Hawk-Eye is a command-line application designed to scan various data sources for Personally Identifiable Information (PII) and secrets. It supports cloud storage (S3, GCS, Firebase), databases (MySQL, PostgreSQL, MongoDB, Redis), file systems, and collaboration platforms (Slack, Google Drive). The tool uses regex pattern matching and OCR to detect sensitive data in multiple file formats including images, PDFs, Office documents, and videos. The architecture is modular with a central dispatcher in main.py that routes commands to specific implementations in the commands/ directory. Shared functionality like file reading, OCR, and pattern matching is encapsulated in internals/system.py. This design allows easy extension to new data sources by adding new command modules. The tool is intended for security auditing and can be run standalone or integrated into scripts/CI/CD pipelines. Features include alert deduplication, severity-based reporting, and Slack/Jira integrations. Despite its comprehensive feature set, the tool maintains separation of concerns, making it maintainable and extensible. The use of third-party libraries for specific data sources keeps core logic focused on scanning and reporting.
This repository is a large collection of standalone PowerShell scripts for Microsoft 365 administration, reporting, auditing, and management. It contains over 100 scripts covering tasks such as exporting mailbox sizes, auditing file deletions, managing licenses, monitoring sign-ins, configuring email signatures, and cleaning up SharePoint version history. Each script is self-contained in its own folder with a README, and they are designed to be run manually or scheduled via Task Scheduler. The scripts heavily rely on Microsoft Graph, Exchange Online Management, PnP.PowerShell, and Teams PowerShell modules, with many supporting certificate-based authentication for unattended execution. Output is almost exclusively CSV files saved locally. The repository also includes several CSV lookup files (e.g., LicenseFriendlyName.csv) that map internal SKU IDs to human-readable product names, which are reused across multiple scripts. Despite the breadth of functionality, the codebase suffers from significant quality issues. There is extensive code duplication—connection logic, module installation, CSV export, and file-open popups are copy-pasted across nearly every script. Many scripts use deprecated modules like MSOnline or rely on Microsoft Graph beta endpoints, creating maintenance risks. Typos, inconsistent variable naming, and hardcoded paths are common. The repository also serves as a marketing funnel for AdminDroid, with promotional banners and links embedded in every script. There is no shared library, no version control for dependencies, no tests, and no CI/CD. The overall architecture is a loose collection of one-off utilities rather than a cohesive application. For an AI agent or engineer evaluating reuse, the most valuable assets are the connection helper patterns (e.g., ConnectMgGraph.ps1) and the license-friendly-name CSV files, which can be extracted and adapted for other M365 automation projects. However, the majority of scripts are tightly coupled to the specific reporting patterns and promotional content of this repository, making direct reuse without significant refactoring impractical.
This repository is a curated list of open-source AWS security tools, organized into categories such as defensive hardening, offensive testing, purple teaming, continuous auditing, DFIR, development security, S3 auditing, and training. It also includes a Packer-based build system to create an Amazon Machine Image (AMI) pre-loaded with many of the listed tools, alongside scripts for cloning tool repositories (install-tools.sh) and generating markdown tables from CSV data (arsenal-kreator.sh). The actual code in the repo is minimal—mainly configuration and simple shell scripts—and the core value is the comprehensive reference list. The AMI build is dated (last manifest from 2018) and many linked tools may have moved or become unmaintained, resulting in significant technical drift. The repo is more of a historic index than an actively developed software project.