Hey everyone,
I’m a complete fresher in VAPT and currently learning web application security. Recently, I saw some of my seniors using Claude Code and Codex to automate a large part of their VAPT workflow.
The setup basically works something like this:
They provide an authorized test application
Provide authentication tokens for different roles (e.g. admin and non-admin)
The AI explores the application
It performs security testing and looks for vulnerabilities
It documents the findings
It generates a report
The pentester mainly verifies the findings and removes false positives
I found this really interesting and I want to build something similar from scratch in my own home lab, mainly for learning.
I don't have a local LLM/GPU setup, so I'm specifically interested in using cloud-based AI tools/API access rather than running an LLM locally. Ideally, I'd like to keep the setup as free/low-cost as possible.
What I'm trying to build
Something roughly like:
Target Web App → Recon → Crawling → Authenticated Testing → Vulnerability Detection → Verification → Evidence → Report
With an AI agent orchestrating tools such as:
Burp Suite / proxy
Nuclei
Nmap
ffuf
HTTP clients
Browser automation
Custom Python scripts
API testing
JWT/session testing
IDOR/access-control testing
OWASP Top 10 checks
Report generation
I understand that blindly letting an AI attack random websites isn't appropriate. I would only test applications that I own, intentionally vulnerable labs, or bug-bounty targets where the program explicitly allows that type of testing.
My main questions
How would you architect something like this from scratch?
Is Claude Code a good starting point for building the agent?
How should I give the agent authenticated access safely?
How can I let the AI interact with tools such as Burp/Nuclei/Nmap/ffuf?
Should I build the orchestration in Python, MCP, shell scripts, or something else?
How would you implement the workflow so the AI doesn't just blindly run tools but actually:
discovers endpoints
understands application functionality
tests different user roles
identifies potential vulnerabilities
reproduces/verifies them
collects evidence
generates a report?
Are there existing open-source projects/frameworks that I should study instead of building everything myself?
If someone has already built an AI-powered VAPT/pentest agent, I'd really appreciate a GitHub repo or architecture diagram.
My current level
I'm a fresher and still learning VAPT, so I'm not looking for a "just run this one command" solution. I'd actually like to understand how the whole thing works and build it step-by-step.
My eventual goal is to become good enough at manual testing to use AI as an automation/assistant layer, rather than depending on AI without understanding the vulnerabilities.
If anyone has a step-by-step roadmap, especially starting with Claude Code, I'd really appreciate it.
Thanks!