This repository is a comprehensive, curated collection of cybersecurity study plans covering 20+ specialized domains such as application security, cloud security (AWS/Azure/GCP), DevSecOps, threat modeling, GRC, GenAI security, and more. It is not a software application or data research project; rather, it is a knowledge base of structured markdown roadmaps designed to guide learners and professionals through role-specific cybersecurity skill development. The plans reference up-to-date frameworks (OWASP Top 10:2025, NIST CSF 2.0, EU AI Act), include curated resources (books, videos, courses, certifications), and are consistently maintained. The repository has high community engagement (5k+ stars) and remains actively updated, though it contains no executable code, data pipelines, or notebooks.
Aaia is a security analysis tool for AWS IAM and Organizations that visualizes identity and access relationships in a Neo4j graph database. It collects AWS data via CLI commands, stores it as JSON, and loads it into Neo4j for graph-based querying and auditing. The architecture consists of a modular Python application with separate components for data collection, loading into Neo4j, and custom auditing modules. Key entry points include the main Aaia.py script, the Aaia_aws_collector.sh shell script for data gathering, and specialized action/module handlers. The data flow moves from AWS CLI → JSON files → Neo4j graph → analysis results via Cypher queries or custom modules. The tool depends on Neo4j (v3.5.17 compatible), AWS CLI, and several Python packages for policy processing and Neo4j interaction.
Evil Limiter is a Linux command-line tool that uses ARP spoofing and traffic shaping (tc/iptables) to monitor, analyze, and limit the bandwidth of devices on a local network without requiring administrative access to those devices. It provides an interactive shell with commands to scan for hosts, limit or block bandwidth per host (upload/download), monitor real-time bandwidth usage, and detect host IP changes. The architecture is a single-threaded interactive menu with background threads for ARP spoofing, bandwidth monitoring, and reconnection watching. It depends on scapy for packet manipulation, netifaces for network interface info, and standard Linux utilities (tc, iptables, sysctl). The codebase is well-organized into modules for console UI, networking operations, and command parsing, but lacks tests and has limited reusability outside its specific purpose.
This repository is a community-driven collection of DuckyScript payloads designed for USB Rubber Ducky, Flipper Zero, and other HID attack devices. It primarily functions as a playbook for penetration testers and red teamers, offering ready-to-inject scripts that automate keystroke injection attacks. The codebase is organized into a flat file tree by platform (Windows, Linux, macOS, mobile) and category (credentials, remote_access, destructive, prank, exfiltration, recon, execution, etc.). Each payload is a self-contained DuckyScript file, often embedding PowerShell, Bash, or Python one-liners that are typed and executed on the target machine. The repository includes hundreds of payloads covering credential theft (e.g., browser password dumping, WiFi key extraction), remote access (reverse shells, persistence via systemd, scheduled tasks), destructive actions (fork bombs, zip bombs, file corruption), exfiltration (webhook, Dropbox, email), and pranks (RickRolls, fake updates, desktop trolling). The architecture is not a traditional application but a script library; the 'code' is primarily configuration/scripting rather than compiled software. Maintenance is active, with monthly snapshot tags and contributions, though many payloads suffer from hardcoded URLs and dependencies on specific OS versions, leading to moderate technical drift. The repository does not contain data pipelines, notebooks, or ML models.
This repository is a comprehensive OSCP pentesting cheatsheet composed of markdown notes and diagrams. It serves as a reference guide for penetration testing methodologies, covering enumeration, privilege escalation, web application testing, Active Directory attacks, and more. While not containing executable code or data processing pipelines, it curates actionable information from various security resources into an organized format. The content is structured as checklists and step-by-step guides for common pentesting tasks, making it immediately applicable for individuals preparing for the OSCP certification or conducting real-world assessments. The repository does not ingest or transform external datasets; instead, it represents synthesized knowledge intended for direct consumption. Despite lacking traditional data engineering components, the repository demonstrates value as a knowledge artifact. Its maintenance is active with recent updates, and the static nature ensures zero technical drift. Reproducibility is trivial as the entire content is self-contained within the repository.
This repository is the archived reference implementation of the CAI (Cybersecurity AI) framework by Alias Robotics. It is a comprehensive, open-source platform for building and deploying AI-powered offensive and defensive security automation. The codebase provides a full-stack agent framework including a Python SDK (Agent, Runner, tools, handoffs, guardrails, tracing, voice, MCP), a CLI/REPL with rich interactive features, a Textual-based TUI, a FastAPI REST API server, and a benchmarking suite (CAIBench) with cyber ranges and CTF challenges. The framework supports multiple LLM providers (OpenAI, LiteLLM, custom) and includes specialized agents for red teaming, blue teaming, bug bounty, DFIR, network analysis, and more. It also features continuous operations (24/7 autonomous loops), session management, cost tracking, and extensive refusal testing (400+ scenarios). While the repository is now archived and will not receive further updates, the SDK components (function_tool decorator, Handoff abstraction, tracing processors, voice pipeline) are well-crafted and could be extracted for reuse in other agent-based projects. The codebase is large and monolithic, with some global mutable state and test duplication, but overall demonstrates strong engineering practices in the cybersecurity AI domain.
SocialFish is a modern dynamic phishing toolkit designed for credential harvesting, session hijacking, and social engineering attacks. It provides a Flask-based web application with an admin dashboard for managing cloned login pages, capturing credentials, intercepting OTP/2FA codes, tracking victim sessions, and injecting post-capture attack payloads (e.g., keyloggers, clipboard stealers, tab jacking). The system supports browser automation via Playwright and Selenium to clone JavaScript-heavy and SPA login flows, and includes tunneling via ngrok/cloudflared for exposing phishing URLs remotely. The architecture is a monolithic Flask app with SQLite storage, WebSocket real-time updates, and a mobile API authenticated by QR tokens. External dependencies include Flask, Flask-SocketIO, Flask-Login, Playwright, Selenium, nmap, qrcode, and PyLaTeX. Despite its feature-rich surface, the codebase exhibits significant quality issues: broken async flows, missing database columns, incomplete routes, version mismatches between requirements files, and security concerns such as default credentials and insecure secret key generation. The project is actively maintained (last commit 2026-05-20) but the code is not production-ready as claimed in documentation.
This repository contains a single Arduino sketch for an RTL8720dn-based WiFi deauther. It hosts a captive web interface on the board's own WiFi network, scans for nearby access points, and allows a user to initiate deauthentication attacks against selected networks by sending crafted deauth frames. The architecture is a monolithic embedded firmware with a simple event loop: it serves HTML pages, parses HTTP POST/GET requests, and uses a submodule for packet injection. The code is tightly coupled to the target hardware and lacks modularity, abstraction, or tests. It is a functional but unrefined hobbyist project with no reusable components.
This repository is a curated cheat sheet for web application security testing, penetration testing, and bug bounty hunting. It aggregates a vast collection of tools, commands, URLs, and references organized by phases: discovering, enumerating, scanning, monitoring, attacking, manual exploitation, and AI-related security. The repo contains no application code; it is a markdown document only. It is a valuable reference for security professionals but lacks any executable software components or data pipelines. The information is comprehensive and well-structured, but the repository itself is not a functional system and does not demonstrate software architecture or engineering craftsmanship beyond content curation.
RogueMaster/awesome-flipperzero-withModules is a Flipper Zero resource distribution hub rather than a conventional runnable application. Its dominant content is a curated awesome-list plus a massive asset dump: the README links to hundreds of community resources (BadUSB payloads, Sub-GHz databases, NFC tools, custom firmware), while the repository itself stores custom firmware update bundles, ESP32 flasher images, WAV files, a few firmware-level C source variants, and tens of thousands of dolphin animation frame binaries organized into themed packs (Anime, Pokemon, Logos, CHERRY, 420, etc.). The only real code is a set of near-identical Flipper animation-manager C files, a small NFC hex-to-binary shell script, and Python dependency helpers for animation tooling. There is no server, API, library interface, CLI application, or build pipeline. Architecturally this is a flat asset repository with no deduplication, no tests, no dependency management, and no validation. Identical .bm bitmap frames and meta.txt animation manifests are copied across many theme directories, causing enormous repository bloat and synchronization drift. The Flipper animation format itself is consistent and well-defined (Flipper Animation v1 metadata, 128x64 monochrome frames, manifest entries with level/butthurt ranges and weights), making the asset schema the most reusable aspect for Flipper modders. However, the codebase surrounding it is weak: no automation, inconsistent metadata edge cases, WIP/uncompiled animation directories mixed into the tree, and high link-rot risk across the curated README. For engineers, this repository is best treated as a catalog of Flipper Zero content and a source of example animation packaging, not as a software system to integrate or extend. It is actively maintained in the sense that new assets and firmware builds are pushed, but engineering quality is below average for a code repository. It would need an asset pipeline, checksumming, deduplication, and manifest validation before it could be considered well-crafted.
This repository is a static README-based reference list that curates 20 links to external blog posts about credential dumping techniques for penetration testing. There is no actual source code, scripts, executables, or any functional software. The entire content is a markdown table with topics and links to the Ignitetechnologies blog. It functions as a curated cheat sheet or index, not as a tool, library, or pipeline. No architecture, entry points, dependencies, or data flows exist. The repository has no reusable components and exhibits zero code craftsmanship—it is purely documentation. Despite having many stars and forks, it offers no software value and is effectively a non-functional repository from a software engineering perspective.