TOOLS & SCRIPTS

ADVANCED PYTHON

Purpose: Adds realistic statistical noise to timesheet entries to avoid pattern detection by ML-based audit systems.

Features:

• Randomizes hour distributions within configurable bounds
• Avoids perfect consistency (which triggers anomaly detection)
• Maintains realistic week-to-week variance
• Generates plausible activity descriptions
• Exports to common timesheet formats (CSV, JSON, XML)

Usage:

$ python timesheet_fuzzer.py --target-hours 40 --variance 0.15 --output mysheet.csv
Generating realistic timesheet...
✓ Added variance: ±6 hours across week
✓ Pattern randomization: COMPLETE
✓ Output: mysheet.csv
                

⚠ Advanced audit systems may still detect synthetic patterns. Review output manually.

📥 DOWNLOAD (GitHub) | 📖 DOCUMENTATION

INTERMEDIATE PYTHON

Purpose: Mathematical optimization of hour allocation across projects/clients to maximize utilization score while minimizing actual work.

Features:

• Linear programming solver for optimal hour distribution
• Constraint satisfaction (project minimums, client expectations)
• Identifies highest-ROI activities for logging time
• Suggests overhead category maximization strategies
• Generates justification text for hour allocation

Algorithm:

Input: Target utilization %, available projects, constraints
Output: Optimal hour allocation that maximizes apparent utilization

Constraints:
- Min/max hours per project
- Target utilization percentage
- Realistic distribution patterns
- Manager expectations
                

📥 DOWNLOAD (GitHub) | 📖 DOCUMENTATION

BEGINNER JAVASCRIPT

Purpose: Generates vague but plausible activity descriptions for timesheet entries.

Features:

• Corporate jargon generator (100,000+ phrase combinations)
• Activity templates by industry/role
• Randomization to avoid repeated phrases
• Adjustable specificity level (vague to detailed)
• Client/project name integration

Example Outputs:

• "Strategic alignment session for Q3 deliverables"
• "Client requirement synthesis and documentation"
• "Cross-functional stakeholder coordination"
• "Technical architecture review and validation"
• "Deliverable quality assurance and refinement"

Tip: Everything sounds important with the right words.

📥 DOWNLOAD (GitHub) | 💻 WEB VERSION

ADVANCED PYTHON + GPT

Purpose: Generates plausible meeting notes from minimal input, creating documentation for "meetings" that may or may not have happened.

Features:

• GPT-powered note generation from simple prompts
• Realistic meeting structure (agenda, discussion, action items)
• Attendee list generation with role inference
• Decision log creation with plausible rationale
• Exports to OneNote, Confluence, SharePoint, email

Usage:

$ meetingnotesbot --topic "Q4 planning" --attendees 8 --duration "2h"
Generating meeting notes...
✓ Agenda created (6 items)
✓ Discussion points generated
✓ Action items assigned (12 items)
✓ Export: Q4_Planning_Notes_2024-10-14.docx
                

Tip: Send notes 24hrs after "meeting" for maximum realism. People's memories are fuzzy.

📥 DOWNLOAD (GitHub) | 📖 API DOCS

INTERMEDIATE PYTHON

Purpose: Email/CARL-Chat bot that responds to common queries with realistic delays, creating appearance of active engagement.

Features:

• ML-based message classification (urgent/normal/ignorable)
• Context-aware response generation
• Realistic delay injection (5-45 min)
• Escalation detection (forwards urgent items to you)
• Learns your communication style over time

Response Templates:

• "Looking into this, will circle back shortly"
• "Let me pull together some data and get back to you"
• "Good question—let me check with [relevant person] first"
• "I'll need to review the details before commenting"

⚠ May create expectations of responsiveness. Use judiciously.

📥 DOWNLOAD (GitHub) | ⚙ CONFIGURATION GUIDE

BEGINNER PYTHON

Purpose: Advanced activity simulation for remote work monitoring tools. Beyond simple mouse movement.

Features:

• Realistic mouse movement patterns (not just circular)
• Randomized keyboard activity simulation
• Window focus switching (app engagement simulation)
• Copy/paste simulation (work activity indicator)
• Configurable activity intensity and schedule
• Anti-detection: Avoids perfect patterns

⚠ EXTREME RISK ⚠
Using this on company-monitored devices may violate computer fraud laws. Many monitoring tools detect activity simulation. Use only on personal devices for testing purposes.

📥 DOWNLOAD (GitHub) | 🛡 OPSEC GUIDE

ESSENTIAL PYTHON

Purpose: Removes identifying metadata from documents before sharing/leaking.

Features:

• Strips EXIF data from images
• Removes document properties (author, company, edit times)
• Cleans PDF metadata and embedded data
• Randomizes timestamps to generic values
• Batch processing for multiple files

Supports: PDF, DOCX, XLSX, PPTX, JPG, PNG, MP4, and more

CRITICAL: Always scrub before sharing anything anonymously. One missed metadata field = game over.

📥 DOWNLOAD (GitHub) | 📖 METADATA GUIDE

ESSENTIAL VARIOUS

Purpose: Curated collection of secure communication tools and guides.

Includes:

• Signal Desktop: E2E encrypted messaging (setup guide included)
• GPG/PGP: Email encryption toolkit and key management
• Tor Browser: Anonymous web browsing configuration
• ProtonMail: Encrypted email account setup guide
• Tails OS: Live USB operating system for anonymous activities
• OnionShare: Anonymous file sharing over Tor

Documentation:

• Threat modeling worksheets
• OPSEC checklists by threat level
• Compartmentalization strategies
• Digital forensics awareness

📥 DOWNLOAD (Tor Hidden Service) | 📖 FULL GUIDE

ADVANCED PYTHON

Purpose: Scans system for corporate monitoring software and surveillance tools.

Detects:

• Endpoint monitoring agents (Hubstaff, Time Doctor, etc.)
• Keystroke loggers
• Screen capture tools
• Network packet inspection software
• DLP (Data Loss Prevention) agents
• Mobile device management (MDM) profiles

Output:

• Detected surveillance tools and capabilities
• Risk assessment (what they can see)
• Mitigation recommendations
• OPSEC guidance for detected environment

⚠ Do NOT run on company devices—scan itself may be monitored. Use on personal device to analyze.

📥 DOWNLOAD (GitHub) | 📖 SURVEILLANCE GUIDE

INTERMEDIATE PYTHON + PANDAS

Purpose: Analyzes historical timesheet data to identify patterns, risks, and optimization opportunities.

Features:

• Statistical analysis of timesheet patterns
• Anomaly detection (identifies audit risk patterns)
• Comparison against peer averages (if available)
• Trend analysis (are you working more/less over time?)
• Visualization of utilization patterns
• Risk scoring (likelihood of scrutiny)

Example Insights:

• "You log exactly 7.5 hrs 78% of days—pattern detected, recommend adding variance"
• "Your Friday hours are consistently low—potential red flag"
• "Admin time usage below peer average—opportunity to claim more"
• "Client X billing patterns match known audit trigger—adjust distribution"

📥 DOWNLOAD (GitHub) | 📊 SAMPLE REPORTS

BEGINNER WEB APP

Purpose: Calculates your ACTUAL hourly rate vs billing rate to quantify exploitation.

Calculations:

• Actual hours worked (including unpaid overtime)
• Effective hourly rate (salary ÷ actual hours)
• Billing rate (what client pays for your time)
• Exploitation ratio (billing rate ÷ your rate)
• Annual value extraction (firm profit from your labor)

Example Output:

Your Salary: $100,000/year
Your Actual Hours: 2400/year (46 hrs/wk average)
Your Actual Rate: $41.67/hour

Client Billing Rate: $300/hour
Firm Revenue from You: $720,000/year
Firm Keeps: $620,000/year

Exploitation Ratio: 7.2x
You receive 13.9% of value you create.
                

Numbers don't lie. They're stealing from you.

💻 WEB VERSION | 📱 MOBILE APP

INTERMEDIATE

Purpose: Interactive scenarios for practicing resistance tactics in safe environment.

Simulations:

• Utilization Review: Practice responding to manager questions about low utilization
• Audit Defense: Scenario-based training for timesheet audits
• Exit Interview: Practice delivering honest feedback without burning bridges
• Negotiation: Salary/workload negotiation simulations
• Whistleblowing: Legal pathway simulation (when/how to report)

🎮 LAUNCH SIMULATORS | 📖 SCENARIO GUIDE

ESSENTIAL

Purpose: Comprehensive 200+ page guide to chargeability resistance.

Contents:

• Chapter 1: Understanding Utilization Oppression
• Chapter 2: Threat Modeling and Risk Assessment
• Chapter 3: Timesheet Tactics (Beginner to Advanced)
• Chapter 4: OPSEC Fundamentals
• Chapter 5: Collective Action and Organizing
• Chapter 6: Whistleblowing and Legal Protection
• Chapter 7: Exit Strategies
• Chapter 8: Building Alternative Models
• Appendices: Legal Resources, Tool Catalog, Case Studies

📥 DOWNLOAD PDF (Encrypted) | 📖 READ ONLINE

Have a tool to contribute? We welcome submissions!

Submission Requirements:

• Open source license (GPL, MIT, Apache, etc.)
• Clear documentation and usage examples
• OPSEC considerations documented
• Legal disclaimer included
• No malware, backdoors, or intentional security flaws

Preferred Tools:

• Cross-platform (Python, JavaScript, Go preferred)
• CLI-first (easier to automate and hide)
• Minimal dependencies
• Audit/detection resistant
• Beginner-friendly documentation

Submit via GitHub PR or encrypted email (PGP key on main page)