Low Risk Wallet 0x874a7d65a03c40a3b9127ac7d0d212c24063202b Analysis Report
Published
27 May 2025
6 views
Wallet Name
0x874a7d65a03c40a3b9127ac7d0d212c24063202b
Overview
Project Scope
Project Scope: Standard review process Based on the analysis of wallet 0x874a7d65a03c40a3b9127ac7d0d212c24063202b: Risk Level: Low Total Issues Found: 6
Suspicious Wallet Hash
0x874a7d65a03c40a3b9127ac7d0d212c24063202b
This is the primary wallet address being investigated in this report.
Methodology
Research Methodology
Analysis Methodology for Wallet 0x874a7d65a03c40a3b9127ac7d0d212c24063202b
PRIMARY FOCUS: Regular Transaction Wallet
- Standard transaction monitoring
- Basic pattern analysis
- Normal risk assessment
1. Transaction Pattern Analysis (Standard Volume Profile)
- Basic transaction flow analysis
- Simple pattern recognition
- Standard volume monitoring
- Regular interaction checks
2. Network Analysis (Simple Network)
- Basic network mapping
- Direct relationship analysis
- Simple connection tracking
- First-degree interaction monitoring
3. Behavioral Analysis (Standard Profile)
- Basic behavioral monitoring
- Standard risk factor checking
- Simple pattern matching
- Single-chain activity tracking
4. Risk Scoring Weights (Customized for this wallet):
- Transaction Patterns: 0.25
- Network Complexity: 0.25
- Behavioral Indicators: 0.25
- Historical Markers: 0.25
5. Specialized Detection Methods:
- Basic anomaly detection
- Standard pattern recognition
- Simple behavior analysis
- Regular monitoring checks
6. Standard Compliance Measures:
- Standard due diligence
- Regular reporting
- Basic transaction tracking
- Normal audit procedures
Key Statistics Influencing Methodology:
- Transaction Count: 0
- Network Connections: 0
- Risk Level: Low
- Total Volume: 0.00
- Suspicious Patterns: 1
Confidence Metrics:
- Analysis Confidence: 85%
- Risk Assessment Accuracy: 80%
- Pattern Recognition Reliability: 85%
This methodology has been specifically tailored for this wallet based on:
- Historical transaction patterns
- Network complexity level
- Risk profile characteristics
- Volume and frequency metrics
- Detected behavioral patterns
The analysis approach will be automatically adjusted as new patterns emerge.
Data Collection
Data Collection Process:
1. Transaction Data Collection
- Collected transaction data from wallet address 0x874a7d65a03c40a3b9127ac7d0d212c24063202b
- No transactions found
- Retrieved token transfer history from the blockchain
2. Tag & Label Collection
- Analyzed 1 tagged transactions
- Found 1 unique tag categories
3. Analysis Results Collection
- Processed 1 analysis results
- Risk Score: 5 ,
- Detected 1 connected addresses
- Detected address list: <QuerySet ['0x874a7d65a03c40a3b9127ac7d0d212c24063202b']>
4. Data Validation Status
- Data integrity: ✓ Verified
- Tag consistency: ✓ Verified
Data Preprocessing
Data Preprocessing Steps:
1. Transaction Data Cleaning
- Removed duplicate transactions
- Standardized timestamp formats
- Normalized transaction amounts to USD values
- Filtered out invalid or incomplete transactions
- Handled missing values in transaction records
2. Feature Engineering
- Created time-based features (hour, day, week patterns)
- Calculated transaction velocity metrics
- Generated network centrality measures
- Derived statistical features from amounts
- Computed temporal transaction patterns
3. Address Clustering
- Grouped related addresses using common spending patterns
- Identified address clusters through heuristic analysis
- Merged addresses with similar behavioral patterns
- Tagged address clusters with risk categories
4. Outlier Detection
- Applied statistical methods to detect anomalous transactions
- Identified unusual patterns in transaction amounts
- Flagged suspicious temporal patterns
- Detected anomalous network connections
- Utilized Local Outlier Factor algorithm for rare event detection
5. Data Aggregation
- Aggregated transaction data by time windows
- Computed summary statistics for each address
- Generated address interaction matrices
- Created temporal activity profiles
- Built community graphs for relationship mapping
6. Data Transformation
- Normalized numerical features
- Encoded categorical variables
- Applied dimensionality reduction where needed
- Scaled features for model compatibility
7. Quality Checks
- Validated data consistency
- Verified feature completeness
- Ensured proper handling of edge cases
- Confirmed data integrity post-processing
Design Pattern
No design pattern information is available for this report.
Analysis
Detected 1 unusual user behaviors. Identified 1 trend anomalies. Discovered 1 time-based irregularities. Identified 1 suspicious wallet communities. Discovered 1 coordinated wallet clusters. Located 1 suspicious transactions.
Overall Risk Assessment: Low
Risk Level Analysis:
The wallet has been classified as LOW RISK with a weighted risk score of 7.1 based on the following specific findings:
All Findings: - 1 unusual user behaviors detected, - 1 trend anomalies detected, - 1 time-based irregularities detected, - 1 suspicious wallet communities detected, - 1 coordinated wallet clusters detected, - 1 suspicious transactions detected This classification indicates MINIMAL CONCERN with standard monitoring recommended. We suggest: - Normal transaction monitoring procedures - Periodic risk reassessment - No special measures required at this time
No network-based suspicious activities detected. The wallet's network connections appear normal.
0x6061394570526d8f79469a6b7373e7aa63c11995ea3bc66efa70cb6fd03301ad:
0x6061394570526d8f79469a6b7373e7aa63c11995ea3bc66efa70cb6fd03301ad:
0x6061394570526d8f79469a6b7373e7aa63c11995ea3bc66efa70cb6fd03301ad: High frequency transactions (less than 1 minute interval)
Suspicious Transactions
| Transaction Hash | Risk Score | Risk Factors |
|---|---|---|
0x6061394…
|
67
High
|
Local Outlier Factor (LOF) detected as anomaly
Anomaly detected by Isolation Forest
Transaction amount significantly higher than average
High frequency transactions (less than 1 minute interval)
Transaction amount significantly higher than user average
Rapid multi-hop layering pattern detected
Very short time between transactions
|
Showing 1 to 10 of 0 transactions
Advanced Analysis Findings
No local outlier anomalies detected. All transactions appear statistically normal.
0x6061394570526d8f79469a6b7373e7aa63c11995ea3bc66efa70cb6fd03301ad: Part of suspicious wallet community
No rapid multi-hop layering patterns detected. Transactions follow expected paths.
0x6061394570526d8f79469a6b7373e7aa63c11995ea3bc66efa70cb6fd03301ad: Part of coordinated wallet cluster
No connections to sanctioned addresses detected. No regulatory compliance concerns identified.
Suspicious Activities
High Risk Patterns:
- Mixing Services: 0 instances detected
- High Value Transfers: 1 transactions
- Unusual Patterns: 0 cases identified
Temporal Analysis:
- Sudden Balance Changes:
- Transaction Frequency:
• Daily: 1 transactions
• Weekly: 1 transactions
Network Metrics:
- Risk Connections: 0 identified
- Flagged Interactions: 0 detected
Advanced Detection:
- Local Outlier Anomalies: 0 detected
- Suspicious Communities: 1 identified
- Layering Patterns: 0 found
- Coordinated Clusters: 1 observed
- Sanctioned Address Links: 0 discovered
Risk Assessment:
- Overall Risk Score: 67.00
- High Risk Activities: 1 instances
Conclusions & Recommendations
Conclusions
Based on our comprehensive analysis of wallet 0x874a7d65a03c40a3b9127ac7d0d212c24063202b, we have reached the following key conclusions:
1. Risk Assessment Overview
- Overall Risk Score: 67.00/1.00
- 1 High Risk Activities Identified
- 0 Suspicious Network Connections
2. Transaction Pattern Analysis
- Detected 0 instances of potential mixing service usage
- Identified 1 high-value transfers requiring attention
- Observed 0 unusual transaction patterns
3. Temporal Behavior
- Daily Transaction Volume: 1 transactions
- Weekly Transaction Volume: 1 transactions
- Notable sudden balance changes detected in temporal analysis
4. Network Analysis
- 0 flagged interactions with other addresses
- Complex transaction paths suggesting potential layering activity
- Multiple connections to previously flagged addresses
5. Advanced Detection Findings
- 0 local outlier anomalies indicating unusual transaction characteristics
- 1 suspicious wallet communities suggesting coordinated activities
- 0 layering patterns potentially obscuring transaction origins
- 1 coordinated wallet clusters identified
- 0 connections to sanctioned addresses representing regulatory risk
Summary: The wallet demonstrates moderate risk factors based on transaction patterns, network connections, temporal behaviors, and advanced detection metrics. The presence of suspicious patterns warrants standard review.
Recommendations
Based on our detailed analysis of wallet 0x874a7d65a03c40a3b9127ac7d0d212c24063202b, we recommend the following actions:
1. Transaction Monitoring Recommendations
- Monitor high-value transfers more closely
- Set transaction thresholds and implement additional verification steps
- Consider implementing velocity checks for large transactions
2. Risk Mitigation Steps
3. Advanced Detection Follow-up
- Monitor identified wallet communities for coordinated activities
- Track wallet community growth and transaction patterns
- Implement alerts for new activity within flagged communities
4. Layering and Clustering Surveillance
- Track coordinated wallet cluster activity
- Monitor for new addresses joining identified clusters
- Analyze temporal patterns across clustered wallets
5. Compliance Actions
6. Future Monitoring Strategy
- Frequency: Weekly monitoring should be sufficient based on current risk assessment
- Scope: Focus on Local Outlier Factor (LOF) detected as anomaly, Anomaly detected by Isolation Forest, Transaction amount significantly higher than average patterns
- Duration: Maintain enhanced monitoring for at least 6 months
7. Additional Recommendations
- Document all findings in compliance management system
- Update risk assessment every 30 days
- Share findings with relevant stakeholders and compliance teams
Severity Assessment
5
Appendices & References
Appendices
Appendix A: Transaction Analysis Details
- Include detailed transaction logs
- Add blockchain explorer screenshots
- Attach any relevant wallet analysis reports
Appendix B: Supporting Documentation
- Include copies of any referenced regulations or guidelines
- Add relevant policy documents
- Attach any correspondence related to the investigation
Appendix C: Technical Analysis
- Include network graphs and visualizations
- Add statistical analysis results
- Attach raw data exports if relevant
Appendix D: Advanced Detection Results
- Include Local Outlier Factor (LOF) analysis outputs
- Add community detection visualizations
- Include layering pattern diagrams
- Attach address clustering results
- Include sanctioned address check reports
Note: Please organize appendices clearly with proper labeling and references. Include any additional materials that support your findings and recommendations.
References
Please include relevant references from the following categories:
1. Blockchain Analysis Tools & Resources
- Links to relevant blockchain explorers used
- API documentation references
- Analysis platform documentation
2. Regulatory & Compliance Documents
- Applicable regulatory guidelines
- AML/CFT frameworks
- Industry compliance standards
- Sanctioned address lists and sources
3. Technical Documentation
- Blockchain analysis methodology references
- Transaction tracing documentation
- Network analysis frameworks
- Anomaly detection algorithms and implementations
4. Internal Resources
- Previous related analysis reports
- Company policies and procedures
- Internal risk assessment guidelines
5. Supporting Materials
- Relevant case studies
- Industry reports and whitepapers
- Expert consultations
- Academic research on detection methods
Note: For each reference, include full citation with date accessed and version/publication info where applicable.
Contact Information
Report Information
Author
Cladious Cladious
Published Date
May 27, 2025
Views
6
Likes
0