AI-Assisted 10 Phases Bug Bounty Ready
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Course Framework

SaaS Product Pentesting
with AI

Train learners to perform end-to-end SaaS product and web application penetration testing using AI-assisted workflows. Covers reconnaissance, vulnerability discovery, exploitation, automation, and professional reporting.

Self-paced 10 Phases Hands-on Labs Bug Bounty Path
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Program Objective

Train learners to perform end-to-end SaaS product & web application penetration testing using AI-assisted workflows. Learners can pursue Bug Bounty after completing the course. The program focuses on leveraging AI for reconnaissance, vulnerability discovery, exploitation, automation, and professional reporting — enabling faster, smarter, and scalable offensive security operations.

Phase 0

AI-First Pentest Mindset

Fully AI-Assisted
  • Role of AI in penetration testing (capabilities vs limitations)
  • Overview of LLM tools — GPT, Claude, Ollama
  • Prompt engineering for security workflows
  • Using AI for troubleshooting and productivity
Phase 1

Foundations & AI-Assisted Lab Architecture

Module 1

Orientation & Professional Ethics

  • Legal boundaries & responsible disclosure
  • Rules of engagement
  • NDA awareness & professional conduct
Module 2

Secure Lab Setup & Environment Design

  • Virtualization — VMs, WSL concepts
  • Kali Linux & Windows lab setup
Module 3

Operating System Mastery

LINUX (KALI)
  • User & privilege management
  • File system
  • File permissions — chmod, chown
  • Service management — systemctl
  • SSH configuration
Phase 2

AI-Assisted Core Technical Foundation

Module 4

Networking Deep Dive

  • IPs and Protocols
  • OSI vs TCP/IP models
  • Subnetting fundamentals
  • Ports & services
  • Firewall basics
  • Packet capture fundamentals
Practical
  • Packet sniffing
  • Manual socket-based port scanner
Module 5

Lab Installations

  • DVWA Lab Setup
  • Metasploitable2 Lab Setup
  • Customized SaaS Product Lab Setup
Module 6

Python for Offensive Security

  • Virtual environments
  • Requests & API handling
  • Socket programming
  • Regex & parsing
  • JSON handling
Practical Projects
Banner Grabber Port Scanner Subdomain Enumerator Log Parser Automation VirusTotal API Integration AbuseIPDB Integration
Phase 3

AI-Assisted Reconnaissance & Enumeration

Module 6

Reconnaissance Engineering

  • Passive vs active recon
  • OSINT fundamentals
  • Google dorking
Tools
NmapAmassSublist3rtheHarvester
Lab
  • Structured recon on target domain
  • Attack surface mapping — Bank lab
Module 7

Scanning & Enumeration

  • Service enumeration
  • SMB & FTP basics
  • Directory brute forcing
  • Vulnerability scanning concepts
Tools
GobusterFFUFNiktoNessus (overview)
Phase 4

AI-Assisted Web & API Security

Module 8

Web Fundamentals

  • HTTP methods & headers
  • Cookies & session management
  • Authentication vs authorization
  • JWT basics
Module 9

OWASP Top 10 — Hands-on

01 SQL Injection
02 Cross-Site Scripting (XSS)
03 IDOR
04 Authentication Flaws
05 CSRF
06 File Upload Vulnerabilities
Labs
  • DVWA exploitation
  • Custom bank lab
Module 10

API Security Testing

  • REST API fundamentals
  • Token handling
  • Broken Object Level Authorization (BOLA)
  • API fuzzing basics
Tools
Burp SuiteOWASP ZAPPostman
Automation
  • Python-based API interaction
  • Testing scripts
Phase 6

AI-Assisted Exploitation & Post-Exploitation

Module 11

Exploitation Techniques

  • Metasploit basics
  • Manual vs automated exploitation
  • Reverse shells
  • Payload fundamentals
Lab
  • Metasploitable exploitation walkthrough
Module 12

Post-Exploitation

  • Privilege escalation basics
  • Password hash concepts
  • John the Ripper basics
  • SSH key handling
  • Persistence overview
Phase 7

AI-Assisted Cryptography & Password Security

Module 13

Cryptography & Password Security

  • Hashing vs encryption
  • MD5, SHA families
  • Salting techniques
  • Symmetric vs asymmetric encryption
  • RSA fundamentals
  • SSH key generation
  • Python cryptography
Phase 8

AI-Driven Reporting & Bug Bounty Workflow

Module 14

Vulnerability Reporting

  • Report structure
  • Risk rating basics
  • Writing Proof of Concept (PoC)
  • Screenshot discipline
  • Writing remediation steps
Phase 9

AI-Powered Custom Tooling

  • Build custom recon tools
  • Automation scripts
  • API integrations

Final Capstone Tracks

Track 1

Bug Bounty Simulation

  • Full reconnaissance
  • Web & API exploitation
  • Report submission
Track 2

Offensive Automation

  • Build recon tools
  • API modules
  • Scanner automation
Track 3

Web Security Audit

  • Full audit of lab
  • Identify vulnerabilities
  • Deliver structured report

Program Outcomes

By the end of this program, learners will be able to:

Perform AI-assisted reconnaissance and attack surface mapping
Identify and exploit SaaS and web vulnerabilities using AI support
Automate penetration testing workflows with AI and Python
Conduct API and SaaS security testing efficiently
Generate professional vulnerability reports using AI
Build intelligent offensive security tools
Participate in bug bounty programs with AI-enhanced productivity