Lazarus High Risk Bybit Hacking Investigation [CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001] - Wallet Analysis Report - Very High Risk - 0xcdea...d312
Published
15 Jul 2025
7 views
Wallet Name
Analysis Target Wallet (CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001) - 0xcdea...d312
Overview
Project Scope
Analysis of wallet 0xcdeaf287d8367b401848ca1a5904efae1bead312 - Lazarus High Risk Bybit Hacking Investigation
Suspicious Wallet Hash
0xcdeaf287d8367b401848ca1a5904efae1bead312
This is the primary wallet address being investigated in this report.
Methodology
Research Methodology
Automated Analysis Methodology for Wallet 0xcdeaf287d8367b401848ca1a5904efae1bead312
1. Data Collection
- Automated transaction retrieval from blockchain
- Historical transaction pattern analysis
- Network connection mapping
2. Analysis Algorithms
- Multi-algorithm approach using 15 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 0xcdeaf287d8367b401848ca1a5904efae1bead312
1. Blockchain Data Retrieval
- Retrieved 15 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 0xcdeaf287d8367b401848ca1a5904efae1bead312
Risk Level: Very High Risk Score: 100/100 Total Issues Identified: 59 Suspicious Transactions: 15
Key Findings: - Automated analysis detected 15 suspicious transactions - Risk assessment indicates very high risk level - 59 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.
0x3ac679edded6296be51cb6d867ab7b1925a878e2c0ba85f9e90b140349e467db: Very short time between transactions
0x589618dce2579b48918ea227bb1d444d18317b7a37f777756e56dc11ceb73f95: Very short time between transactions
0xa32096d7d80ec8550963657ca14c68380eb43fa3358e6fff36447e3dac22f405: Very short time between transactions
0x3bee43da8c49839ff6fdad0b2a27c1449aacabfa18f6e30e39ba5ea227b74105: Very short time between transactions
0x9d1e462cf3b25389029a74e5e892f43fddbcddaf61e002b362ad15f5263f79c5: Very short time between transactions
0xae2b3ce783777b434e3eb39829fa0caf38c4562616a3a6c021d6c4d1a85c978c: Very short time between transactions
0xfe6499e332a5e6513e811345e63a50e9e2728090a04b36b561ad22f03e9b0306: Very short time between transactions
0x741560532eabe0c16a0624fe30f32e1a4c6d7b8f5668ddb2eee7f989534e856b: Very short time between transactions
0xc21bc81651f6fc05c79d7235d5f609258a3ea3acc0c06f6cd14ade5f0923a373: Very short time between transactions
0x2f62c7503c7ca051635aba9488aebffa65be8a55bb20b5b044da3df3257078f1: Very short time between transactions
0x1b686fe59505a49c312db5d55d824108bf835548cb047100b57ac4feb826cc3b: Very short time between transactions
0xbd7c6365fc96ab37cb2ef3fe683dc30a33f19ef73647489f3c45d3d77b46da66: Very short time between transactions
0x9c76a85da449b3707be7d2ca2a177e2db1ac6eb928d92a9bfa44db74c7f2a4b1: Very short time between transactions
0x30b2c21f3b694273100f038c89adcf4170b48e9c9a04f39b8e743e5e217bea41: Very short time between transactions
0x3ac679edded6296be51cb6d867ab7b1925a878e2c0ba85f9e90b140349e467db: High frequency transactions (less than 1 minute interval)
0x589618dce2579b48918ea227bb1d444d18317b7a37f777756e56dc11ceb73f95: High frequency transactions (less than 1 minute interval)
0xa32096d7d80ec8550963657ca14c68380eb43fa3358e6fff36447e3dac22f405: High frequency transactions (less than 1 minute interval)
0x3bee43da8c49839ff6fdad0b2a27c1449aacabfa18f6e30e39ba5ea227b74105: High frequency transactions (less than 1 minute interval)
0x9d1e462cf3b25389029a74e5e892f43fddbcddaf61e002b362ad15f5263f79c5: High frequency transactions (less than 1 minute interval)
0xae2b3ce783777b434e3eb39829fa0caf38c4562616a3a6c021d6c4d1a85c978c: High frequency transactions (less than 1 minute interval)
0xfe6499e332a5e6513e811345e63a50e9e2728090a04b36b561ad22f03e9b0306: High frequency transactions (less than 1 minute interval), Regular interval transactions between the same wallets
0x741560532eabe0c16a0624fe30f32e1a4c6d7b8f5668ddb2eee7f989534e856b: High frequency transactions (less than 1 minute interval), Regular interval transactions between the same wallets
0xc21bc81651f6fc05c79d7235d5f609258a3ea3acc0c06f6cd14ade5f0923a373: High frequency transactions (less than 1 minute interval)
0x2f62c7503c7ca051635aba9488aebffa65be8a55bb20b5b044da3df3257078f1: High frequency transactions (less than 1 minute interval)
0x1b686fe59505a49c312db5d55d824108bf835548cb047100b57ac4feb826cc3b: High frequency transactions (less than 1 minute interval)
0xbd7c6365fc96ab37cb2ef3fe683dc30a33f19ef73647489f3c45d3d77b46da66: High frequency transactions (less than 1 minute interval)
0x9c76a85da449b3707be7d2ca2a177e2db1ac6eb928d92a9bfa44db74c7f2a4b1: High frequency transactions (less than 1 minute interval)
0x30b2c21f3b694273100f038c89adcf4170b48e9c9a04f39b8e743e5e217bea41: High frequency transactions (less than 1 minute interval)
Suspicious Transactions
| Transaction Hash | Risk Score | Risk Factors |
|---|---|---|
0x589618d…
|
54
High
|
Short time frame between transactions
Very short time between transactions
Transaction amount significantly higher than user average
Transaction amount significantly higher than average
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
|
0x3bee43d…
|
51
High
|
High frequency transactions (less than 1 minute interval)
Short time frame between transactions
Rapid accumulation of large transactions
Very short time between transactions
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
|
0x9d1e462…
|
54
High
|
High frequency transactions (less than 1 minute interval)
Short time frame between transactions
Rapid multi-hop layering pattern detected
Rapid accumulation of large transactions
Very short time between transactions
Low transaction fee
Large transaction amount
|
0x1b686fe…
|
60
High
|
High frequency transactions (less than 1 minute interval)
Short time frame between transactions
Rapid multi-hop layering pattern detected
Very short time between transactions
Multiple round number transactions
Transaction amount significantly lower than average
Low transaction fee
Part of coordinated wallet cluster
Transaction amount halved compared to previous transaction
|
0x3ac679e…
|
100
High
|
Short time frame between transactions
Receives funds from exploit address: 0x23db72...
Transaction involves DeFi exploit address: Bybit Exploiter 29
Related to 90 high-risk transactions (highest score: 100)
Transaction amount significantly higher than user average
Transaction amount significantly higher than average
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
Transaction amount doubled compared to previous transaction
|
0xa984a46…
|
50
High
|
High frequency transactions (less than 1 minute interval)
Related to high-risk transaction ['0x95bf1db34834b5f8b3ddbad6ee21f46a6c1f35b387255e5561aff45d4484ce04'] (score: 100)
Very short time between transactions
Transaction amount significantly higher than user average
Transaction amount significantly higher than average
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
|
0xa32096d…
|
56
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
Part of coordinated wallet cluster
Transaction amount halved compared to previous transaction
|
0xbd7c636…
|
42
High
|
Repetitive transaction amount
Short time frame between transactions
High frequency transactions (less than 1 minute interval)
Very short time between transactions
Multiple round number transactions
Transaction amount significantly lower than average
Low transaction fee
Part of coordinated wallet cluster
|
0xfe6499e…
|
51
High
|
High frequency transactions (less than 1 minute interval)
Short time frame between transactions
Rapid accumulation of large transactions
Very short time between transactions
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
|
0x7415605…
|
67
High
|
High frequency transactions (less than 1 minute interval)
Short time frame between transactions
Rapid multi-hop layering pattern detected
Rapid accumulation of large transactions
Very short time between transactions
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
|
0x2f62c75…
|
69
High
|
High frequency transactions (less than 1 minute interval)
Short time frame between transactions
Rapid multi-hop layering pattern detected
Rapid accumulation of large transactions
Very short time between transactions
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
Transaction amount doubled compared to previous transaction
|
0xc21bc81…
|
60
High
|
High frequency transactions (less than 1 minute interval)
Short time frame between transactions
Rapid multi-hop layering pattern detected
Very short time between transactions
Multiple round number transactions
Transaction amount significantly lower than average
Low transaction fee
Part of coordinated wallet cluster
Transaction amount halved compared to previous transaction
|
0x9c76a85…
|
50
High
|
Short time frame between transactions
Rapid multi-hop layering pattern detected
Transaction amount significantly lower than average
Low transaction fee
Transaction amount doubled compared to previous transaction
Part of coordinated wallet cluster
|
0x30b2c21…
|
57
High
|
Repetitive transaction amount
Short time frame between transactions
High frequency transactions (less than 1 minute interval)
Rapid multi-hop layering pattern detected
Very short time between transactions
Transaction amount significantly lower than average
Low transaction fee
Part of coordinated wallet cluster
|
0xae2b3ce…
|
51
High
|
High frequency transactions (less than 1 minute interval)
Short time frame between transactions
Rapid multi-hop layering pattern detected
Very short time between transactions
Transaction amount significantly lower than average
Low transaction fee
Regular interval transactions between the same wallets
|
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: 15
Medium Risk Activities: 0
Total Flagged Transactions: 15
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 0xcdeaf287d8367b401848ca1a5904efae1bead312:
1. Risk Assessment
- Overall Risk Level: Very High
- Standardized Risk Score: 100/100
- Average Transaction Risk Score: 58.13
- Total Suspicious Patterns: 15
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 19:49:23 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
7
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