Lazarus High Risk Bybit Hacking Investigation [CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001] - Wallet Analysis Report - Very High Risk - 0x8eb7...18de
Published
14 Jul 2025
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Wallet Name
Analysis Target Wallet (CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001) - 0x8eb7...18de
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Overview
Project Scope
Analysis of wallet 0x8eb74d3647128bd83cf5670d89184c97326d18de - Lazarus High Risk Bybit Hacking Investigation
Suspicious Wallet Hash
0x8eb74d3647128bd83cf5670d89184c97326d18de
This is the primary wallet address being investigated in this report.
Methodology
Research Methodology
Automated Analysis Methodology for Wallet 0x8eb74d3647128bd83cf5670d89184c97326d18de
1. Data Collection
- Automated transaction retrieval from blockchain
- Historical transaction pattern analysis
- Network connection mapping
2. Analysis Algorithms
- Multi-algorithm approach using 11 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 0x8eb74d3647128bd83cf5670d89184c97326d18de
1. Blockchain Data Retrieval
- Retrieved 11 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 0x8eb74d3647128bd83cf5670d89184c97326d18de
Risk Level: Very High Risk Score: 100/100 Total Issues Identified: 43 Suspicious Transactions: 11
Key Findings: - Automated analysis detected 11 suspicious transactions - Risk assessment indicates very high risk level - 43 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.
0x01ce811aa45d6aa6be682b03c327613a86788905a8a4b2bda3bba9195bd8cc16: Very short time between transactions
0x65ab03417f542208c43598960e5ab17c7ef7a1563eb09d0917485f2ccbb2ba99: Very short time between transactions
0x1233360143dd745ceeb0340e5954d3494a473d97f8b3a83795097df2e90656f5: Very short time between transactions
0x9383cb34c923d45b0769283c6de0d960f8603faafdf1a489e849a6425bf91b14: Very short time between transactions
0x5a71193ea22d040b41a52cd6fd92b62ed618631b102f5fc1a93891984a2b80d0: Very short time between transactions
0x142dbceb57a775de1b5a817fd52ea239a229ffd164b5f21d91d3c6a078864437: Very short time between transactions
0x08ce20c9ad1ffe4547cfec01eb19daf92e81142ae58ce15f2e82f8bc8cc0a133: Very short time between transactions
0x5ce40ea804cf4bd8753464ce860df2bc2193aa86d08a65851bdb6a35dc7c98ec: Very short time between transactions
0x40d0643e179b39ff7b434b2c5e0fa52b23c25b4228536cb11da51e7a93939cfc: Very short time between transactions
0x10c2a5c1a40028cd848af382b7aae30db48d411253a3e54ab3a35755015aa1c2: Very short time between transactions
0x289118b8ea60d646e9514d966d75a99ffcdcef9393a2cd6dc6d1d7e5380f2f6d: Transaction amount significantly higher than average, Transaction amount doubled compared to previous transaction
0x01ce811aa45d6aa6be682b03c327613a86788905a8a4b2bda3bba9195bd8cc16: High frequency transactions (less than 1 minute interval)
0x65ab03417f542208c43598960e5ab17c7ef7a1563eb09d0917485f2ccbb2ba99: High frequency transactions (less than 1 minute interval)
0x1233360143dd745ceeb0340e5954d3494a473d97f8b3a83795097df2e90656f5: High frequency transactions (less than 1 minute interval)
0x9383cb34c923d45b0769283c6de0d960f8603faafdf1a489e849a6425bf91b14: High frequency transactions (less than 1 minute interval)
0x5a71193ea22d040b41a52cd6fd92b62ed618631b102f5fc1a93891984a2b80d0: High frequency transactions (less than 1 minute interval)
0x142dbceb57a775de1b5a817fd52ea239a229ffd164b5f21d91d3c6a078864437: High frequency transactions (less than 1 minute interval)
0x08ce20c9ad1ffe4547cfec01eb19daf92e81142ae58ce15f2e82f8bc8cc0a133: High frequency transactions (less than 1 minute interval)
0x5ce40ea804cf4bd8753464ce860df2bc2193aa86d08a65851bdb6a35dc7c98ec: High frequency transactions (less than 1 minute interval)
0x40d0643e179b39ff7b434b2c5e0fa52b23c25b4228536cb11da51e7a93939cfc: High frequency transactions (less than 1 minute interval)
0x10c2a5c1a40028cd848af382b7aae30db48d411253a3e54ab3a35755015aa1c2: High frequency transactions (less than 1 minute interval)
Summary
Total Suspicious Transactions
11
Average Risk Score
43.0
Top Tags
No tags
Suspicious Transactions
| Transaction Hash | Risk Score | Risk Factors | Tags |
|---|---|---|---|
0x65ab034…
|
36
Medium
|
Short time frame between transactions
High frequency transactions (less than 1 minute interval)
Low transaction fee
Part of coordinated wallet cluster
Transaction amount significantly lower than average
Transaction amount halved compared to previous transaction
|
No tags
|
0x08ce20c…
|
34
Medium
|
Short time frame between transactions
Fan-in structuring detected: 4 similar amounts from different addresses totaling 0.00
Low transaction fee
Part of coordinated wallet cluster
Transaction amount significantly lower than average
Transaction amount halved compared to previous transaction
|
No tags
|
0x142dbce…
|
53
High
|
Short time frame between transactions
Anomaly detected by Isolation Forest
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
|
0x9383cb3…
|
33
Medium
|
Short time frame between transactions
Large transaction amount
High frequency transactions (less than 1 minute interval)
Low transaction fee
Transaction amount doubled compared to previous transaction
Very short time between transactions
|
No tags
|
0x5a71193…
|
36
Medium
|
Short time frame between transactions
High frequency transactions (less than 1 minute interval)
Low transaction fee
Part of coordinated wallet cluster
Transaction amount significantly lower than average
Transaction amount halved compared to previous transaction
|
No tags
|
0x1233360…
|
44
High
|
Short time frame between transactions
Regular interval transactions between the same wallets
High frequency transactions (less than 1 minute interval)
Low transaction fee
Part of coordinated wallet cluster
Transaction amount significantly lower than average
Transaction amount halved compared to previous transaction
|
No tags
|
0x5ce40ea…
|
39
Medium
|
Short time frame between transactions
Fan-in structuring detected: 3 similar amounts from different addresses totaling 0.00
Fan-in structuring detected: 4 similar amounts from different addresses totaling 0.00
Regular interval transactions between the same wallets
Repetitive transaction amount
Low transaction fee
Part of coordinated wallet cluster
Transaction amount significantly lower than average
|
No tags
|
0x10c2a5c…
|
32
Medium
|
Short time frame between transactions
Fan-in structuring detected: 3 similar amounts from different addresses totaling 0.00
Fan-in structuring detected: 4 similar amounts from different addresses totaling 0.00
Repetitive transaction amount
Low transaction fee
Part of coordinated wallet cluster
Transaction amount significantly lower than average
|
No tags
|
0x01ce811…
|
44
High
|
Short time frame between transactions
Anomaly detected by Isolation Forest
Large transaction amount
High frequency transactions (less than 1 minute interval)
Low transaction fee
Rapid accumulation of large transactions
|
No tags
|
0x40d0643…
|
32
Medium
|
Short time frame between transactions
Fan-in structuring detected: 3 similar amounts from different addresses totaling 0.00
Fan-in structuring detected: 4 similar amounts from different addresses totaling 0.00
Repetitive transaction amount
Low transaction fee
Part of coordinated wallet cluster
Transaction amount significantly lower than average
|
No tags
|
0x289118b…
|
100
High
|
Transaction amount significantly higher than average
Transaction involves DeFi exploit address: Bybit Exploiter 26
Anomaly detected by Isolation Forest
Transaction amount significantly higher than user average
Large transaction amount
High frequency transactions (less than 1 minute interval)
Receives funds from exploit address: 0x83c767...
Low transaction fee
Related to 104 high-risk transactions (highest score: 100)
Very short time between transactions
|
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: 11
Medium Risk Activities: 0
Total Flagged Transactions: 11
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 0x8eb74d3647128bd83cf5670d89184c97326d18de:
1. Risk Assessment
- Overall Risk Level: Very High
- Standardized Risk Score: 100/100
- Average Transaction Risk Score: 43.91
- Total Suspicious Patterns: 11
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 10:01:56 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
11
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