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AI-POWERED // PENETRATION TESTINGPHANTOM
DRAGON_AI
AI that hunts vulnerabilities. 50 modules across a 17-phase pipeline with LLM reasoning, adaptive payloads, exploit-chain discovery, and deep OSINT intelligence, roughly 62,000 lines of Python.
This is the engine our engineers run to deliver every $2,499 pentest, a real person drives it against your systems, then hands you a fixed-price report. It is not a self-serve cloud scanner.
50_MODULES17_PHASE_PIPELINE62K+_LOC
CAPABILITIES
BEYOND_PATTERN_MATCHING
Six capabilities that make this an AI penetration testing tool, not a scanner, it reasons about your systems, it doesn't just pattern-match.
The model is hybrid: automated penetration testing for breadth (50 modules, a 17-phase pipeline, 75+ scanner modules), one human engineer for judgment. Every finding is verified by a person before it reaches your report. Read the full comparison in AI vs manual penetration testing, or see the fixed-price web and API pentest this engine delivers.
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.
Mutation Engine
AI-driven mutation engine and differential analysis test variations beyond a static payload library. Every reported finding is verified by an engineer.
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.
COMPARISON
STANDARD_VS_AI
FEATURETRADITIONALPHANTOM_DRAGON_AI
Detection MethodPattern matchingLLM reasoning + differential
PayloadsStatic libraryAdaptive AI-generated
False PositivesBasic filtering7-strategy + tech-stack veto
OSINTBasic reconDeep SIGINT/HUMINT/COMINT
Exploit ChainsIndividual findingsMulti-step attack graphs
ComplianceManual mappingOWASP/PCI/SOC2/HIPAA/NIST
ReportsPDF/textHTML/PDF/SARIF/MD + AI summaries
DashboardCLI outputReal-time Rich TUI
OUTPUT
DELIVERABLES
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.
EXECUTION
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.
INTEL
FAQ
Q: Is this fully autonomous?
A: No. The 17-phase pipeline automates scanning end to end, but a Ghost Protocol engineer scopes every engagement, drives the run, and verifies every finding before it reaches your report.
Q: What AI models does it support?
A: Ollama (local), OpenAI, GitHub Copilot, and Phantom (custom). The AI layer handles reasoning, payload generation, validation, and report writing.
Q: How does it reduce false positives?
A: 7-strategy validation: deterministic replay, differential analysis, timing correlation, pattern confidence, semantic context, tech-stack veto, and AI reasoning.
Q: What's the scanning coverage?
A: 50 modules across injection, authentication, API security, data exposure, fuzzing, business logic, exploit chains, OSINT deep intelligence, and compliance mapping.
STOP_GUESSING.
START_KNOWING.
Let AI find what manual testing misses. Get a comprehensive assessment with actionable remediation.
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