Lazarus High Risk Bybit Hacking Investigation [CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001] - Wallet Analysis Report - Very High Risk - 0xd0f1...09d3
Published
15 Jul 2025
8 views
Wallet Name
Analysis Target Wallet (CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001) - 0xd0f1...09d3
Overview
Project Scope
Analysis of wallet 0xd0f19c5f83a9bdd4eaffbdcc95371f32413109d3 - Lazarus High Risk Bybit Hacking Investigation
Suspicious Wallet Hash
0xd0f19c5f83a9bdd4eaffbdcc95371f32413109d3
This is the primary wallet address being investigated in this report.
Methodology
Research Methodology
Automated Analysis Methodology for Wallet 0xd0f19c5f83a9bdd4eaffbdcc95371f32413109d3
1. Data Collection
- Automated transaction retrieval from blockchain
- Historical transaction pattern analysis
- Network connection mapping
2. Analysis Algorithms
- Multi-algorithm approach using 12 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 0xd0f19c5f83a9bdd4eaffbdcc95371f32413109d3
1. Blockchain Data Retrieval
- Retrieved 12 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 0xd0f19c5f83a9bdd4eaffbdcc95371f32413109d3
Risk Level: Very High Risk Score: 100/100 Total Issues Identified: 46 Suspicious Transactions: 12
Key Findings: - Automated analysis detected 12 suspicious transactions - Risk assessment indicates very high risk level - 46 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.
0xe56fac359b94125aa70bb80b33629d4b5a019024688269f432e7e60ab93aa434: Very short time between transactions
0x4b262ee5a3afbaeb484b42b1f73ae6cb205e618791396becf23e9be49278c83e: Very short time between transactions
0xd0383de8b34693fb2580f6523ce2f252c28dec61742dfa7b154ec44739de1960: Very short time between transactions
0xcbe4777cab6ff4fc95f79d6e14f3b43b0a696c5c7e0213faaa6634897e85c02f: Very short time between transactions
0xbf931a08721928b72ff5d7ccd7314e5dd5278a5604631cd7bd2977a44f09509a: Very short time between transactions
0x32924543a6dfe2de84b3f68265cfe04f3dbd16f6a0a21065da9110b71eecd09a: Very short time between transactions
0x193e0750e5d43129d4a5c103cb390c1b3586265cd4e627922fedfbabe4f18947: Very short time between transactions
0x4714daaebf23a9e0b142cac7e216442ce734763aafb14450e7a20ad454ac1bcd: Very short time between transactions
0xaa8b6fda8f3a1266e504ca772d0455f12b9336ec2ada6961b6256b6f95a9e777: Very short time between transactions
0x70d048308cd34d5ce3b3ad018e8de3867f250bb2a9f1d470ba218b50b586cfeb: Very short time between transactions
0x0d9da9ad2e4c85c2d64f4af32db972e227c989ca31b9e82628faa53f4240c6f4: Very short time between transactions
0x69b9892c9a2133566c1f9999b1fd79c4f6b03adc9c84f6005034b1faeccca6a4: Transaction amount doubled compared to previous transaction, Transaction amount significantly higher than average
0xcbe4777cab6ff4fc95f79d6e14f3b43b0a696c5c7e0213faaa6634897e85c02f: Transaction amount halved compared to previous transaction
0xe56fac359b94125aa70bb80b33629d4b5a019024688269f432e7e60ab93aa434: High frequency transactions (less than 1 minute interval), Regular interval transactions between the same wallets
0x4b262ee5a3afbaeb484b42b1f73ae6cb205e618791396becf23e9be49278c83e: High frequency transactions (less than 1 minute interval)
0xd0383de8b34693fb2580f6523ce2f252c28dec61742dfa7b154ec44739de1960: High frequency transactions (less than 1 minute interval)
0xbf931a08721928b72ff5d7ccd7314e5dd5278a5604631cd7bd2977a44f09509a: High frequency transactions (less than 1 minute interval)
0x32924543a6dfe2de84b3f68265cfe04f3dbd16f6a0a21065da9110b71eecd09a: High frequency transactions (less than 1 minute interval)
0x193e0750e5d43129d4a5c103cb390c1b3586265cd4e627922fedfbabe4f18947: High frequency transactions (less than 1 minute interval)
0x4714daaebf23a9e0b142cac7e216442ce734763aafb14450e7a20ad454ac1bcd: High frequency transactions (less than 1 minute interval)
0xaa8b6fda8f3a1266e504ca772d0455f12b9336ec2ada6961b6256b6f95a9e777: High frequency transactions (less than 1 minute interval)
0x70d048308cd34d5ce3b3ad018e8de3867f250bb2a9f1d470ba218b50b586cfeb: High frequency transactions (less than 1 minute interval)
0x0d9da9ad2e4c85c2d64f4af32db972e227c989ca31b9e82628faa53f4240c6f4: High frequency transactions (less than 1 minute interval)
Suspicious Transactions
| Transaction Hash | Risk Score | Risk Factors |
|---|---|---|
0xaa8b6fd…
|
43
High
|
Short time frame between transactions
Very short time between transactions
Transaction amount significantly lower than average
Low transaction fee
Part of coordinated wallet cluster
Transaction amount halved compared to previous transaction
|
0xe56fac3…
|
37
Medium
|
Repetitive transaction amount
Short time frame between transactions
Rapid accumulation of large transactions
Very short time between transactions
Low transaction fee
Large transaction amount
|
0xcbe4777…
|
43
High
|
Short time frame between transactions
Very short time between transactions
Transaction amount significantly lower than average
Low transaction fee
Part of coordinated wallet cluster
Transaction amount halved compared to previous transaction
|
0x70d0483…
|
40
High
|
Repetitive transaction amount
Short time frame between transactions
Very short time between transactions
Transaction amount significantly lower than average
Low transaction fee
Part of coordinated wallet cluster
|
0x0d9da9a…
|
42
High
|
Short time frame between transactions
Very short time between transactions
Transaction amount significantly lower than average
Low transaction fee
Anomaly detected by Isolation Forest
Transaction amount doubled compared to previous transaction
Related to high-risk transaction ['0xea9a9516129df056672715daff74fc1e5cb11cf8042b21de11db4d731cd2dc51'] (score: 100)
|
0x69b9892…
|
100
High
|
Short time frame between transactions
Rapid accumulation of large transactions
Very short time between transactions
Transaction amount significantly higher than user average
Transaction amount significantly higher than average
Low transaction fee
Transaction involves DeFi exploit address: Bybit Exploiter 27
Anomaly detected by Isolation Forest
Large transaction amount
Receives funds from exploit address: 0x52207e...
Transaction amount doubled compared to previous transaction
Related to 95 high-risk transactions (highest score: 100)
|
0x193e075…
|
30
Medium
|
High frequency transactions (less than 1 minute interval)
Short time frame between transactions
Very short time between transactions
Transaction amount significantly lower than average
Low transaction fee
Transaction amount halved compared to previous transaction
|
0x4b262ee…
|
39
Medium
|
High frequency transactions (less than 1 minute interval)
Related to 4 high-risk transactions (highest score: 100)
Very short time between transactions
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
|
0xd0383de…
|
48
High
|
Short time frame between transactions
Related to 4 high-risk transactions (highest score: 100)
Very short time between transactions
Transaction amount significantly higher than average
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
|
0x3292454…
|
41
High
|
High frequency transactions (less than 1 minute interval)
Short time frame between transactions
Rapid accumulation of large transactions
Related to 4 high-risk transactions (highest score: 100)
Very short time between transactions
Low transaction fee
Large transaction amount
Transaction amount halved compared to previous transaction
|
0x4714daa…
|
39
Medium
|
Short time frame between transactions
Rapid accumulation of large transactions
Very short time between transactions
Low transaction fee
Large transaction amount
Transaction amount doubled compared to previous transaction
|
0xbf931a0…
|
40
High
|
Repetitive transaction amount
Short time frame between transactions
Very short time between transactions
Transaction amount significantly lower than average
Low transaction fee
Part of coordinated wallet cluster
|
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: 12
Medium Risk Activities: 0
Total Flagged Transactions: 12
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 0xd0f19c5f83a9bdd4eaffbdcc95371f32413109d3:
1. Risk Assessment
- Overall Risk Level: Very High
- Standardized Risk Score: 100/100
- Average Transaction Risk Score: 45.17
- Total Suspicious Patterns: 12
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: 2025-07-15 20:15:04 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 15, 2025
Views
8
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