Security

Large-scale security analysis of 500+ top mobile banking apps reveals widespread vulnerabilities, decade-old codebases, and concerning backend centralization patterns.

Security

Precision beats payload spray using Ostorlab's AI engine to systematically land RCE on Titiler and proves exfiltration without a single stack trace.

Security

This article showcases Ostorlab's AI Pentest Engine's process for analyzing an Android application for Intent Redirection vulnerabilities. Follow the engine's journey from static analysis and initial findings to rigorous dynamic validation, demonstrating its ability to not only identify potential threats but also to meticulously discard false positives.

Security

This article presents a thorough, hands-on analysis and real-world exploitation of a hardcoded GCP service account with overprivileged Pub/Sub access discovered in a HackerOne mobile app. It details how Ostorlab’s AI-powered pentesting engine automated the full cycle—from authentication and permission enumeration to end-to-end message injection/interception—enabling remediation within four days.

Security

This technical analysis reveals how sophisticated attack chains—combining path traversal, symbolic link manipulation, and Android SDK quirks—can breach Signal Android's defenses to extract sensitive internal files, despite its legendary encryption remaining intact. While Signal patched these vulnerabilities within days, the discoveries offer crucial lessons about how seemingly minor bugs can be chained into powerful exploits, and why even the best security architecture needs multiple layers of defense

Security

This article presents a thorough, hands-on analysis and proof of concept for exploiting an OOB XXE vulnerability CVE-2021-29620 in Report Portal. It details how Ostorlab's AI-powered pentesting engine was used to automate the full cycle.

Product

Ostorlab’s AI Monkey Tester transforms mobile app security testing by using natural language prompts and generative AI to automatically generate intelligent, context-aware test scenarios, resulting in up to a 10x increase in application coverage compared to traditional, rule-based testing approaches.

Security

This article presents a thorough, hands-on analysis and proof of concept for exploiting the stored XSS vulnerability CVE-2025-52559 in Zulip. It details how Ostorlab's AI-powered pentesting engine was used to automate the full cycle.