PhantomDragon AI
v3.1.0 — Dragonfire Edition
AI-powered penetration testing. 50 modules across a 17-phase pipeline with LLM reasoning, adaptive payloads, exploit chain discovery, and deep OSINT intelligence. 48,000+ lines of Python.
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~~~~~~ ~~~~~~ /~~~'Beyond Pattern Matching
LLM Reasoning
Multi-provider AI analyzes responses, confirms vulnerabilities, and generates executive summaries with confidence scoring.
Adaptive Payloads
AI generates context-aware payloads based on target responses, technology stack, and WAF evasion.
Attack Chain Analysis
Discovers multi-step exploit paths combining individual vulnerabilities into real-world attack scenarios.
Zero-Day Discovery
AI-driven mutation engine and differential analysis find novel vulnerabilities beyond known patterns.
7-Strategy Validation
Deterministic replay, differential analysis, AI reasoning, semantic context, and tech-stack veto eliminate false positives.
50 Modules
17-phase scanning pipeline across 50 modules — from OSINT deep intelligence to exploit framework and compliance.
Standard vs AI-Powered
What You Receive
Multi-Format Reports
HTML with risk ring gauges, PDF, SARIF for CI/CD, and Markdown — all AI-enhanced.
Attack Chain Graphs
Interactive exploit path visualizations showing how vulnerabilities chain into real attacks.
Executive Summary
AI-generated business impact analysis with risk scores and board-ready language.
Compliance Mapping
Findings auto-mapped to OWASP, PCI DSS, SOC 2, HIPAA, ISO 27001, NIST, and GDPR.
How It Works
Scope & Deploy
Define targets. AI configures optimal scan profile and phase selection.
Deep Reconnaissance
17-phase pipeline: DNS, tech fingerprint, cloud infra, email security, OSINT.
Intelligent Testing
50 modules with AI reasoning. Adaptive payloads. Exploit chain discovery.
Validated Results
7-strategy validation, FP suppression database, compliance-mapped reports.
Common Questions
Is this fully autonomous?
Yes. Point it at a target and it runs the full 17-phase pipeline autonomously — from reconnaissance through reporting — with an optional agent loop for iterative deep testing.
What AI models does it support?
Ollama (local), OpenAI, GitHub Copilot, and Phantom (custom). The AI layer handles reasoning, payload generation, validation, and report writing.
How does it reduce false positives?
7-strategy validation: deterministic replay, differential analysis, timing correlation, pattern confidence, semantic context, tech-stack veto, and AI reasoning.
What's the scanning coverage?
50 modules across injection, authentication, API security, data exposure, fuzzing, business logic, exploit chains, OSINT deep intelligence, and compliance mapping.