sqlmap is an automated penetration testing tool that detects and exploits SQL injection vulnerabilities in web applications. Its core functionality includes database fingerprinting, data extraction (tables, columns, users, passwords), file system read/write, OS command execution, and out-of-band exfiltration via DNS or ICMP. The architecture is a modular monolith: a central controller orchestrates DBMS-specific plugins (30+ databases), injection technique engines (boolean blind, error-based, UNION, time-based, stacked queries, DNS, OData, SPARQL, JWT, NoSQL, etc.), and tamper scripts for WAF bypass. The tool exposes both a CLI (sqlmap.py) and a REST API (sqlmapapi.py). External dependencies are minimal—most third-party libraries are vendored (chardet, colorama, beautifulsoup, pydes, fcrypt). The codebase demonstrates deep knowledge of SQL dialects, HTTP protocol handling, and security research, with extensive offline test suites and deterministic test harnesses. Notable technical strengths include pure-Python protocol clients (TDS, Kerberos, gRPC-Web), disk-spilling data structures (BigArray), and a safe JSON serializer that replaces pickle. Drift risks include remnants of Python 2 compatibility shims, bundled crypto implementations, and static fingerprinting data that may lag behind new DBMS versions.
This is the official OWASP Cheat Sheet Series repository, providing concise, actionable security guidance for developers. It contains over 150 markdown cheat sheets covering web application security, cloud security, AI security, and more. The repository is primarily a documentation project but includes a sophisticated build system (MkDocs, Docker, CI/CD) and tooling for quality assurance: markdown linting, link checking, text linting, and automated PR review agents. The link checker is a standout reusable component with modular architecture. The project is actively maintained with strict quality gates and a well-defined contribution process.
The OWASP Web Security Testing Guide (WSTG) is a comprehensive, community-maintained documentation project defining standard test cases for web application security assessments. It is primarily a structured knowledge base written in Markdown, organized by testing categories including Information Gathering, Authentication, Injection, and API Testing. The repository also serves as the source for multiple derived artifacts: a Jekyll static website (wstg.owasp.org), downloadable PDF/EPUB ebooks via a Pandoc+Typst pipeline, and machine-readable test checklists in JSON, XLSX, and Markdown formats. The build infrastructure includes Python scripts for site generation and navigation, GitHub Actions for CI/CD (linting, link checking, deployment), and a versioned release process that supports multiple channels (latest, stable, past versions). Although the primary content is documentation, the repository functions as a publication platform with significant automation and is actively maintained by a community of contributors. It is not a software application in the traditional sense, but the build tooling and CI/CD pipelines qualify it as an application-focused project with strong data engineering characteristics in its checklist generation and structured content management.
Garden is a one-URL automated asset discovery and passive security scanning tool designed for authorized targets. It performs passive, read-only scans (bounded GET requests within same-origin boundaries) without active exploitation. The tool supports two primary modes: quick (anonymous) scans and authenticated coverage analysis across three fixed contexts (anonymous, user, admin). Outputs include structured Markdown reports with asset inventory, evidence, security control observations, and explicit coverage gap explanations, emphasizing that zero findings do not imply safety unless coverage is fully qualified. The architecture is a Python 3.10+ application using FastAPI for the web API, Typer for the CLI, SQLAlchemy with Alembic for database management, and Playwright for browser automation during login and inventory collection. The system follows a service layer pattern shared by CLI, Web, and API entry points, with a multi-stage pipeline (validate → collect → normalize → compare coverage → replay authorization → analyze → report) orchestrated by ScanApplicationService. External dependencies include httpx for HTTP requests, Pydantic for data validation, and Jinja2 for templating. Garden is positioned as an internal AppSec workflow for post-authentication verification of authorized application surfaces, not as a general-purpose vulnerability scanner like Burp or ZAP. It features centralized redaction of sensitive data across all outputs, an ephemeral secret store for temporary credential handling, and a plugin-based security check system with six built-in low-risk checks. The codebase includes extensive test coverage (unit, integration, e2e), a comprehensive threat model, and detailed implementation plans for versioned releases (v0.2 trusted report quality, v0.3 passive authenticated coverage).
DefectDojo is an open-source application security posture management (ASPM) and vulnerability management platform. It ingests scan results from over 100 security tools (SAST, DAST, SCA, container, cloud, secrets, infrastructure) via a consistent parser interface, normalizes findings, deduplicates them, and tracks remediation workflows across engagements and products. The system is a Django monolith with a REST API (Django REST Framework), Celery async workers for imports, SLA enforcement, and JIRA/GitHub sync, PostgreSQL for persistence, and Valkey/Redis as the message broker. Key entry points include the Django admin UI, DRF API viewsets, and Celery task dispatchers. External dependencies are PostgreSQL, Redis/Valkey, and optional integrations with JIRA, Slack, Microsoft Teams, and SSO providers (LDAP, OAuth2, SAML). The repository includes a Pro edition layer with additional features (custom RBAC, audit logging, priority SLA) that coexist with the open-source core via feature flags and conditional imports. The codebase demonstrates strong engineering with a well-defined parser factory pattern, prefetch mixins for API efficiency, SSRF-safe HTTP clients, and a request-level caching system, though it carries some technical debt from an ongoing V3 location model migration and numerous deprecated endpoints slated for removal.
SILENTCHAIN AI™ Community Edition is a Burp Suite extension that performs AI-powered passive vulnerability scanning of HTTP traffic. It intercepts requests/responses through Burp's proxy, sends them to configurable AI providers (Burp AI, Ollama, OpenAI, Claude, Gemini, Azure), and generates OWASP Top 10 vulnerability findings. The extension features a modular architecture with a thread pool for background AI processing, Swing-based UI integrated into Burp Suite, and persistence for settings via Burp's preferences API. Key capabilities include bidirectional data sanitization to prevent leaking secrets to AI providers, robust JSON parsing for handling LLM output inconsistencies, layered HTTP filtering (scope, content-type, rate limiting, URL deduplication), and real-time UI updates showing findings, task status, and statistics.
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.
This repository serves as the central community hub for the freeRASP mobile security SDK. It does not contain any source code itself; instead, it aggregates platform-specific implementations (Android, iOS, Flutter, React Native, etc.) via Git submodules. The actual security detection logic, integration APIs, and threat monitoring are implemented in the respective submodule repositories. This meta-repo provides documentation, issue tracking, and release coordination across platforms. It is well-maintained with active issue triage and a CI workflow for issue monitoring. The project is licensed under MIT with a fair usage policy.