maltrail
by stamparm
Maltrail is a malicious traffic detection system that leverages public blacklists and heuristic analysis to identify suspicious network activity.
Malicious traffic detection system
Primary Use Case
Maltrail is primarily used by network administrators and security professionals to monitor network traffic for signs of intrusion, malware communication, and other malicious activities. It helps in real-time detection and alerting of suspicious domains, IPs, URLs, and user-agent strings, facilitating proactive threat hunting and network security enforcement.
- Utilizes numerous public blacklists and custom user-defined lists for threat detection
- Supports detection of malicious domains, IP addresses, URLs, and HTTP User-Agent headers
- Includes advanced heuristic mechanisms to identify unknown threats
- Provides a web-based reporting interface for monitoring and analysis
- Detects a wide range of suspicious activities including mass scans, port scanning, and data leakage
- Manually curated static trails from AV reports and personal research
- Supports real-life case detection such as ransomware, malware C&Cs, and anonymous attackers
- Open-source with MIT license and supports Python 2.6/2.7 and 3.x
Installation
- Clone the repository: git clone https://github.com/stamparm/maltrail.git
- Navigate to the maltrail directory
- Install required dependencies (Python environment recommended)
- Run the sensor component to start monitoring network traffic
- Run the server component to enable the web-based reporting interface
Usage
>_ python sensor.pyStarts the sensor to capture and analyze network traffic for malicious trails
>_ python server.pyStarts the server to provide the web-based reporting interface
- Integrate Maltrail alerts with SIEM platforms for centralized incident correlation and faster response.
- Use Maltrail's heuristic detection to identify zero-day or unknown threats during red team exercises.
- Leverage Maltrail's blacklist feeds to automate network access blocking for suspicious IPs and domains.
- Deploy sensors at network choke points to maximize visibility of lateral movement and data exfiltration attempts.
- Combine Maltrail with endpoint detection tools to enrich threat hunting and forensic investigations.
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