Lazarus High Risk Bybit Hacking Investigation [CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001] - Wallet Analysis Report - Very High Risk - 0x0ea0...de38
Published
13 Jul 2025
8 views
Wallet Name
Analysis Target Wallet (CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001) - 0x0ea0...de38
Overview
Project Scope
Analysis of wallet 0x0ea023e71f0e13d275b0b886d87aff2f7516de38 - Lazarus High Risk Bybit Hacking Investigation
Suspicious Wallet Hash
0x0ea023e71f0e13d275b0b886d87aff2f7516de38
This is the primary wallet address being investigated in this report.
Methodology
Research Methodology
Automated Analysis Methodology for Wallet 0x0ea023e71f0e13d275b0b886d87aff2f7516de38
1. Data Collection
- Automated transaction retrieval from blockchain
- Historical transaction pattern analysis
- Network connection mapping
2. Analysis Algorithms
- Multi-algorithm approach using 14 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 0x0ea023e71f0e13d275b0b886d87aff2f7516de38
1. Blockchain Data Retrieval
- Retrieved 14 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 0x0ea023e71f0e13d275b0b886d87aff2f7516de38
Risk Level: Very High Risk Score: 100/100 Total Issues Identified: 55 Suspicious Transactions: 14
Key Findings: - Automated analysis detected 14 suspicious transactions - Risk assessment indicates very high risk level - 55 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.
0x15cd32b8c3b82f3325d2d019fba9242b511666420603da31c8879e8804120261: Very short time between transactions
0xe5e488f36f15c28a2dcb05ca41afdf970ba9d5f6f60021680f40ab62c0be2b04: Very short time between transactions
0x90f97eb53478d3a5d5ec957c158a8cade0d9c5ec756139d1692aee7d959c5ad9: Very short time between transactions
0x921d532a1bf99b9530efc9da1051da401d686dd9fbc225f69fcd11d79db2c71b: Very short time between transactions
0xe52d655e30bcadeba87955c4ab55937f4b956ac29e98944eab2720d014505e94: Very short time between transactions
0x01840af5219437f974d3f7b3c83b1fc6d7f91e6e0a5906a213b056c8c18b5218: Very short time between transactions
0x5c82aca13bd458928628c99173c8ebbb30c36e19b3844edbfba482b25eaf2368: Very short time between transactions
0x5b881fdc0e97dc80a7499936b95fd450b828c96a88a49215cd004c8907332e5e: Very short time between transactions
0x68be9ef6ca2b9fff3acc988a0a83247f0b22579257985a461712f82b88c77d3f: Very short time between transactions
0xee1a162c32426ac2415a5174e617ff0c9bf36ae7c2fe2028ab3ff3871a13c9fb: Very short time between transactions
0x118b1ccf5e56fb3c2ec27003ad2266226d2602c17e3489bf47aa2e30121f2cfc: Very short time between transactions
0xaa5b18f56520dd2dd27354c5a5da94830edfd5accb8475820f8b69371f751fc1: Very short time between transactions
0xd8afd58dc6d9103f751051241addf74df333369673d81e803e6b6b32d551ddc0: Very short time between transactions
0xe52d655e30bcadeba87955c4ab55937f4b956ac29e98944eab2720d014505e94: Transaction amount halved compared to previous transaction
0xd8afd58dc6d9103f751051241addf74df333369673d81e803e6b6b32d551ddc0: Transaction amount significantly lower than average
0x15cd32b8c3b82f3325d2d019fba9242b511666420603da31c8879e8804120261: High frequency transactions (less than 1 minute interval)
0xe5e488f36f15c28a2dcb05ca41afdf970ba9d5f6f60021680f40ab62c0be2b04: High frequency transactions (less than 1 minute interval)
0x90f97eb53478d3a5d5ec957c158a8cade0d9c5ec756139d1692aee7d959c5ad9: High frequency transactions (less than 1 minute interval)
0x921d532a1bf99b9530efc9da1051da401d686dd9fbc225f69fcd11d79db2c71b: High frequency transactions (less than 1 minute interval)
0xe52d655e30bcadeba87955c4ab55937f4b956ac29e98944eab2720d014505e94: High frequency transactions (less than 1 minute interval)
0x01840af5219437f974d3f7b3c83b1fc6d7f91e6e0a5906a213b056c8c18b5218: High frequency transactions (less than 1 minute interval)
0x5c82aca13bd458928628c99173c8ebbb30c36e19b3844edbfba482b25eaf2368: High frequency transactions (less than 1 minute interval)
0x5b881fdc0e97dc80a7499936b95fd450b828c96a88a49215cd004c8907332e5e: High frequency transactions (less than 1 minute interval)
0x68be9ef6ca2b9fff3acc988a0a83247f0b22579257985a461712f82b88c77d3f: High frequency transactions (less than 1 minute interval)
0xee1a162c32426ac2415a5174e617ff0c9bf36ae7c2fe2028ab3ff3871a13c9fb: High frequency transactions (less than 1 minute interval)
0x118b1ccf5e56fb3c2ec27003ad2266226d2602c17e3489bf47aa2e30121f2cfc: High frequency transactions (less than 1 minute interval)
0xaa5b18f56520dd2dd27354c5a5da94830edfd5accb8475820f8b69371f751fc1: Regular interval transactions between the same wallets, High frequency transactions (less than 1 minute interval)
0xd8afd58dc6d9103f751051241addf74df333369673d81e803e6b6b32d551ddc0: High frequency transactions (less than 1 minute interval)
Suspicious Transactions
| Transaction Hash | Risk Score | Risk Factors |
|---|---|---|
0x66ccf77…
|
47
High
|
Short time frame between transactions
Transaction amount significantly higher than average
Anomaly detected by Isolation Forest
Large transaction amount
Related to 2 high-risk transactions (highest score: 93)
High frequency transactions (less than 1 minute interval)
Very short time between transactions
|
0x90f97eb…
|
63
High
|
Short time frame between transactions
Transaction amount significantly higher than average
Anomaly detected by Isolation Forest
Large transaction amount
Related to 2 high-risk transactions (highest score: 93)
Rapid multi-hop layering pattern detected
Very short time between transactions
|
0xe52d655…
|
31
Medium
|
Short time frame between transactions
Multiple round number transactions
Related to 17 high-risk transactions (highest score: 83)
High frequency transactions (less than 1 minute interval)
Low transaction fee
Very short time between transactions
Transaction amount significantly lower than average
Transaction amount halved compared to previous transaction
|
0x01840af…
|
31
Medium
|
Short time frame between transactions
Multiple round number transactions
Related to 17 high-risk transactions (highest score: 83)
High frequency transactions (less than 1 minute interval)
Low transaction fee
Very short time between transactions
Transaction amount significantly lower than average
Transaction amount halved compared to previous transaction
|
0x5c82aca…
|
43
High
|
Short time frame between transactions
Multiple round number transactions
Related to 3 high-risk transactions (highest score: 78)
High frequency transactions (less than 1 minute interval)
Rapid multi-hop layering pattern detected
Repetitive transaction amount
Very short time between transactions
Transaction amount significantly lower than average
|
0x5b881fd…
|
76
High
|
Short time frame between transactions
Anomaly detected by Isolation Forest
Regular interval transactions between the same wallets
High frequency transactions (less than 1 minute interval)
Rapid multi-hop layering pattern detected
Low transaction fee
Part of coordinated wallet cluster
Very short time between transactions
Transaction amount significantly lower than average
Related to high-risk transaction ['0xd3eb7a944d506dd9bd0625d817ec20924afd715103d37658c4385cb9a50c4229'] (score: 76)
|
0x68be9ef…
|
57
High
|
Short time frame between transactions
Transaction amount significantly higher than average
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
|
0xee1a162…
|
29
Medium
|
Short time frame between transactions
Low transaction fee
Outgoing structuring detected: 3 similar amounts totaling 0.00
Very short time between transactions
Transaction amount significantly lower than average
Transaction amount halved compared to previous transaction
|
0xd8afd58…
|
26
Medium
|
Short time frame between transactions
Repetitive transaction amount
Low transaction fee
Outgoing structuring detected: 3 similar amounts totaling 0.00
Very short time between transactions
Transaction amount significantly lower than average
|
0x15cd32b…
|
100
High
|
Transaction amount significantly higher than average
Related to 3 high-risk transactions (highest score: 100)
Anomaly detected by Isolation Forest
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...
|
0xe5e488f…
|
100
High
|
Short time frame between transactions
Transaction amount significantly higher than average
Related to 3 high-risk transactions (highest score: 100)
Anomaly detected by Isolation Forest
Large transaction amount
Low transaction fee
Transaction involves DeFi exploit address: Bybit Exploiter 49
Very short time between transactions
Receives funds from exploit address: 0x723a70...
|
0x118b1cc…
|
57
High
|
Short time frame between transactions
Transaction amount significantly higher than average
Anomaly detected by Isolation Forest
Large transaction amount
Low transaction fee
Transaction amount doubled compared to previous transaction
Rapid accumulation of large transactions
Very short time between transactions
|
0x921d532…
|
71
High
|
Short time frame between transactions
Anomaly detected by Isolation Forest
High frequency transactions (less than 1 minute interval)
Rapid multi-hop layering pattern detected
Low transaction fee
Part of coordinated wallet cluster
Related to 4 high-risk transactions (highest score: 81)
Very short time between transactions
Transaction amount significantly lower than average
Transaction amount halved compared to previous transaction
|
0xaa5b18f…
|
29
Medium
|
Short time frame between transactions
Low transaction fee
Outgoing structuring detected: 3 similar amounts totaling 0.00
Very short time between transactions
Transaction amount significantly lower than average
Transaction amount halved compared to previous transaction
|
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: 14
Medium Risk Activities: 0
Total Flagged Transactions: 14
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 0x0ea023e71f0e13d275b0b886d87aff2f7516de38:
1. Risk Assessment
- Overall Risk Level: Very High
- Standardized Risk Score: 100/100
- Average Transaction Risk Score: 54.29
- Total Suspicious Patterns: 14
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: 2025-07-13 22:16:07 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 13, 2025
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