Automated Bug Bounty Reconnaissance Frameworks

This project serves as a centralized, community-driven repository of technical knowledge and administrative resources. It provides a structured taxonomy that aggregates disparate information into a searchable framework, supporting continuous learning and rapid problem-solving for system administrators and cybersecurity practitioners. By mapping resources across offensive security, infrastructure management, and software development, it offers a unified path for skill acquisition and professional reference. The project is defined by a command-line-first design philosophy, prioritizing terminal-based utilities and scriptable interfaces to facilitate efficient system administration and repeatable security workflows. It distinguishes itself through a platform-agnostic approach, maintaining documentation and operational guides that remain applicable across diverse Unix-like and cloud-based environments. This modular toolchain integration allows users to compose custom environments tailored to specific administrative or security tasks. The repository covers a broad capability surface, including comprehensive toolkits for system auditing, network management, and infrastructure hardening. It provides structured learning paths for cybersecurity skill development, ranging from ethical hacking labs and penetration testing standards to vulnerability assessment and system configuration best practices. The collection also encompasses a wide array of productivity tools, diagnostic utilities, and educational materials designed to streamline routine maintenance and enhance overall security posture.

This project is an automated security testing suite designed to detect and exploit database vulnerabilities. It functions as a command-line utility that streamlines the identification, verification, and exploitation of web application flaws by automating the injection of malicious payloads into input parameters. The tool provides a comprehensive framework for database enumeration, allowing users to extract schema information, user data, and system configurations from identified injection points. What distinguishes this tool is its sophisticated engine for dynamic payload adaptation and heuristic fingerprinting, which adjusts injection techniques in real-time based on server responses. It supports advanced post-exploitation capabilities, including remote command execution on the underlying host operating system and file system access through database-level vulnerabilities. To navigate restricted environments, the software incorporates out-of-band data exfiltration channels and a middleware pipeline for applying user-defined transformations to bypass security filters and web application firewalls. The suite covers a broad range of operational requirements, including stateful session management, anti-CSRF token handling, and extensive request customization. It supports various target specification methods, such as proxy log analysis and remote API management, while offering granular control over scan performance and detection thresholds. The software is distributed as a command-line application, with configuration management supported through external file loading and command-line arguments.

Subfinder is a passive subdomain enumeration tool and DNS asset discovery utility designed for mapping the external attack surface of a domain. It functions as a passive reconnaissance framework that identifies subdomains by querying curated third-party data sources and APIs without interacting directly with the target infrastructure. The tool utilizes a modular provider interface to integrate various passive sources and employs concurrent request orchestration to manage simultaneous network queries. It includes wildcard DNS filtering to identify and remove catch-all records, ensuring the resulting list contains unique and valid hosts. The utility is designed for security toolchain integration, supporting pipeline-based data streaming through standard input and output chaining. It provides capabilities for multi-format result export and includes a software development kit to embed the enumeration engine into other applications.

This project is a comprehensive cybersecurity tool collection designed to support security research, penetration testing, and vulnerability assessment. It functions as a unified penetration testing suite, providing a centralized environment where professionals can access a wide range of offensive security utilities to identify system weaknesses and study attack vectors. The platform distinguishes itself through a modular architecture that aggregates disparate security scripts into a single, hierarchical command-line interface. It simplifies the management of these utilities by integrating external repositories, allowing users to fetch and organize third-party tools directly into a structured local directory. By utilizing a categorized menu system and shell-based process execution, the suite enables efficient navigation and direct invocation of specialized tools for tasks ranging from forensic analysis and reverse engineering to exploit development. The toolkit covers a broad spectrum of security domains, including web and wireless attack vectors, cloud security, payload creation, and social media analysis. It also incorporates automated environment setup to handle the installation of necessary system packages and language runtimes, ensuring compatibility across its diverse collection of utilities.

A comprehensive curated list of available Bug Bounty & Disclosure Programs and Write-ups.

The framework is a comprehensive penetration testing platform designed for the development, testing, and execution of security exploits. It serves as a research toolkit and automated assessment environment, enabling security professionals to identify and validate vulnerabilities within networked systems and infrastructure through repeatable, standardized procedures. The platform distinguishes itself through a modular architecture that supports reflective payload injection, allowing for the execution of code directly in memory without writing to disk. It utilizes an asynchronous event loop to manage high-performance, concurrent network connections and features a transport-agnostic communication layer that abstracts protocols to maintain persistent command and control. Users can extend the core functionality through a plugin system and define complex exploit logic using a domain-specific language. The framework provides robust capabilities for remote payload management, including the configuration of network settings like sleep intervals and timeout thresholds. It maintains state persistence across long-running sessions by storing discovered host information and vulnerability data in a relational database. The software is designed for cross-platform deployment, with installation support available for Linux, macOS, and Windows environments.

Subfinder is a security reconnaissance framework designed for subdomain enumeration and attack surface management. It functions as a discovery engine that identifies and maps internet-exposed infrastructure, cloud-hosted assets, and network ranges to maintain a comprehensive inventory of an organization's digital footprint. The project distinguishes itself through a modular, template-driven scanning engine that executes security checks against discovered assets. It leverages cloud-native asset discovery to query provider APIs and infrastructure metadata, while supporting distributed agent orchestration to parallelize discovery workloads across remote nodes. For dynamic web application analysis, the tool incorporates headless browser rendering to execute client-side code and capture visual state. The platform provides a broad capability surface for security operations, including asynchronous interaction monitoring to detect blind vulnerabilities and server-side request forgery. It features a domain-specific language for granular filtering of scan results and supports pipeline-oriented data streaming to integrate findings into external security tools and reporting systems. The software is implemented in Go and provides a command-line interface for executing discovery tasks and managing security workflows.

MediaCrawler is an automated web scraping framework designed to extract public posts, comments, and creator metadata from various social media platforms. It functions as a headless browser automator, utilizing real browser instances to render dynamic content and execute the client-side scripts necessary for interacting with modern web interfaces. The system distinguishes itself through a focus on session persistence and network flexibility. It supports remote debugging to reuse active browser sessions and cookies, which helps minimize the risk of triggering platform security challenges. To maintain stable data collection at scale, the tool integrates proxy-based request routing, allowing users to distribute traffic across external IP services to bypass rate limits and geographic restrictions. The architecture is built for extensibility and modularity, employing a provider pattern that allows developers to integrate new platforms or custom storage backends through standardized interfaces. Users can manage complex scraping workflows via command-line configuration, enabling the definition of specific targets and storage formats—such as JSON, CSV, or various database systems—without modifying the core logic. The project also includes utilities for data visualization, such as generating word clouds from collected comments. Installation requires setting up the necessary runtime environments, including a JavaScript engine for handling complex client-side rendering and the appropriate browser automation drivers.

reconftw is an attack surface management framework and reconnaissance workflow orchestrator designed to automate the discovery, mapping, and monitoring of external digital assets. It operates as a modular tool-chain pipeline that coordinates a sequence of security tools to perform intelligence gathering and vulnerability scanning. The project distinguishes itself through a cloud-native deployment model that parallelizes scanning workloads across a fleet of remote VPS instances to bypass local resource constraints. It utilizes container-based environment isolation to ensure consistent execution across different cloud providers and features a checkpoint system to resume interrupted workflows from the last point of failure. The toolkit covers a broad range of capabilities, including passive and active subdomain enumeration, open-source intelligence gathering, and network infrastructure analysis. It also incorporates automated vulnerability scanning for common web flaws and CVEs, differential asset tracking to identify new targets, and the generation of security reports using artificial intelligence. The environment can be deployed via container orchestration and integrated into CI/CD pipelines for recurring security checks.

Gitleaks is a security scanning engine designed to identify hardcoded credentials, API keys, and other sensitive information within version control systems and local file structures. It functions as a static analysis tool that automates the detection of secrets, helping to prevent the accidental exposure of sensitive data during the development lifecycle. The tool distinguishes itself through its ability to perform deep forensic analysis of git history, allowing users to audit entire project timelines or enforce security gates within continuous integration pipelines. It supports complex detection logic through composite rules and provides mechanisms for baseline management, which enables teams to ignore existing findings and focus exclusively on new security risks. By offering pre-commit hook integration and exit-code-based orchestration, it allows for the enforcement of security policies directly within developer workflows and automated build environments. Beyond core scanning, the project provides a broad set of utilities for managing security findings, including support for decoding obfuscated strings, inspecting compressed archives, and filtering results through allowlisting or path exclusions. It facilitates compliance and reporting by exporting structured data, which can be integrated into external dashboards or tracking systems. The tool is built to handle various input sources, including direct file system traversal and standard input streams, ensuring compatibility with diverse development and deployment environments.

HowToHunt is a bug bounty hunting knowledge base and a structured guide for web application penetration testing. It provides a research methodology for organizing security testing procedures and validating application behaviors against known vulnerability patterns. The project features a curated library of security flaws and reconnaissance techniques. It organizes security testing into modular playbooks, checklists, and categorical vulnerability mappings to align specific exploitation techniques with target weaknesses. The repository covers a systematic sequence of information gathering tasks for web security reconnaissance and the identification of potential attack vectors. It also includes a framework for web vulnerability research and the validation of security flaws through test-case-driven processes.

This project is a comprehensive, community-sourced knowledge base designed for security professionals and researchers. It functions as a centralized repository of offensive security techniques, providing a structured collection of exploit payloads, attack vectors, and methodologies for conducting vulnerability assessments and penetration testing. The repository distinguishes itself through a cross-platform payload taxonomy that categorizes exploitation methods by vulnerability type and target environment, enabling rapid lookup during security assessments. It maintains high standards of data integrity and collaborative growth by utilizing version-controlled knowledge management and template-driven content generation, ensuring that the research remains current and consistent across a wide range of technical domains. The project covers a broad capability surface, including detailed references for web application security, database injection, insecure deserialization, and AI model security testing. It also aggregates external resources, such as research papers and third-party tools, to provide a holistic view of modern threat analysis and defensive research. The documentation is organized as a hierarchical tree of markdown files, designed for easy navigation and reference during active security engagements.

MHDDoS is a command-line utility designed for volumetric stress testing and infrastructure resilience assessment. It functions as a comprehensive framework for simulating high-volume network and application layer traffic to evaluate the capacity and stability of web services and network infrastructure. The tool distinguishes itself through its ability to generate complex, protocol-specific traffic patterns and raw packet structures. By employing dynamic header randomization and specialized payload injection, it simulates diverse request behaviors intended to test the effectiveness of security filters and protection services. It also includes integrated capabilities for infrastructure reconnaissance, allowing users to resolve network details and identify server endpoints prior to testing. The framework covers a broad spectrum of testing methodologies, ranging from application-layer request flooding to network-layer resource exhaustion. It supports both transport-layer packet crafting and high-concurrency web traffic simulation to identify bandwidth bottlenecks and processing limits. The project is distributed as a collection of scripts and is accessible via a command-line interface.

Lighthouse is an automated diagnostic tool that evaluates web pages against industry standards for performance, accessibility, and search engine optimization. It functions as a programmatic analysis engine and a command-line utility, allowing developers to integrate comprehensive web quality checks directly into continuous integration pipelines and local development workflows. The project distinguishes itself through a modular architecture that utilizes artifact-based data collection to ensure consistent analysis across different environments. It supports a headless execution mode for automated testing and provides a plugin-driven framework, enabling developers to register custom audit logic and specialized reporting categories to meet unique project requirements. Beyond its core auditing capabilities, the tool detects underlying web frameworks and content management systems to provide tailored optimization recommendations. It generates structured, machine-readable reports and offers multiple interfaces, including a browser-integrated panel and a dedicated extension, to facilitate real-time feedback during the development process.

Some public notes

Firecrawl is a web data extraction platform designed to convert unstructured web content into clean, LLM-ready formats like markdown or JSON. It functions as an autonomous web crawler and scraper, capable of mapping entire domains, performing recursive navigation, and executing complex data gathering tasks. By leveraging headless browser orchestration, the system handles dynamic, JavaScript-heavy pages to ensure comprehensive data capture. The platform distinguishes itself through its focus on agentic workflows, providing a programmatic interface that allows autonomous agents to perform live web research, interact with pages, and execute multi-step navigation tasks. It supports distributed crawling infrastructure, enabling users to scale data collection across multiple nodes while managing concurrency and long-running jobs through asynchronous queueing. The system also integrates with agentic frameworks via standardized protocols, allowing for seamless connection to AI-powered clients and automated pipelines. Beyond its core extraction capabilities, the project provides a suite of developer tools for site mapping, batch scraping, and web searching. It includes features for stateful session persistence, webhook-based notifications, and configurable crawl depth, allowing for granular control over how information is retrieved and processed. The project offers comprehensive API documentation and SDKs to facilitate integration into backend services and local development environments. Users can deploy the crawling infrastructure within their own private networks or utilize managed cloud services.

PentestGPT is an autonomous security testing framework that leverages large language models to plan, execute, and coordinate end-to-end penetration testing engagements. By functioning as an autonomous agent, the system automates the entire testing lifecycle, from initial reconnaissance and vulnerability analysis to the generation of custom exploits and the execution of post-exploitation tasks. The platform distinguishes itself through a multi-agent orchestration system that coordinates specialized AI agents to collaborate on complex, multi-stage attack chains. It integrates multimodal context, synthesizing both visual and textual data to inform its decision-making process. To ensure consistency and continuity, the framework maintains persistent session state, allowing users to pause and resume assessments without losing critical context or progress. The system provides a comprehensive suite of capabilities for managing external security utilities, including the ability to parse raw command-line output into structured data for automated analysis. It operates within isolated, containerized environments to ensure that testing workflows remain reproducible and secure across diverse target architectures.

SecLists is a centralized library of security assessment data designed to support vulnerability discovery and penetration testing. It functions as a comprehensive repository of wordlists, payloads, and testing methodologies used to audit software, firmware, and internet-connected hardware for technical vulnerabilities. The project distinguishes itself through a standardized taxonomy and a language-agnostic data format, which allows security tools to predictably ingest and utilize its assets regardless of the underlying programming environment. By decoupling raw testing data from execution logic, the repository ensures that its collections of usernames, passwords, and injection patterns remain portable and compatible with a wide range of custom auditing frameworks and automated security tools. The collection covers a broad spectrum of security testing domains, including brute-force credential testing, web application fuzzing, and automated vulnerability scanning. It also provides structured guidance for firmware analysis and internet-connected device hardening, enabling researchers to apply consistent methodologies when identifying insecure configurations or potential system flaws. The repository is organized as a collection of flat-file assets within a hierarchical directory structure, facilitating integration into automated security workflows.

Inspired by https://github.com/djadmin/awesome-bug-bounty, a list of bug bounty write-up that is categorized by the bug nature

Colly is a high-performance web scraping framework designed for the automated extraction of structured data from websites. It provides a programmable toolkit that manages the complexities of large-scale data collection, including concurrent request orchestration, automatic cookie handling, and robots.txt compliance. By utilizing an asynchronous execution model, the engine maintains high throughput while preventing resource exhaustion during recursive or distributed crawling tasks. The framework is distinguished by its modular, event-driven architecture, which allows developers to hook into specific lifecycle stages of a network request to process content or control flow. It features a flexible middleware pipeline for handling proxy rotation, user agents, and rate limiting, alongside an interface-driven storage layer that supports swapping default in-memory state for persistent external databases. This design enables the coordination of multiple scraping instances and the maintenance of crawl history across application restarts. Beyond its core engine, the project offers extensive customization options for network transport, including support for custom round-trippers to manage connection pooling and timeouts. It also provides robust observability tools, allowing for the attachment of custom debuggers and logging observers to monitor internal state during execution. Developers can further extend functionality through a plugin system or by sharing request context and configuration across different collector instances to support complex, multi-stage data extraction workflows.