mike-arnica

packj

Packj stops :zap: Solarwinds-, ESLint-, and PyTorch-like attacks by flagging malicious/vulnerable open-source dependencies ("weak links") in your software supply-chain

sys-mount

High level FFI binding around the sys mount & umount2 calls, for Rust

Nettacker

Automated Penetration Testing Framework - Open-Source Vulnerability Scanner - Vulnerability Management

safe-package

simple_libc

Safe, friendly Rust interfaces to some commonly used Unix libc functions.

fd-writer

Simple writer to file descriptor using libc

fork

Library for creating a new process detached from the controling terminal (daemon) using the fork and setsid syscalls.

tinyfw

A toy containers aware firewall built in Rust

dumpscan

Finding secrets in kernel and user memory

openssh_key_parser

gitleaks

Protect and discover secrets using Gitleaks 🔑

tag-security

🔐CNCF Security Technical Advisory Group -- secure access, policy control, privacy, auditing, explainability and more!

ripsecrets

A command-line tool to prevent committing secret keys into your source code

GitGoat

GitGoat is an open source tool that was built to enable DevOps and Engineering teams to design and implement a sustainable misconfiguration prevention strategy. It can be used to test products with access to GitHub repositories without a risk to your production environment.

high-entropy-string

A library for classifying strings as potential secrets.

cherrybomb

Stop half-done APIs! Cherrybomb is a CLI tool that helps you avoid undefined user behaviour by auditing your API specifications, validating them and running API security tests.

GitGoat

GitGoat is an open source tool that was built to enable DevOps and Engineering teams to design and implement a sustainable misconfiguration prevention strategy. It can be used to test products with access to GitHub repositories without a risk to your production environment.

Malicious-Code-Detection-in-Stack-Overflow

Stack overflow as one of the most important information sources for researchers and developers rely on. The stack overflow provides ready- to- use copy and paste codes snippets, which provides huge benefits for researchers and software developers in studying their behavior. The impact of this behavior on code security is unknown. Due to complex nature of code security, it is very difficult to provide secure solutions without knowing the type of malware in the code. Malicious executable programs in stack overflow are designed to damage user’s systems without their consent. It is very important to find the malicious codes-snippets in such online programming platform. In this report, we tried to identify the malware from the data of code snippets present in stack overflow. We evaluated based on the collected data set using ten-fold cross validations and comparisons with SVM and decision tree.

malicious_code_detection