Search Results for "feedback"

...The platform supports multiple penetration testing categories, including web security, cryptography, reversing, forensics, privilege escalation, and binary exploitation. PentestGPT runs in a Docker-first environment, providing a secure, reproducible setup with built-in tooling and session persistence. It offers real-time feedback and live walkthroughs, allowing users to observe each step of the testing process as it unfolds. Built with a modular and extensible architecture, PentestGPT supports cloud and local LLMs, making it suitable for research, education, and authorized security testing.

...The project emphasizes efficiency and minimal performance overhead, ensuring that blocking rules do not negatively impact browsing speed. It also includes mechanisms for reporting issues and refining filters based on user feedback.

...During a search session, users review results and provide feedback that allows GitGot to filter out irrelevant or repetitive findings. This feedback is used to build blacklists that eliminate results based on repository names, file names, user names, or fuzzy matches of file content. The approach helps reduce noise while guiding the search process toward more relevant results.

AFL (American Fuzzy Lop) is a widely used graybox fuzzer that discovers bugs by mutating inputs and steering execution using lightweight instrumentation. Instead of random mutations alone, it uses coverage feedback to evolve input corpora, pushing programs into deeper and more interesting code paths. Its workflow emphasizes quick start: point it at a target binary with compile-time instrumentation (or use QEMU-based mode when recompilation isn’t possible), seed it with a small corpus, and let it iterate. AFL is known for finding serious security issues in complex software due to its corpus minimization, queue management, and deterministic mutation stages that balance breadth and depth. ...

This project is an example application built with React Native that demonstrates how to implement client login authentication in a mobile context. It shows how to integrate WebViews or native modules to handle login flows, fetch tokens, and manage persistent user sessions across platforms (iOS and Android). Because mobile authentication flows often involve more complexity than web—such as secure storage, token renewal, and redirect handling—the example gives a scaffold for real-world usage....