Lazarus High Risk Bybit Hacking Investigation [CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001] - Wallet Analysis Report - Very High Risk - 0x4b75...25f2
Published
14 Jul 2025
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Wallet Name
Analysis Target Wallet (CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001) - 0x4b75...25f2
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Overview
Project Scope
Analysis of wallet 0x4b75736fb79269cf995d31595fd01b8e67fd25f2 - Lazarus High Risk Bybit Hacking Investigation
Suspicious Wallet Hash
0x4b75736fb79269cf995d31595fd01b8e67fd25f2
This is the primary wallet address being investigated in this report.
Methodology
Research Methodology
Automated Analysis Methodology for Wallet 0x4b75736fb79269cf995d31595fd01b8e67fd25f2
1. Data Collection
- Automated transaction retrieval from blockchain
- Historical transaction pattern analysis
- Network connection mapping
2. Analysis Algorithms
- Multi-algorithm approach using 10 detection methods
- Statistical anomaly detection
- Behavioral pattern analysis
- Network-based risk assessment
3. Risk Scoring
- Weighted risk factor calculation
- Multi-dimensional analysis
- Historical comparison baseline
- Real-time pattern detection
4. Report Generation
- Automated findings compilation
- Risk level determination
- Recommendation synthesis
- Compliance-ready documentation
Data Collection
Data Collection Process for 0x4b75736fb79269cf995d31595fd01b8e67fd25f2
1. Blockchain Data Retrieval
- Retrieved 10 analysis data points
- Collected complete transaction history
- Gathered network connection data
2. Analysis Processing
- Applied multiple detection algorithms
- Performed statistical analysis
- Generated risk indicators
- Created behavioral profiles
3. Quality Assurance
- Data validation checks
- Algorithm consistency verification
- Result accuracy confirmation
Data Preprocessing
Data Preprocessing Steps:
1. Data Cleaning
- Removed duplicate transactions
- Standardized timestamp formats
- Validated transaction data integrity
2. Feature Engineering
- Created time-based features
- Calculated statistical metrics
- Generated network features
3. Normalization
- Applied consistent scaling
- Handled missing values
- Optimized for analysis algorithms
Design Pattern
No design pattern information is available for this report.
Analysis
General Analysis Summary for 0x4b75736fb79269cf995d31595fd01b8e67fd25f2
Risk Level: Very High Risk Score: 100/100 Total Issues Identified: 40 Suspicious Transactions: 10
Key Findings: - Automated analysis detected 10 suspicious transactions - Risk assessment indicates very high risk level - 40 total suspicious patterns identified across all algorithms - Standardized risk score: 100/100
Analysis Confidence: High (automated multi-algorithm approach) Recommendation: Immediate investigation required
No suspicious patterns detected.
0x1498099a8c59f85ae858af561731589d45128c64ff1a0023cb8e028c464096ef: Very short time between transactions
0x3ec03dd9c8c5e4d78d68c6db13f192c1d6f7a93976bc4c5262599b90ce6462bc: Very short time between transactions
0x0860e40b4aebb5bffc674ca4bf8aaf11adebf46fba10705c63f413be8e20e5d3: Very short time between transactions
0x271006e6083b206e2040da0a1ba173803a23af15587078978825fd83701089db: Very short time between transactions
0xf58cdb9c1fd35a69d5ef50f49cb0fa5fb07726c2a64bc837e301a78be76379bc: Very short time between transactions
0xd24ae4aa87e0e13ed661027c44d9600358d34a9d2e1afae4cb95daa3f06ca241: Very short time between transactions
0x28edcaa4a9bbf1d9fee9095809285e2fbbf6e2342d24dd9605386adf5c0873a0: Very short time between transactions
0xad60eb4ac274504d285f527f8502292fbe6ad7ec02b4e45547b4045041eaee85: Very short time between transactions
0x75d200a0f91b6f16317eaa1c4d44a2a7c62d54c899eb4a15a3485dfc35e3435e: Very short time between transactions
0x1498099a8c59f85ae858af561731589d45128c64ff1a0023cb8e028c464096ef: Regular interval transactions between the same wallets, High frequency transactions (less than 1 minute interval)
0x3ec03dd9c8c5e4d78d68c6db13f192c1d6f7a93976bc4c5262599b90ce6462bc: High frequency transactions (less than 1 minute interval)
0x4dcedca7e757fd97743f14e85dc09f3680280f71d6221d9fcaf0f4b3bc484eb4: Regular interval transactions between the same wallets
0x0860e40b4aebb5bffc674ca4bf8aaf11adebf46fba10705c63f413be8e20e5d3: Regular interval transactions between the same wallets, High frequency transactions (less than 1 minute interval)
0x271006e6083b206e2040da0a1ba173803a23af15587078978825fd83701089db: High frequency transactions (less than 1 minute interval)
0xf58cdb9c1fd35a69d5ef50f49cb0fa5fb07726c2a64bc837e301a78be76379bc: Regular interval transactions between the same wallets, High frequency transactions (less than 1 minute interval)
0xd24ae4aa87e0e13ed661027c44d9600358d34a9d2e1afae4cb95daa3f06ca241: Regular interval transactions between the same wallets, High frequency transactions (less than 1 minute interval)
0x28edcaa4a9bbf1d9fee9095809285e2fbbf6e2342d24dd9605386adf5c0873a0: Regular interval transactions between the same wallets, High frequency transactions (less than 1 minute interval)
0xad60eb4ac274504d285f527f8502292fbe6ad7ec02b4e45547b4045041eaee85: Regular interval transactions between the same wallets, High frequency transactions (less than 1 minute interval)
0x75d200a0f91b6f16317eaa1c4d44a2a7c62d54c899eb4a15a3485dfc35e3435e: High frequency transactions (less than 1 minute interval)
Summary
Total Suspicious Transactions
10
Average Risk Score
52.5
Top Tags
No tags
Suspicious Transactions
| Transaction Hash | Risk Score | Risk Factors | Tags |
|---|---|---|---|
0x75d200a…
|
63
High
|
Short time frame between transactions
Transaction amount significantly higher than average
Anomaly detected by Isolation Forest
Transaction amount significantly higher than user average
Large transaction amount
High frequency transactions (less than 1 minute interval)
Low transaction fee
Transaction amount doubled compared to previous transaction
Rapid accumulation of large transactions
Very short time between transactions
|
No tags
|
0x1498099…
|
100
High
|
Transaction amount significantly higher than average
Related to 42 high-risk transactions (highest score: 100)
Anomaly detected by Isolation Forest
Transaction amount significantly higher than user average
Large transaction amount
High frequency transactions (less than 1 minute interval)
Low transaction fee
Transaction involves DeFi exploit address: Bybit Exploiter 49
Very short time between transactions
Receives funds from exploit address: 0x723a70...
|
No tags
|
0x271006e…
|
54
High
|
Short time frame between transactions
Transaction amount significantly higher than average
Anomaly detected by Isolation Forest
Transaction amount significantly higher than user average
Large transaction amount
Low transaction fee
Very short time between transactions
|
No tags
|
0x4dcedca…
|
52
High
|
Short time frame between transactions
Transaction amount significantly higher than average
Anomaly detected by Isolation Forest
Transaction amount significantly higher than user average
Large transaction amount
Very short time between transactions
Related to 2 high-risk transactions (highest score: 92)
|
No tags
|
0x0860e40…
|
30
Medium
|
Short time frame between transactions
Multiple round number transactions
Low transaction fee
Very short time between transactions
Transaction amount significantly lower than average
Related to 19 high-risk transactions (highest score: 89)
Transaction amount halved compared to previous transaction
|
No tags
|
0x3ec03dd…
|
100
High
|
Short time frame between transactions
Transaction amount significantly higher than average
Related to 42 high-risk transactions (highest score: 100)
Anomaly detected by Isolation Forest
Transaction amount significantly higher than user average
Large transaction amount
Low transaction fee
Transaction amount doubled compared to previous transaction
Transaction involves DeFi exploit address: Bybit Exploiter 49
Receives funds from exploit address: 0x723a70...
|
No tags
|
0xf58cdb9…
|
48
High
|
Short time frame between transactions
Anomaly detected by Isolation Forest
Low transaction fee
Transaction amount doubled compared to previous transaction
Part of coordinated wallet cluster
Transaction amount significantly lower than average
|
No tags
|
0xd24ae4a…
|
30
Medium
|
Short time frame between transactions
Multiple round number transactions
Low transaction fee
Very short time between transactions
Transaction amount significantly lower than average
Related to 19 high-risk transactions (highest score: 89)
Transaction amount halved compared to previous transaction
|
No tags
|
0x28edcaa…
|
28
Medium
|
Short time frame between transactions
Multiple round number transactions
High frequency transactions (less than 1 minute interval)
Repetitive transaction amount
Low transaction fee
Very short time between transactions
Transaction amount significantly lower than average
Related to 19 high-risk transactions (highest score: 89)
|
No tags
|
0xad60eb4…
|
36
Medium
|
Short time frame between transactions
Multiple round number transactions
Regular interval transactions between the same wallets
High frequency transactions (less than 1 minute interval)
Repetitive transaction amount
Low transaction fee
Very short time between transactions
Transaction amount significantly lower than average
Related to 19 high-risk transactions (highest score: 89)
|
No tags
|
Showing 1 to 10 of 0 transactions
Advanced Analysis Findings
No Local Outlier Factor analysis data is available for this report.
No wallet community detection data is available for this report.
No transaction layering pattern data is available for this report.
No address clustering data is available for this report.
No sanctioned address connection data is available for this report.
Suspicious Activities
Suspicious Activities Summary:
High Risk Activities: 10
Medium Risk Activities: 0
Total Flagged Transactions: 10
Pattern Categories:
- Network-based anomalies
- Behavioral inconsistencies
- Statistical outliers
- Temporal irregularities
Automated Detection Results:
- Algorithm coverage: Comprehensive
- Detection confidence: High
- Risk classification: Validated
Conclusions & Recommendations
Conclusions
Analysis Conclusions for 0x4b75736fb79269cf995d31595fd01b8e67fd25f2:
1. Risk Assessment
- Overall Risk Level: Very High
- Standardized Risk Score: 100/100
- Average Transaction Risk Score: 54.10
- Total Suspicious Patterns: 10
2. Key Findings
- Automated analysis completed successfully
- Multiple detection algorithms applied
- Comprehensive risk evaluation performed
- Standardized scoring methodology applied (score: 100/100)
3. Confidence Level
- Analysis Quality: High
- Data Coverage: Complete
- Algorithm Performance: Validated
4. Summary
The automated analysis has identified significant concerns.
Immediate action recommended.
Recommendations
Immediate Action Recommendations:
1. Priority Actions
- Escalate to compliance team immediately
- Implement enhanced monitoring
- Consider transaction restrictions
- Document all findings
2. Investigation Requirements
- Detailed transaction review required
- Source of funds investigation
- Enhanced due diligence protocols
- Regular monitoring updates
3. Compliance Measures
- File suspicious activity reports if required
- Implement know-your-customer procedures
- Apply enhanced monitoring protocols
- Document risk mitigation measures
Severity Assessment
Very High
Appendices & References
Appendices
Appendix A: Automated Analysis Results
Appendix B: Algorithm Details and Methodology
Appendix C: Risk Assessment Matrix
Appendix D: Transaction Pattern Analysis
Appendix E: Network Connection Analysis
Appendix F: Case Reference Documentation - CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001
Appendix G: Investigation Team Notes - Cladious Forensics Team
References
1. Blockchain Analysis Framework - Cladious Platform
2. Risk Assessment Guidelines - Financial Action Task Force (FATF)
3. Automated Analysis Documentation - Internal Methodology
Contact Information
Primary Analyst: Cladious Auto
Email: [email protected]
Generated: 2025-07-14 03:32:45 UTC
Investigation Team: Cladious Forensics Team
Case Reference: CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001
Platform: Cladious Security Analysis Platform
For questions or additional analysis requests, please contact the investigation team.
This report contains confidential information and should be handled according to your organization's data protection policies.
Report Information
Author
Cladious Auto
Published Date
July 14, 2025
Views
5
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