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Tags: Security
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1–16 of 16 · Most stars

John the Ripper jumbo - advanced offline password cracker, which supports hundreds of hash and cipher types, and runs on many operating systems, CPUs, GPUs, and even some FPGAs

Thefatrat a massive exploiting tool : Easy tool to generate backdoor and easy tool to post exploitation attack like browser attack and etc . This tool compiles a malware with popular payload and then the compiled malware can be execute on windows, android, mac . The malware that created with this tool also have an ability to bypass most AV software protection .

  • thefatrat
  • bypass
  • linux
  • autorun

Capstone disassembly/disassembler framework for ARM, ARM64 (ARMv8), Alpha, BPF, Ethereum VM, HPPA, LoongArch, M68K, M680X, Mips, MOS65XX, PPC, RISC-V(rv32G/rv64G), SH, Sparc, SystemZ, TMS320C64X, TriCore, Webassembly, XCore and X86.

OSSEC is an Open Source Host-based Intrusion Detection System that performs log analysis, file integrity checking, policy monitoring, rootkit detection, real-time alerting and active response.

Up to 100x faster strings for C, C++, CUDA, Python, Rust, Swift, JS, & Go, leveraging NEON, AVX2, AVX-512, SVE, GPGPU, & SWAR to accelerate search, hashing, sorting, edit distances, sketches, and memory ops 🦖

The wolfSSL library is a small, fast, portable implementation of TLS/SSL for embedded devices to the cloud. wolfSSL supports up to TLS 1.3 and DTLS 1.3! Update to wolfSSL 5.9.1 for the latest CVE fixes.

Hardened allocator designed for modern systems. It has integration into Android's Bionic libc and can be used externally with musl and glibc as a dynamic library for use on other Linux-based platforms. It will gain more portability/integration over time.

  • malloc
  • security
  • memory-allocation
  • malloc-library

Android Loadable Kernel Modules - mostly used for reversing and debugging on controlled systems/emulators

  • loadable-kernel-modules
  • android-lkms
  • emulators
  • kernel

collection of C/C++ programs that try to get compilers to exploit undefined behavior

Reducing Bias in Modeling Real-world Password Strength via Deep Learning and Dynamic Dictionaries