Search Results for "inject"

Dynamic instrumentation toolkit for developers, reverse-engineers, and security researchers. Inject your own scripts into black box processes. Hook any function, spy on crypto APIs or trace private application code, no source code needed. Edit, hit save, and instantly see the results. All without compilation steps or program restarts. Works on Windows, macOS, GNU/Linux, iOS, Android, and QNX. Install the Node.js bindings from npm, grab a Python package from PyPI, or use Frida through its Swift bindings, .NET bindings, Qt/Qml bindings, or C API. ...

A system-wide touch event simulation library for iOS 11.0 - 14. This library enables you to simulate touch events on iOS 11.0 - 14 with just one line of code! Currently, the repository is mainly for programmers. In the future, I will make it suitable for people who do not understand how to code.

Jeffy is a Serverless "Application" Framework for Python consisting of a suite of Utilities for Lambda functions that make developing serverless applications easy. There are three main things that Jeffy is focused on: 1. Logging - Jeffy provides easy to see JSON format logging. All events, responses and errors are captured and you can make configurations for any additional attributes you'd like to see on the logs. 2. Decorators - Jeffy has an extensive range of decorators/ event...

...It blends debugger-style attachment (via gdb/ptrace techniques) with Python-aware helpers so you can inspect threads, frames, locals, and heap objects without restarting the target. This is invaluable for post-mortem diagnosis of production daemons where reproducing a bug in a dev shell is impractical. pyringe can inject arbitrary Python into the target process, enabling on-the-spot logging, state dumps, or gentle patching to keep a system limping along while you gather evidence. It’s also useful for forensic snapshots: enumerate objects of a certain type, find reference cycles, or measure memory pressure without pre-instrumentation. While powerful, it’s designed for careful, auditable use—showing exactly what code runs and where—so teams can regain visibility when black-box processes go sideways.