A security-focused endpoint monitoring and analysis platform designed to detect, investigate, and report unauthorized outbound data transfers.
The project aims to identify which processes are sending data over the internet, determine where the data is being sent, analyze transfer behavior, and detect potential data exfiltration attempts.
Data exfiltration is the unauthorized transfer of information from a system to an external destination.
This project focuses on:
- Process monitoring
- Network activity analysis
- Process-to-network correlation
- Outbound data tracking
- Suspicious behavior detection
- Security alert generation
The goal is to provide visibility into endpoint network activity and help identify processes that may be transferring sensitive data outside the system.
- Monitor outbound network activity
- Attribute network connections to specific processes
- Analyze data transfer behavior
- Detect suspicious upload patterns
- Generate security alerts
- Build process activity timelines
- Support incident investigation workflows
Enumerate active processes running on the endpoint.
Example:
PID: 4120
Process: python.exe
Monitor active network connections.
Track:
- Local Address
- Remote Address
- Remote Port
- Protocol
- Connection State
Example:
Process:
python.exe
Destination:
104.18.x.x
Protocol:
TCP
Port:
443
Associate network activity with the responsible process.
Example:
python.exe
↓
Connected To
↓
example.com
Measure:
- Upload volume
- Download volume
- Transfer rate
- Session statistics
Example:
Process:
python.exe
Uploaded:
850 MB
Downloaded:
12 MB
Collect contextual information about network destinations.
Track:
- IP Address
- Domain Name
- Connection History
- Frequency of Communication
Example:
Destination:
api.example.com
Connections:
57
Build a chronological view of process activity.
Example:
10:01 Process Started
10:03 Network Connection Opened
10:04 Upload Activity Detected
10:10 Connection Closed
Detect potentially abnormal behaviors.
Examples:
- Excessive outbound transfers
- Repeated connections to unknown destinations
- Continuous background uploads
- Unexpected network activity
Example:
Alert
Process:
python.exe
Reason:
Unusual outbound transfer volume
Generate alerts for:
- High upload volume
- Suspicious communication patterns
- Unknown process activity
- Potential data exfiltration events
Create investigation reports containing:
- Process information
- Network destinations
- Data transfer statistics
- Event timeline
- Detection findings
Processes
│
▼
Process Monitor
│
▼
Network Monitor
│
▼
Correlation Engine
│
▼
Behavior Analysis Engine
│
▼
Detection Engine
│
▼
Alerting & Reporting
- Active connection enumeration
- Network activity collection
- Connection tracking
- Process discovery
- PID tracking
- Process-to-connection mapping
- Destination analysis
- Domain resolution
- Communication statistics
- Upload monitoring
- Download monitoring
- Transfer metrics
- Event collection
- Activity timeline generation
- Historical analysis
- Behavioral rules
- Anomaly detection
- Alert generation
- Multi-event correlation
- Exfiltration pattern identification
- Investigation support
- Security notifications
- Detection alerts
- Incident creation
- Process isolation
- Connection blocking
- Automated response workflows
- Endpoint monitoring
- Threat detection
- Security analytics
- Incident response
Planned Technologies:
- C++
- Windows API
- Winsock
- Multithreading
- Event Logging
- Security Telemetry
- Security Software Engineers
- Endpoint Security Engineers
- Detection Engineers
- Security Researchers
- SOC Analysts
- Incident Responders
Build a lightweight endpoint security platform capable of:
- Monitoring endpoint activity
- Detecting unauthorized outbound communications
- Identifying potential data exfiltration attempts
- Supporting threat investigation and incident response
through process-aware network intelligence and behavioral analysis.
License to be determined.