zBenchmark vs Neural Shield

zBenchmark tests the performance of your iPhone, iPad, or iPod Touch's processor and memory system. It provides seven types of benchmark and graphs the results of them: • 64-bit memory bandwidth using transfers to/from main registers. • 128-bit memory bandwidth using transfers to/from vector registers. • Integer math operations. • Single-precision floating point math operations. • Double-precision floating point math operations. • Prime number generation. • Raytracing. The app also provides technical details about your device.

Neural Shield – AI-Powered Phishing Protection Neural Shield helps you stay safe from online scams by using machine learning to detect suspicious content in emails, text messages, and other communications. Currently, Neural Shield leverages algorithms trained on public phishing databases to give you quick feedback on whether a message may be a phishing attempt. With Neural Shield, you can: • Scan suspicious messages by pasting text or taking a screenshot. • Get instant AI feedback on potential phishing risks. • Report phishing attempts you encounter. Your reports are essential — they help our team verify threats, improve AI training, and protect others in your community. • Contribute to community safety by joining a shared effort against phishing and online fraud. ! Important Note :While our AI is continuously improving, its detection is not yet 100% accurate. Always use your judgment and verify sensitive requests before taking action. Key Features • Phishing Detection : Check emails, texts, and suspicious content with AI-based analysis. • Paste or Capture: Paste message text or snap a screenshot for quick scanning. • Community Reporting: Actively report phishing cases you see — your input strengthens the AI and helps protect others. • User Contribution Matters: Each report you share helps improve training performance and supports a safer online community. • Machine Learning Engine: Powered by models trained on public phishing databases. • Continuous Improvement: Reports from users directly enhance detection accuracy over time.