Lazarus High Risk Bybit Hacking Investigation [CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001] - Wallet Analysis Report - Very High Risk - 0xc241...bf99
Published
15 Jul 2025
6 views
Wallet Name
Analysis Target Wallet (CLADIOUS-[BYBIT_HACKER_LAZARUS_ITER]-2025-001) - 0xc241...bf99
LLM Analysis
Overview
Project Scope
Analysis of wallet 0xc241f393430be89d24ca0dcb35b111e03ed9bf99 - Lazarus High Risk Bybit Hacking Investigation
Suspicious Wallet Hash
0xc241f393430be89d24ca0dcb35b111e03ed9bf99
This is the primary wallet address being investigated in this report.
Methodology
Research Methodology
Automated Analysis Methodology for Wallet 0xc241f393430be89d24ca0dcb35b111e03ed9bf99
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 0xc241f393430be89d24ca0dcb35b111e03ed9bf99
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 0xc241f393430be89d24ca0dcb35b111e03ed9bf99
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.
0x8630b349aeefe1583bc5e3c25c5aba0e12f1b7c7f662b88c7640cb92c42e6bcc: Very short time between transactions
0x83f2e0d54972be8108d29256b7d5cf565b921f8649932ea02fbd878ab7a43507: Very short time between transactions
0x8ad55be201c977ecdfe6fd63b2400e52920421d20cc30aa96bb1a050826bc513: Very short time between transactions
0xda661ac79f3c56e99d31120c5a4e5bdea0b6e156f732c07d0c75f8e63e8d2394: Very short time between transactions
0x1c83b82680b5d74f77d48567dd51a6d12740b489a6dd675c95787f2806402a77: Very short time between transactions
0xe9737685204095ee4fce4cbcfde108d84ac759634e42e03cf4dfaba2741f40df: Very short time between transactions
0x4f0ff41bc261999c1e9ba0cfa816c1423873eb3a86c18c2a0ace108edc194fd9: Very short time between transactions
0xbc0428db9a680a6560daaeada4e88833e67dde8b7ae96ec951240c73aed7a557: Very short time between transactions
0x8fea57d8413033ac112336deb929990c53a62e1085aae099bd19894b9d5e09e5: Very short time between transactions
0x2415fbe454d3d7dcc604e4e8075be32039e91ed1c257ab27997d1c17cdc01d8c: Very short time between transactions
0xe95a67c68c8a8e0da03abff222137459aad05dd588efac10aedbe7c086a5063e: Very short time between transactions
0x0bc1e6b15012b11febbd50481cfb5cac9761fcd4c2ee7b7772a7120362495077: Very short time between transactions
0xd526e98a0f5f3866078037d4f2a62c9a8f26d17d3895e891dbd5d07695c5cdf8: Very short time between transactions
0x8630b349aeefe1583bc5e3c25c5aba0e12f1b7c7f662b88c7640cb92c42e6bcc: Transaction amount doubled compared to previous transaction
0x83f2e0d54972be8108d29256b7d5cf565b921f8649932ea02fbd878ab7a43507: Transaction amount halved compared to previous transaction
0x4f0ff41bc261999c1e9ba0cfa816c1423873eb3a86c18c2a0ace108edc194fd9: Transaction amount doubled compared to previous transaction
0x8630b349aeefe1583bc5e3c25c5aba0e12f1b7c7f662b88c7640cb92c42e6bcc: High frequency transactions (less than 1 minute interval)
0x83f2e0d54972be8108d29256b7d5cf565b921f8649932ea02fbd878ab7a43507: High frequency transactions (less than 1 minute interval)
0x8ad55be201c977ecdfe6fd63b2400e52920421d20cc30aa96bb1a050826bc513: High frequency transactions (less than 1 minute interval)
0xda661ac79f3c56e99d31120c5a4e5bdea0b6e156f732c07d0c75f8e63e8d2394: High frequency transactions (less than 1 minute interval)
0x1c83b82680b5d74f77d48567dd51a6d12740b489a6dd675c95787f2806402a77: High frequency transactions (less than 1 minute interval)
0xe9737685204095ee4fce4cbcfde108d84ac759634e42e03cf4dfaba2741f40df: High frequency transactions (less than 1 minute interval)
0x4f0ff41bc261999c1e9ba0cfa816c1423873eb3a86c18c2a0ace108edc194fd9: High frequency transactions (less than 1 minute interval)
0xbc0428db9a680a6560daaeada4e88833e67dde8b7ae96ec951240c73aed7a557: High frequency transactions (less than 1 minute interval)
0x8fea57d8413033ac112336deb929990c53a62e1085aae099bd19894b9d5e09e5: High frequency transactions (less than 1 minute interval)
0x2415fbe454d3d7dcc604e4e8075be32039e91ed1c257ab27997d1c17cdc01d8c: High frequency transactions (less than 1 minute interval)
0xe95a67c68c8a8e0da03abff222137459aad05dd588efac10aedbe7c086a5063e: High frequency transactions (less than 1 minute interval)
0x0bc1e6b15012b11febbd50481cfb5cac9761fcd4c2ee7b7772a7120362495077: High frequency transactions (less than 1 minute interval)
0xd526e98a0f5f3866078037d4f2a62c9a8f26d17d3895e891dbd5d07695c5cdf8: High frequency transactions (less than 1 minute interval)
Suspicious Transactions
| Transaction Hash | Risk Score | Risk Factors | Tags |
|---|---|---|---|
0x8ad55be…
|
65
High
|
Short time frame between transactions
Rapid multi-hop layering pattern detected
Very short time between transactions
Outgoing structuring detected: 3 similar amounts totaling 106.37
Transaction amount significantly higher than average
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
Transaction amount doubled compared to previous transaction
|
No tags
|
0x83f2e0d…
|
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
|
No tags
|
0x2415fbe…
|
42
High
|
Short time frame between transactions
Very short time between transactions
Transaction amount significantly lower than average
Fan-in structuring detected: 3 similar amounts from different addresses totaling 0.00
Low transaction fee
Part of coordinated wallet cluster
Transaction amount halved compared to previous transaction
|
No tags
|
0x8fea57d…
|
58
High
|
High frequency transactions (less than 1 minute interval)
Short time frame between transactions
Very short time between transactions
Outgoing structuring detected: 3 similar amounts totaling 106.37
Transaction amount significantly higher than average
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
Transaction amount doubled compared to previous transaction
Regular interval transactions between the same wallets
|
No tags
|
0xda661ac…
|
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
Transaction amount significantly lower than average
Low transaction fee
Part of coordinated wallet cluster
Transaction amount halved compared to previous transaction
|
No tags
|
0xe973768…
|
59
High
|
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
Part of coordinated wallet cluster
Transaction amount halved compared to previous transaction
|
No tags
|
0x4f0ff41…
|
59
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
Transaction amount doubled compared to previous transaction
Part of coordinated wallet cluster
|
No tags
|
0xbc0428d…
|
41
High
|
Repetitive transaction amount
Short time frame between transactions
High frequency transactions (less than 1 minute interval)
Very short time between transactions
Transaction amount significantly lower than average
Low transaction fee
Part of coordinated wallet cluster
|
No tags
|
0xe95a67c…
|
40
High
|
Repetitive transaction amount
Short time frame between transactions
Very short time between transactions
Transaction amount significantly lower than average
Fan-in structuring detected: 3 similar amounts from different addresses totaling 0.00
Low transaction fee
Part of coordinated wallet cluster
|
No tags
|
0x0bc1e6b…
|
40
High
|
Repetitive transaction amount
Short time frame between transactions
Very short time between transactions
Transaction amount significantly lower than average
Fan-in structuring detected: 3 similar amounts from different addresses totaling 0.00
Low transaction fee
Part of coordinated wallet cluster
|
No tags
|
0xd526e98…
|
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
|
No tags
|
0x8630b34…
|
100
High
|
High frequency transactions (less than 1 minute interval)
Transaction involves DeFi exploit address: Bybit Exploiter 15
Related to 147 high-risk transactions (highest score: 100)
Very short time between transactions
Receives funds from exploit address: 0x229093...
Transaction amount significantly higher than user average
Transaction amount significantly higher than average
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
|
No tags
|
0x367f16d…
|
51
High
|
Short time frame between transactions
Very short time between transactions
Outgoing structuring detected: 3 similar amounts totaling 106.37
Transaction amount significantly higher than average
Low transaction fee
Anomaly detected by Isolation Forest
Large transaction amount
Transaction amount halved compared to previous transaction
|
No tags
|
0x1c83b82…
|
29
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 doubled compared to previous transaction
|
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: 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 0xc241f393430be89d24ca0dcb35b111e03ed9bf99:
1. Risk Assessment
- Overall Risk Level: Very High
- Standardized Risk Score: 100/100
- Average Transaction Risk Score: 51.00
- 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: 2025-07-15 18:12:14 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
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