Medium Risk Wallet 0x854f5cc104492b4ffeb42fa81fd03bb195340e2e Analysis Report
Published
25 Apr 2025
5 views
Wallet Name
Fake_Phishing1086779 related Fake_Phishing_r_1086779
Overview
Project Scope
Project Scope: Scope Wallet details have been reviewed Based on the analysis of wallet 0x854f5cc104492b4ffeb42fa81fd03bb195340e2e: Risk Level: Medium Total Issues Found: 14
Suspicious Wallet Hash
0x854f5cc104492b4ffeb42fa81fd03bb195340e2e
This is the primary wallet address being investigated in this report.
Methodology
Research Methodology
Analysis Methodology for Wallet 0x854f5cc104492b4ffeb42fa81fd03bb195340e2e
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: Medium
- Total Volume: 0.00
- Suspicious Patterns: 2
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 0x854f5cc104492b4ffeb42fa81fd03bb195340e2e
- No transactions found
- Retrieved token transfer history from the blockchain
2. Tag & Label Collection
- Analyzed 2 tagged transactions
- Found 1 unique tag categories
3. Analysis Results Collection
- Processed 2 analysis results
- Risk Score: 24 ,
- Detected 2 connected addresses
- Detected address list: <QuerySet ['0x854f5cc104492b4ffeb42fa81fd03bb195340e2e', '0x854f5cc104492b4ffeb42fa81fd03bb195340e2e']>
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 2 unusual user behaviors. Identified 2 trend anomalies. Discovered 2 time-based irregularities. Identified 2 suspicious wallet communities. Found 2 rapid multi-hop layering patterns. Discovered 2 coordinated wallet clusters. Located 2 suspicious transactions.
Overall Risk Assessment: Medium
Risk Level Analysis:
The wallet has been classified as MEDIUM RISK with a weighted risk score of 17.2 based on the following specific findings:
All Findings: - 2 unusual user behaviors detected, - 2 trend anomalies detected, - 2 time-based irregularities detected, - 2 suspicious wallet communities detected, - 2 rapid multi-hop layering patterns detected, - 2 coordinated wallet clusters detected, - 2 suspicious transactions detected This classification indicates MODERATE CONCERN requiring appropriate monitoring. We recommend: - Regular monitoring of the identified patterns - Periodic review of new transactions - Standard risk management protocols - Documentation of findings for future reference
No network-based suspicious activities detected. The wallet's network connections appear normal.
0x9771fb677880f4767e1fd5bdb7deb2cb90897d6d0e562f66f87f7f122b6f259c: Very short time between transactions
0x250d4e29a2fcaba72648608c93ed8940716c3e81373141bd2aca1579ebbeb6bb:
0x9771fb677880f4767e1fd5bdb7deb2cb90897d6d0e562f66f87f7f122b6f259c:
0x250d4e29a2fcaba72648608c93ed8940716c3e81373141bd2aca1579ebbeb6bb:
0x9771fb677880f4767e1fd5bdb7deb2cb90897d6d0e562f66f87f7f122b6f259c: High frequency transactions (less than 1 minute interval), Regular interval transactions between the same wallets
0x250d4e29a2fcaba72648608c93ed8940716c3e81373141bd2aca1579ebbeb6bb: High frequency transactions (less than 1 minute interval)
Suspicious Transactions
| Transaction Hash | Risk Score | Risk Factors |
|---|---|---|
0x250d4e2…
|
44
High
|
Part of suspicious wallet community
Low transaction fee
Very short time between transactions
Related to high-risk transaction 0x39f76b... (score: 67)
High frequency transactions (less than 1 minute interval)
Rapid multi-hop layering pattern detected
|
0x9771fb6…
|
52
High
|
Short time frame between transactions
Part of suspicious wallet community
Transaction amount significantly lower than average
Low transaction fee
High frequency transactions (less than 1 minute interval)
Rapid multi-hop layering pattern detected
Transaction amount halved compared to previous transaction
|
Showing 1 to 10 of 0 transactions
Advanced Analysis Findings
No local outlier anomalies detected. All transactions appear statistically normal.
0x9771fb677880f4767e1fd5bdb7deb2cb90897d6d0e562f66f87f7f122b6f259c: Part of suspicious wallet community
0x250d4e29a2fcaba72648608c93ed8940716c3e81373141bd2aca1579ebbeb6bb: Part of suspicious wallet community
0x250d4e29a2fcaba72648608c93ed8940716c3e81373141bd2aca1579ebbeb6bb: Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern 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0x9771fb677880f4767e1fd5bdb7deb2cb90897d6d0e562f66f87f7f122b6f259c: Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering pattern detected, Rapid multi-hop layering 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0x9771fb677880f4767e1fd5bdb7deb2cb90897d6d0e562f66f87f7f122b6f259c: Part of coordinated wallet cluster
0x250d4e29a2fcaba72648608c93ed8940716c3e81373141bd2aca1579ebbeb6bb: 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: 2 transactions
- Unusual Patterns: 0 cases identified
Temporal Analysis:
- Sudden Balance Changes:
- Transaction Frequency:
• Daily: 2 transactions
• Weekly: 2 transactions
Network Metrics:
- Risk Connections: 0 identified
- Flagged Interactions: 0 detected
Advanced Detection:
- Local Outlier Anomalies: 0 detected
- Suspicious Communities: 2 identified
- Layering Patterns: 2 found
- Coordinated Clusters: 2 observed
- Sanctioned Address Links: 0 discovered
Risk Assessment:
- Overall Risk Score: 48.00
- High Risk Activities: 2 instances
Conclusions & Recommendations
Conclusions
Based on our comprehensive analysis of wallet 0x854f5cc104492b4ffeb42fa81fd03bb195340e2e, we have reached the following key conclusions:
1. Risk Assessment Overview
- Overall Risk Score: 48.00/1.00
- 2 High Risk Activities Identified
- 0 Suspicious Network Connections
2. Transaction Pattern Analysis
- Detected 0 instances of potential mixing service usage
- Identified 2 high-value transfers requiring attention
- Observed 0 unusual transaction patterns
3. Temporal Behavior
- Daily Transaction Volume: 2 transactions
- Weekly Transaction Volume: 2 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
- 2 suspicious wallet communities suggesting coordinated activities
- 2 layering patterns potentially obscuring transaction origins
- 2 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 enhanced monitoring.
Recommendations
Based on our detailed analysis of wallet 0x854f5cc104492b4ffeb42fa81fd03bb195340e2e, 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
- Monitor detected layering patterns closely
- Implement hop analysis for multi-stage transactions
- Set alerts for rapid multi-hop transaction sequences
- 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 Part of suspicious wallet community, Short time frame between transactions, Transaction amount significantly lower 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
24
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
April 25, 2025
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