Case Study · 2025
DragonSploit — AI-Powered Vulnerability Scanner
AI · Security · Backend Engineering
The Problem
Traditional vulnerability scanners run the same checks on every target regardless of what technology it's running. This creates two problems: wasted time running irrelevant checks, and too many false positive alerts that developers learn to ignore. The challenge was to build a smarter scanner that understands what kind of system it's scanning and runs only the relevant security tests.
The Solution
Hamed built DragonSploit with an intent-based orchestration engine. Instead of running a fixed list of checks, the engine first analyzes the target to detect what technology stack it's using (WordPress, Nginx, Node.js, etc.) and then dynamically selects the most relevant vulnerability tests to run. An AI layer helps interpret scan intent and route to the right strategy. A deterministic validation layer verifies AI outputs to prevent hallucinations from generating false results.
Technologies Used
- Node.js (orchestration engine)
- AI / LLM integration (intent-based routing)
- Stack detection module (WordPress, Nginx, Node.js, etc.)
- Deterministic validation layer
- Modular probe architecture
Results
By running only relevant checks for each target, the scanner completes faster than static queue-based approaches.
Context-aware stack detection means the scanner doesn't flag issues that don't apply to the target's actual technology.
The engine interprets scanning intent and dynamically selects strategies — no manual configuration required.
A deterministic validation layer confirms AI-generated findings before they're reported, ensuring accuracy.
What This Proves
DragonSploit demonstrates Hamed's ability to combine AI capabilities with practical security engineering — building systems that are not just technically impressive but actually more accurate and useful than traditional approaches.
If you need a security review of your application or want to discuss a custom security tool — contact Hamed.