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PhantomTrace - Quick Start Guide

Welcome to PhantomTrace! This guide will help you get started quickly.

Installation

Prerequisites

  • Python 3.8 or higher
  • pip (Python package manager)

Install Steps

# Navigate to the project directory
cd Anti-forensics

# Install the package
pip install -r requirements.txt
pip install -e .

First Steps

1. Test Installation

# Run a simple test
python -c "from phantomtrace import QuantumDecay; print('✓ PhantomTrace installed successfully!')"

2. Run Your First Example

# Run the complete workflow example
python examples/complete_workflow.py

This will demonstrate all major features in action.

Basic Usage

Command Line Interface

PhantomTrace includes a CLI for quick operations:

# Secure file deletion
phantomtrace quantum-delete sensitive_file.txt --passes 7

# Timestamp manipulation
phantomtrace temporal-fog document.pdf --days-offset -30 --randomize

# Generate decoys
phantomtrace shadow-clone --type mixed --count 50

# Log manipulation
phantomtrace log-smoke system.log --entries 50

# Inject entropy
phantomtrace entropy-inject file.dat --type slack

Python API

Use PhantomTrace programmatically:

from phantomtrace import QuantumDecay, TemporalFog, ShadowClone

# Secure file deletion
qd = QuantumDecay()
qd.quantum_delete("sensitive.txt", passes=7)

# Timestamp manipulation
tf = TemporalFog()
tf.apply_fog("document.pdf", days_offset=-30, randomize=True)

# Generate decoys
sc = ShadowClone()
decoys = sc.create_believable_decoys(count=50)

Module Overview

1. Quantum Decay

Purpose: Secure file deletion with non-deterministic patterns

from phantomtrace import QuantumDecay

qd = QuantumDecay(verify=True, secure_rename=True)
qd.quantum_delete("file.txt", passes=7)
print(qd.get_stats())

2. Temporal Fog

Purpose: Sophisticated timestamp manipulation

from phantomtrace import TemporalFog

tf = TemporalFog()
tf.apply_fog("file.txt", days_offset=-30, break_correlation=True)

3. Shadow Clones

Purpose: Generate believable decoy files and activities

from phantomtrace import ShadowClone

sc = ShadowClone(output_dir="./decoys")
decoys = sc.create_believable_decoys(activity_type='mixed', count=50)

4. Memory Whisper

Purpose: RAM-only operations with secure memory wiping

from phantomtrace import MemoryWhisper

mw = MemoryWhisper()
addr = mw.allocate_secure_memory(1024 * 1024)  # 1MB
# ... use memory ...
mw.secure_wipe_memory(addr, 1024 * 1024)

5. Data Camouflage

Purpose: Multi-layer steganography with polymorphic encoding

from phantomtrace import DataCamouflage

dc = DataCamouflage()
dc.hide_in_image(
    secret_data=b"secret message",
    cover_image_path="cover.png",
    output_path="stego.png"
)

6. Log Smoke

Purpose: Log manipulation and noise injection

from phantomtrace import LogSmoke

ls = LogSmoke()
ls.inject_noise("system.log", num_entries=50)

7. Entropy Injector

Purpose: Inject randomness to break pattern analysis

from phantomtrace import EntropyInjector

ei = EntropyInjector()
ei.inject_file_slack("file.dat")
ei.poison_file_carver("./directory", num_files=100)

Common Workflows

Privacy Protection Workflow

from phantomtrace import QuantumDecay, TemporalFog, EntropyInjector

# 1. Modify timestamps before deletion
tf = TemporalFog()
tf.apply_fog("sensitive.txt", randomize=True)

# 2. Inject entropy
ei = EntropyInjector()
ei.inject_file_slack("sensitive.txt")

# 3. Securely delete
qd = QuantumDecay()
qd.quantum_delete("sensitive.txt", passes=7)

Decoy Generation Workflow

from phantomtrace import ShadowClone, TemporalFog

# 1. Create decoys
sc = ShadowClone()
decoys = sc.create_believable_decoys(count=100)

# 2. Apply realistic timestamps
tf = TemporalFog()
for decoy in decoys:
    tf.apply_fog(decoy, randomize=True)

Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=phantomtrace

# Run specific test file
pytest tests/test_modules.py -v

Best Practices

  1. Always backup important data before using destructive operations
  2. Test in isolated environments first
  3. Understand the legal implications in your jurisdiction
  4. Use appropriate pass counts for your threat model
  5. Combine multiple techniques for better results

Troubleshooting

Import Errors

# Make sure PhantomTrace is installed
pip install -e .

# Check Python version
python --version  # Should be 3.8+

Permission Errors

Some operations require elevated privileges:

# Windows (Run as Administrator)
# Right-click Command Prompt → Run as Administrator

# Linux/Mac
sudo python script.py

Module Not Found

# Install missing dependencies
pip install -r requirements.txt

# For optional features
pip install scapy  # Network features
pip install pillow  # Image steganography

Next Steps

  1. Explore Examples: Check the examples/ directory
  2. Read Documentation: See docs/ for detailed information
  3. Read Research: Check docs/research.md for academic background
  4. Contribute: See CONTRIBUTING.md to contribute

Getting Help

  • Issues: Open an issue on GitHub
  • Questions: Start a discussion
  • Security: Report privately

Disclaimer

⚠️ Important: This tool is for educational, research, and authorized security testing only. Users are responsible for ensuring their use complies with applicable laws.

Happy researching! Use PhantomTrace responsibly.