives are an engineering-capacity problem, not only a scanner-quality problem. Learn how to measu...

When Does an AI Scanner Become an AI Pentest?

Learn what separates AI-powered scanning from AI pentesting and how Ostorlab Deep Agentic Scan follows evid...

Source Code Security: From Signal to Validated Risk | Ostorlab

Learn how source code security testing works, why traditional SAST creates false positives, and how agentic...

Ostorlab vs. Manual Pentesting: More Critical Findings, Less Time, Lower Cost

Ostorlab reports more critical findings, shorter testing time, and assessment costs of one-tenth to one-for...

How to Vet a Third-Party Mobile App Before You Allow It in Your Company

A five-step mobile app vetting checklist for security teams (permissions, trackers, malware, data flows, st...

Precheck: Know Your Mobile Scan Will Work Before It Runs for Hours

Precheck verifies that a mobile app installs, launches, logs in and runs its UI prompts on a real device. W...

Does AI Security Testing Hallucinate? LLM Guesses vs. Proof-of-Exploit

Language models hallucinate by default, and security findings are no exception. See why, and the harness, e...

Ostorlab vs MobSF: Analyst-Driven vs AI-Driven Mobile Security Testing (2026)

Ostorlab vs MobSF (Mobile Security Framework) for mobile app security testing: static and dynamic analysis,...

Ostorlab vs Oversecured: Mobile App Security Testing Compared (2026)

Ostorlab vs Oversecured for mobile app security testing: iOS and Android coverage, exploit proof, authentic...