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Basic Information

Reaper is an open-source application security testing framework designed for application security analysts, penetration testers, and bug bounty hunters. It unifies multiple stages of appsec testing into a single workflow by combining reconnaissance, request proxying, request tampering and replay, active testing, vulnerability validation, collaboration, and reporting. The project emphasizes a modern, lightweight, and extensible architecture that can be used interactively by humans or orchestrated by AI agents. Reaper is positioned as a platform for running autonomous workflows and for integrating LLM-powered agents to assist with repetitive or complex tasks. The repository includes documentation and a getting-started guide, is actively developed, and is distributed under the Apache 2.0 license.

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App Details

Features
Reaper centralizes core application security testing capabilities: reconnaissance, request proxying, request tampering and replay, active testing, and vulnerability validation. It supports live collaboration and consolidated reporting to streamline team workflows. The design is lightweight and extensible to allow plugins or extensions and to adapt to varying testing needs. Reaper is built to be orchestrated by AI, with explicit mention of LLM-powered AI agents to automate tasks and run autonomous workflows. The project provides documentation for installation and usage and emphasizes maintainability and extensibility as part of its core design goals.
Use Cases
Reaper reduces manual effort and the complexity of juggling multiple discrete tools by stitching reconnaissance, proxying, tampering, active tests, validation, and reporting into a single workflow. By enabling AI agent orchestration, it accelerates repetitive tasks such as parameter tuning, data analysis, findings summarization, and report generation. The framework aims to decrease security engineer burnout by automating routine activities while preserving human oversight for critical decisions. Its extensible architecture makes it adaptable to different testing programs and allows teams to run autonomous workflows that scale testing throughput and consistency.

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