7-Phase Workflow - AutoPentestX

AutoPentestX executes a comprehensive 7-phase penetration testing workflow automatically. Each phase builds on the previous one, creating a complete picture of the target’s security posture.

Complete Workflow Overview

The run_full_assessment() method in main.py:136 orchestrates all seven phases:

def run_full_assessment(self):
    """Execute complete penetration testing workflow"""
    self.start_time = time.time()
    
    # Phase 1: Database initialization
    # Phase 2: Network scanning  
    # Phase 3: Vulnerability detection
    # Phase 4: CVE intelligence
    # Phase 5: Risk assessment
    # Phase 6: Exploitation simulation
    # Phase 7: Report generation

Phase 1: Initialization

Database Setup

The assessment begins with database initialization (main.py:144-159):

print(f"[PHASE 1] Initializing attack sequence...")
self.scan_id = self.db.insert_scan(self.target)
if not self.scan_id:
    print(f"[✗] CRITICAL ERROR: Database initialization failed")
    return False
print(f"[✓] Mission ID: {self.scan_id} | Status: ACTIVE")

Create Scan Record

Generates unique scan ID and creates database entry with timestamp

Verify Database

Ensures SQLite connection is active and tables exist

Initialize Storage

Prepares directories for reports, logs, and exploit scripts

The scan ID tracks all results throughout the assessment and allows historical comparison of scans against the same target.

Phase 2: Network Reconnaissance

Port Scanning & Service Detection

Comprehensive network scanning using Nmap (main.py:161-180):

print(f"[PHASE 2] Network reconnaissance in progress...")
scanner = Scanner(self.target)
self.scan_results = scanner.run_full_scan()

if not self.scan_results:
    print(f"[✗] ABORT: Network reconnaissance failed")
    return False
print(f"[✓] Phase 2 complete - {len(self.scan_results.get('ports', []))} ports discovered")

Scanning Capabilities

TCP Scanning

All 65,535 TCP ports with service detection

UDP Scanning

Top 20 UDP ports for common services

OS Detection

Operating system fingerprinting via TCP/IP stack analysis

Banner Grabbing

Service version identification from banners

Data Collected

Open port numbers
Service names (HTTP, SSH, FTP, etc.)
Service versions (Apache 2.4.41, OpenSSH 8.2p1)
Operating system family and version
Network latency and responsiveness

Database Storage

# Update database with OS detection
self.db.update_scan(self.scan_id, 
                  os_detection=self.scan_results.get('os_detection', 'Unknown'))

# Store each discovered port
for port in self.scan_results.get('ports', []):
    self.db.insert_port(self.scan_id, port)

Phase 3: Vulnerability Analysis

Web Vulnerability Scanning

Deep vulnerability analysis using Nikto and SQLMap (main.py:183-207):

if not self.skip_web:
    print(f"[PHASE 3] Vulnerability analysis initiated...")
    vuln_scanner = VulnerabilityScanner(
        self.target, 
        self.scan_results.get('ports', [])
    )
    self.vuln_results = vuln_scanner.run_full_scan()

This phase can be skipped with --skip-web for faster scans or when web testing isn’t needed.

Detection Methods

Common Vulnerabilities

Checks for default credentials, outdated software, misconfigurations

Web Application Scanning

Nikto scans for web server vulnerabilities, dangerous files, outdated versions

SQL Injection Testing

SQLMap tests for SQL injection points in web applications

Service-Specific Checks

Custom checks for FTP, SSH, SMB, and other common services

Vulnerability Storage

# Store vulnerabilities in database
for vuln in self.vuln_results.get('vulnerabilities', []):
    self.db.insert_vulnerability(self.scan_id, vuln)

# Store web-specific vulnerabilities  
for web_vuln in self.vuln_results.get('web_vulnerabilities', []):
    self.db.insert_web_vulnerability(self.scan_id, web_vuln)

Phase 4: CVE Intelligence

Automated CVE Lookup

Cross-references discovered services with CVE databases (main.py:209-230):

print(f"[PHASE 4] Accessing CVE intelligence database...")
cve_lookup = CVELookup()
services = self.scan_results.get('services', [])
self.cve_results = cve_lookup.lookup_services(services)

CVE Matching Process

Service Identification

Extracts service name and version from scan results

Database Query

Queries CVE databases (NVD, CVE Details) for matching vulnerabilities

CVSS Scoring

Retrieves CVSS scores and severity ratings for each CVE

Exploit Availability

Checks if public exploits exist for identified CVEs

CVE Data Structure

for cve in self.cve_results:
    vuln_data = {
        'port': cve.get('port'),
        'service': cve.get('service'),
        'name': cve.get('cve_id'),
        'description': cve.get('description'),
        'cve_id': cve.get('cve_id'),
        'cvss_score': cve.get('cvss_score'),
        'risk_level': cve.get('risk_level'),
        'exploitable': cve.get('exploitable', False)
    }
    self.db.insert_vulnerability(self.scan_id, vuln_data)

High CVSS scores (7.0+) indicate critical vulnerabilities that require immediate attention.

Phase 5: Risk Assessment

Multi-Factor Risk Calculation

Comprehensive risk analysis combining all vulnerability data (main.py:233-254):

print(f"[PHASE 5] Computing threat matrix...")
risk_engine = RiskEngine()
self.risk_results = risk_engine.calculate_overall_risk(
    self.scan_results,
    self.vuln_results.get('vulnerabilities', []),
    self.cve_results,
    self.vuln_results.get('web_vulnerabilities', []),
    self.vuln_results.get('sql_vulnerabilities', [])
)

Risk Factors

Port Exposure

Number and type of open ports (higher = riskier)

Vulnerability Count

Total vulnerabilities weighted by severity

CVSS Scores

Aggregate CVSS scores from all CVEs

Exploit Availability

Whether public exploits exist for vulnerabilities

Risk Levels

CRITICAL: CVSS 9.0-10.0 or actively exploited vulnerabilities
HIGH: CVSS 7.0-8.9 or multiple serious issues
MEDIUM: CVSS 4.0-6.9 or configuration weaknesses
LOW: CVSS 0.1-3.9 or informational findings
INFO: No security impact, awareness only

Database Update

self.db.update_scan(
    self.scan_id,
    total_ports=len(self.scan_results.get('ports', [])),
    open_ports=len(self.scan_results.get('ports', [])),
    vulnerabilities_found=self.risk_results.get('total_vulnerabilities', 0),
    risk_score=self.risk_results.get('overall_risk_level', 'UNKNOWN'),
    status='completed'
)

Phase 6: Exploitation Simulation

Safe Mode Exploitation

Metasploit integration with safety controls (main.py:256-290):

if not self.skip_exploit:
    print(f"[PHASE 6] Exploit simulation [SAFE MODE]...")
    exploit_engine = ExploitEngine(safe_mode=self.safe_mode)
    
    # Match exploits to vulnerabilities
    matched_exploits = exploit_engine.match_exploits(
        self.vuln_results.get('vulnerabilities', []),
        self.cve_results
    )
    
    # Simulate exploitation
    if matched_exploits:
        self.exploit_results = exploit_engine.simulate_exploitation(
            matched_exploits, 
            self.target
        )

Phase 6 can be skipped with --skip-exploit for compliance requirements or faster assessments.

Exploit Matching

The exploit engine matches vulnerabilities to known exploits (exploit_engine.py:70-117):

def match_exploits(self, vulnerabilities, cves):
    matched_exploits = []
    
    # Match based on service versions
    for vuln in vulnerabilities:
        service = vuln.get('service', '').lower()
        version = vuln.get('version', '').lower()
        
        for key, exploit in self.exploit_db.items():
            if key.lower() in f"{service} {version}":
                matched_exploits.append({
                    'vulnerability': vuln,
                    'exploit': exploit,
                    'confidence': 'HIGH'
                })

Exploit Database

Built-in exploit mappings (exploit_engine.py:22-53):

vsftpd 2.3.4: Backdoor command execution
ProFTPD 1.3.3c: Backdoor vulnerability
EternalBlue (MS17-010): SMB remote code execution
Shellshock: Bash environment variable injection
Drupalgeddon2: Drupal RCE vulnerability

Safe Mode Behavior

In safe mode (default), the tool:

Identifies Exploits

Matches vulnerabilities to Metasploit modules

Simulates Execution

Logs what would happen without actually executing

Generates RC Scripts

Creates Metasploit resource scripts for manual testing

Records Results

Stores simulation results in database

if self.safe_mode:
    print("[*] Running in SAFE MODE - No actual exploitation will occur")
    result = {
        'status': 'SIMULATED',
        'safe_mode': True,
        'result': 'Exploit would be executed in non-safe mode'
    }

Disabling safe mode with --no-safe-mode can cause system damage or instability. Only disable for authorized testing in isolated environments.

Phase 7: Report Generation

Professional PDF Reports

Final phase generates comprehensive documentation (main.py:293-310):

print(f"[PHASE 7] Compiling classified intelligence report...")
pdf_generator = PDFReportGenerator(self.target, self.scan_id)
report_file = pdf_generator.generate_report(
    self.scan_results,
    self.vuln_results.get('vulnerabilities', []),
    self.cve_results,
    self.vuln_results.get('web_vulnerabilities', []),
    self.vuln_results.get('sql_vulnerabilities', []),
    self.risk_results,
    self.exploit_results,
    self.tester_name
)

Report Contents

Executive Summary

High-level overview suitable for non-technical stakeholders:

Overall risk level and score
Critical findings count
Top 5 recommendations
Business impact assessment

Technical Findings

Detailed technical information for security teams:

Complete port scan results
All identified vulnerabilities
CVE details with CVSS scores
Exploit simulation results

Risk Assessment

Comprehensive risk analysis:

Risk calculation methodology
Individual vulnerability ratings
Aggregate risk scoring
Threat prioritization

Remediation Guidance

Actionable recommendations:

Prioritized fix list
Configuration changes
Patch requirements
Compensating controls

Report Formats

PDF: Primary format with professional styling
Database: SQLite for historical analysis
Logs: Text logs for debugging and audit trails
RC Scripts: Metasploit scripts for validation testing

Workflow Execution

Automatic Progress

All phases execute automatically with real-time progress indicators:

╔══════════════════════════════════════════════════════════════════╗
║ [PHASE 1] ▶ Initializing attack sequence...                    ║
╚══════════════════════════════════════════════════════════════════╝
[✓] Mission ID: 12345 | Status: ACTIVE

╔══════════════════════════════════════════════════════════════════╗
║ [PHASE 2] ▶ Network reconnaissance in progress...             ║
╚══════════════════════════════════════════════════════════════════╝
[✓] Phase 2 complete - 15 ports discovered

Error Handling

The workflow includes comprehensive error handling (main.py:324-341):

except KeyboardInterrupt:
    print(f"[!] MISSION ABORT - Operator initiated shutdown")
    if self.scan_id:
        self.db.update_scan(self.scan_id, status='interrupted')
    return False

except Exception as e:
    print(f"[✗] CRITICAL SYSTEM ERROR: {e}")
    if self.scan_id:
        self.db.update_scan(self.scan_id, status='failed')
    return False

All partial results are saved even if the scan is interrupted, allowing you to review findings up to the failure point.

Timeline & Performance

Typical Execution Times

Phase	Time Range	Factors
Phase 1	< 1 second	Database initialization
Phase 2	3-15 minutes	Number of ports, network latency
Phase 3	5-20 minutes	Number of web services, SQLMap depth
Phase 4	1-3 minutes	CVE API response times
Phase 5	< 1 second	Risk calculation
Phase 6	1-5 minutes	Number of matched exploits
Phase 7	1-2 minutes	Report complexity

Total: Typically 10-30 minutes for a complete assessment

What’s Next?

Safe Mode Details

Learn about exploitation safety mechanisms

Run Your First Scan

Execute your first penetration test

CLI Reference

Complete command-line options

Understanding Reports

Interpret generated PDF reports

Get Started

Core Concepts

Guides

Configuration

Troubleshooting

​Complete Workflow Overview

​Phase 1: Initialization

​Database Setup

​Phase 2: Network Reconnaissance

​Port Scanning & Service Detection

​Scanning Capabilities

TCP Scanning

UDP Scanning

OS Detection

Banner Grabbing

​Data Collected

​Database Storage

​Phase 3: Vulnerability Analysis

​Web Vulnerability Scanning

​Detection Methods

​Vulnerability Storage

​Phase 4: CVE Intelligence

​Automated CVE Lookup

​CVE Matching Process

​CVE Data Structure

​Phase 5: Risk Assessment

​Multi-Factor Risk Calculation

​Risk Factors

Port Exposure

Vulnerability Count

CVSS Scores

Exploit Availability

​Risk Levels

​Database Update

​Phase 6: Exploitation Simulation

​Safe Mode Exploitation

​Exploit Matching

​Exploit Database

​Safe Mode Behavior

​Phase 7: Report Generation

​Professional PDF Reports

​Report Contents

​Report Formats

​Workflow Execution

​Automatic Progress

​Error Handling

​Timeline & Performance

​Typical Execution Times

​What’s Next?

Safe Mode Details

Run Your First Scan

CLI Reference

Understanding Reports

Build docs developers (and LLMs) love

Complete Workflow Overview

Phase 1: Initialization

Database Setup

Phase 2: Network Reconnaissance

Port Scanning & Service Detection

Scanning Capabilities

Data Collected

Database Storage

Phase 3: Vulnerability Analysis

Web Vulnerability Scanning

Detection Methods

Vulnerability Storage

Phase 4: CVE Intelligence

Automated CVE Lookup

CVE Matching Process

CVE Data Structure

Phase 5: Risk Assessment

Multi-Factor Risk Calculation

Risk Factors

Risk Levels

Database Update

Phase 6: Exploitation Simulation

Safe Mode Exploitation

Exploit Matching

Exploit Database

Safe Mode Behavior

Phase 7: Report Generation

Professional PDF Reports

Report Contents

Report Formats

Workflow Execution

Automatic Progress

Error Handling

Timeline & Performance

Typical Execution Times

What’s Next?