Lazarus High Risk Bybit Hacking Investigation [CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001] - Wallet Analysis Report - Very High Risk - 0xb9fa...d3dd
Published
15 Jul 2025
5 views
Wallet Name
Analysis Target Wallet (CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001) - 0xb9fa...d3dd
LLM Analysis
Overview
Project Scope
Analysis of wallet 0xb9fa328264e0a193890aad438888438fe143d3dd - Lazarus High Risk Bybit Hacking Investigation
Suspicious Wallet Hash
0xb9fa328264e0a193890aad438888438fe143d3dd
This is the primary wallet address being investigated in this report.
Methodology
Research Methodology
Automated Analysis Methodology for Wallet 0xb9fa328264e0a193890aad438888438fe143d3dd
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 0xb9fa328264e0a193890aad438888438fe143d3dd
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 0xb9fa328264e0a193890aad438888438fe143d3dd
Risk Level: Very High Risk Score: 100/100 Total Issues Identified: 47 Suspicious Transactions: 12
Key Findings: - Automated analysis detected 12 suspicious transactions - Risk assessment indicates very high risk level - 47 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.
0x8df310e0f3d22633ee922b0caa602e272da0a9123324db05158f4c6b037b02da: Very short time between transactions
0xe343e2e274d5a04f2ed29a0ffd69a110dece38e50e2e50fcc0767b19e0386a45: Transaction amount significantly higher than user average, Very short time between transactions
0x59e898d70610706d8f41762aa3e483a37d96ddc295ce70806e3dfa01307ccd05: Very short time between transactions
0x4aa9f2b12ed5e42f9feef17261e34596df3eb3dd847903bed6425c04172e952c: Very short time between transactions
0x4d84ea8c778c6145ec801e1e0d4c887068d316e4cfbc1c92690751e7e9ec2235: Very short time between transactions
0x139d143a210393ad5c530e3d3e46f54d07a86bd4ecf2a9feb9bfc4f85622ddf8: Very short time between transactions
0x734c0df0b21a589e29e76a2cfcde31ba5ed1fb8d7ebaa796c8d00c3f1eb99001: Very short time between transactions
0x00102f21ce194b2fc619314a3e9fcab6acd6a4ba31a0458d98acf68458888051: Transaction amount significantly higher than user average, Very short time between transactions
0x26103f6260fad89f526b1899e593f6fecf7b20cdacd9c5beb7326455d1c50d91: Very short time between transactions
0x368e743df86091b7f4a55c63c03f1c9040da8bdd7a6cf8c090303025b27af71c: Very short time between transactions
0xda5c79ab71221d9aa516c8966997a56189eadc48d0f924d9ce9a2fcf3c86810c: Very short time between transactions
0x8df310e0f3d22633ee922b0caa602e272da0a9123324db05158f4c6b037b02da: Transaction amount doubled compared to previous transaction
0xe343e2e274d5a04f2ed29a0ffd69a110dece38e50e2e50fcc0767b19e0386a45: Transaction amount doubled compared to previous transaction, Transaction amount significantly higher than average
0x59e898d70610706d8f41762aa3e483a37d96ddc295ce70806e3dfa01307ccd05: Transaction amount significantly lower than average
0x4aa9f2b12ed5e42f9feef17261e34596df3eb3dd847903bed6425c04172e952c: Transaction amount halved compared to previous transaction
0x139d143a210393ad5c530e3d3e46f54d07a86bd4ecf2a9feb9bfc4f85622ddf8: Transaction amount significantly lower than average, Transaction amount halved compared to previous transaction
0x734c0df0b21a589e29e76a2cfcde31ba5ed1fb8d7ebaa796c8d00c3f1eb99001: Transaction amount significantly lower than average
0x00102f21ce194b2fc619314a3e9fcab6acd6a4ba31a0458d98acf68458888051: Transaction amount doubled compared to previous transaction, Transaction amount significantly higher than average
0x26103f6260fad89f526b1899e593f6fecf7b20cdacd9c5beb7326455d1c50d91: Transaction amount significantly lower than average, Transaction amount halved compared to previous transaction
0x368e743df86091b7f4a55c63c03f1c9040da8bdd7a6cf8c090303025b27af71c: Transaction amount significantly lower than average, Transaction amount halved compared to previous transaction
0xda5c79ab71221d9aa516c8966997a56189eadc48d0f924d9ce9a2fcf3c86810c: Transaction amount significantly lower than average
0x8df310e0f3d22633ee922b0caa602e272da0a9123324db05158f4c6b037b02da: High frequency transactions (less than 1 minute interval)
0xe343e2e274d5a04f2ed29a0ffd69a110dece38e50e2e50fcc0767b19e0386a45: High frequency transactions (less than 1 minute interval)
0x59e898d70610706d8f41762aa3e483a37d96ddc295ce70806e3dfa01307ccd05: High frequency transactions (less than 1 minute interval)
0x4aa9f2b12ed5e42f9feef17261e34596df3eb3dd847903bed6425c04172e952c: High frequency transactions (less than 1 minute interval)
0x4d84ea8c778c6145ec801e1e0d4c887068d316e4cfbc1c92690751e7e9ec2235: High frequency transactions (less than 1 minute interval)
0x139d143a210393ad5c530e3d3e46f54d07a86bd4ecf2a9feb9bfc4f85622ddf8: High frequency transactions (less than 1 minute interval)
0x734c0df0b21a589e29e76a2cfcde31ba5ed1fb8d7ebaa796c8d00c3f1eb99001: High frequency transactions (less than 1 minute interval)
0x00102f21ce194b2fc619314a3e9fcab6acd6a4ba31a0458d98acf68458888051: High frequency transactions (less than 1 minute interval)
0x26103f6260fad89f526b1899e593f6fecf7b20cdacd9c5beb7326455d1c50d91: High frequency transactions (less than 1 minute interval)
0x368e743df86091b7f4a55c63c03f1c9040da8bdd7a6cf8c090303025b27af71c: High frequency transactions (less than 1 minute interval)
0xda5c79ab71221d9aa516c8966997a56189eadc48d0f924d9ce9a2fcf3c86810c: High frequency transactions (less than 1 minute interval)
Suspicious Transactions
| Transaction Hash | Risk Score | Risk Factors | Tags |
|---|---|---|---|
0xb96a6db…
|
29
Medium
|
Short time frame between transactions
Very short time between transactions
Related to 2 high-risk transactions (highest score: 85)
Transaction amount significantly lower than average
Low transaction fee
Transaction amount halved compared to previous transaction
|
No tags
|
0x4d84ea8…
|
40
High
|
Related to high-risk transaction ['0x4fa44f74857dd7534938e8e30cdfa62fef5167cb12b5c9f372e2c7ad401d6f1d'] (score: 77)
Transaction amount significantly higher than average
Transaction amount significantly higher than user average
Local Outlier Factor (LOF) detected as anomaly
Anomaly detected by Isolation Forest
Transaction amount doubled compared to previous transaction
|
No tags
|
0x139d143…
|
0
Low
|
Transaction involves trusted address (Exchange/DeFi Protocol)
|
No tags
|
0x734c0df…
|
0
Low
|
Transaction involves trusted address (Exchange/DeFi Protocol)
|
No tags
|
0x00102f2…
|
100
High
|
Transaction amount significantly lower than average
Transaction amount halved compared to previous transaction
Related to 239 high-risk transactions (highest score: 100)
Sends funds to exploit address: 0x47666f...
Transaction involves DeFi exploit address: Bybit Exploiter 1
|
No tags
|
0x26103f6…
|
0
Low
|
Transaction involves trusted address (Exchange/DeFi Protocol)
|
No tags
|
0x368e743…
|
0
Low
|
Transaction involves trusted address (Exchange/DeFi Protocol)
|
No tags
|
0xda5c79a…
|
0
Low
|
Transaction involves trusted address (Exchange/DeFi Protocol)
|
No tags
|
0x59e898d…
|
0
Low
|
Transaction involves trusted address (Exchange/DeFi Protocol)
|
No tags
|
0x4aa9f2b…
|
35
Medium
|
Repetitive transaction amount
High frequency transactions (less than 1 minute interval)
Very short time between transactions
Related to 2 high-risk transactions (highest score: 90)
Multiple round number transactions
Transaction amount significantly lower than average
Short time frame between transactions
Local Outlier Factor (LOF) detected as anomaly
|
No tags
|
0x8df310e…
|
48
High
|
High frequency transactions (less than 1 minute interval)
Very short time between transactions
Transaction amount significantly higher than average
Transaction amount significantly higher than user average
Local Outlier Factor (LOF) detected as anomaly
Anomaly detected by Isolation Forest
|
No tags
|
0xe343e2e…
|
85
High
|
Related to 8 high-risk transactions (highest score: 88)
Round amount consistent with mixer
Very short time between transactions
Transaction amount significantly higher than average
Transaction amount significantly higher than user average
Local Outlier Factor (LOF) detected as anomaly
Anomaly detected by Isolation Forest
|
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: 6
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 0xb9fa328264e0a193890aad438888438fe143d3dd:
1. Risk Assessment
- Overall Risk Level: Very High
- Standardized Risk Score: 100/100
- Average Transaction Risk Score: 28.08
- 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 17:04:42 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
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