Research Methodology

Scientific methods, data collection techniques, and analysis processes used in the July 4th Anomaly analysis

1. Data Collection Methodology

Blockchain Data Mining

  • Primary Source: Bitcoin Core Full Node (v25.0)
  • Data Range: July 1, 2025 - July 10, 2025
  • Blocks Analyzed: 850,000 - 851,500 range
  • Transaction Count: ~2.1 million transactions examined

OP_RETURN Message Analysis

  • Hex Code Parsing: Automated parsing with Python scripts
  • Text Analysis: UTF-8 and ASCII encoding checks
  • Timestamp Correlation: Matching transaction times with message content

Website Archaeology

  • Wayback Machine: salomonbros.com domain history
  • DNS Records: WHOIS and DNS propagation analysis
  • SSL Certificate Analysis: Let's Encrypt certificate history

2. Cryptographic Analysis Methodology

ECDSA Vulnerability Analysis

  • Nonce Reuse Detection: r-value correlation analysis
  • Lattice Reduction: Private key recovery using LLL algorithm
  • Signature Malleability: DER encoding anomalies

Address Analysis

  • P2PKH vs P2SH Comparison: Address format security analysis
  • Vanity Address Detection: Special pattern search
  • Clustering Analysis: Address ownership correlation

3. Hypothesis Development Process

Multi-Scenario Analysis

  • Brainstorming: Listing all possible scenarios
  • Evidence Weighting: Scoring supporting evidence for each hypothesis
  • Occam's Razor: Prioritizing the simplest explanation

Peer Review Process

  • Cryptography Experts: Technical analysis validation
  • Blockchain Developers: Code and transaction analysis
  • Security Researchers: Attack vector assessment

4. Data Validation and Quality Control

Cross-Validation

  • Multiple Blockchain Explorers: Blockchair, Blockchain.info, Mempool.space
  • Independent Node Control: Data comparison across 3 different full nodes
  • Hash Verification: Manual verification of all transaction hashes

Error Margin Calculation

  • Timestamp Uncertainty: ±10 minute tolerance
  • Amount Calculations: Satoshi-level precision
  • Probabilistic Analyses: 95% confidence interval

5. Ethical Standards

Privacy and Security

  • Anonymization: Concealing real person identities
  • Responsible Disclosure: Responsible reporting of security vulnerabilities
  • Legal Compliance: International research ethics standards

Academic Integrity

  • Source Documentation: Detailed records of all references
  • Conflict of Interest: No financial connections present
  • Transparency: Complete documentation of analysis process

6. Limitations and Constraints

Technical Limitations

  • Blockchain Transparency: Invisibility of off-chain activities
  • Time Constraints: Real-time analysis challenges
  • Computational Power: Cryptographic analysis capacity

Methodological Constraints

  • Speculative Analysis: Situations lacking definitive proof
  • Bias Risk: Impact of researcher preconceptions
  • Data Gaps: Inaccessibility of some critical information