
grubcrawler
The world's fastest agentic crawler. Reclaimed. Reinvented. Ready for war.

The world's fastest agentic crawler. Reclaimed. Reinvented. Ready for war.

Linux system-call monitor using ptrace to trace file, process, network, and memory activity, with namespace isolation and machine learning…

Collects multi-source security logs from reproducible Docker attack scenarios, builds attack chains, and provides the SecLog-Bench-216 benchmark for…

This project contains the source code for the CERT Basic Fuzzing Framework (BFF) and the CERT Failure Observation Engine (FOE).

Reverse Engineering: Decompiling Binary Code with Large Language Models

Detects process injection and memory manipulation used by malware. Finds RWX regions, shellcode patterns, API hooks, thread hijacking, and process…

A fast universal code security scanner, written in Rust. Batteries included: supports 14 languages, TUI for triage, secrets, post-quantum audits,…

C-based Android static analysis framework for decompilation, secret detection, endpoint discovery, permission analysis, and native library scanning…

FARO - Document Sensitivity Detector

A Binary Genetic Traits Lexer Framework

Automating Host Exploitation with AI

Runtime behavioral analysis tool that sandboxes suspicious packages in Docker, traces syscalls with strace, maps process cascades into directed…

A machine learning tool that ranks strings based on their relevance for malware analysis.

Open-source threat intelligence platform for malware and observable analysis. Enriches IPs, domains, URLs, and hashes with external sources, performs…

AI-powered Windows diagnostic & auto-repair tool using Google Gemini. Detect crashes, optimize performance, scan for malware, and generate PowerShell…

Memory-free continual learning framework for malware classification using mode connectivity-based interpolation. Supports class-incremental and…

0-day malware detection for binaries, source & scripts (that doesn't suck)

Official code for the ISSTA 2026 paper: Is "Knowing It’s Malicious" Enough? Evaluating LLMs for Fine-Grained Malware Behavior Auditing