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Description
Malcolm serves as an open-source platform for security monitoring, aimed at assisting security experts in the collection, processing, and analysis of network data to facilitate threat detection and incident response. By integrating a suite of robust tools, it enables users to capture and visualize network traffic, log information, and security alerts effectively. The platform features a user-friendly interface that simplifies the investigation of potential threats, granting security analysts detailed insights into network activities. Scalability is a key aspect of Malcolm, as it offers versatile deployment options suitable for a range of environments, from small businesses to large corporations. Additionally, its modular architecture allows users to tailor the platform according to their unique security needs, while seamless integration with other observability tools enhances overall monitoring capabilities. Although Malcolm excels in general network traffic analysis, its developers recognize a specific demand within the community for tools that deliver insights into protocols employed in industrial control systems (ICS), thereby addressing a critical niche in security monitoring. This focus on ICS enhances the platform’s relevance in sectors where such systems are vital for operational integrity and safety.
Description
MixMode's Network Security Monitoring platform offers unmatched network visibility, automated threat detection, and in-depth network investigation capabilities, all driven by advanced Unsupervised Third-Wave AI technology. This platform provides users with extensive visibility, enabling them to swiftly pinpoint threats in real time through Full Packet Capture and long-term Metadata storage. With its user-friendly interface and straightforward query language, any security analyst can conduct thorough investigations, gaining insights into the complete lifecycle of threats and network irregularities. Leveraging the power of Third-Wave AI, MixMode adeptly detects Zero-Day Attacks in real time by analyzing typical network behavior and highlighting any unusual activity that deviates from established patterns. Initially developed for initiatives at DARPA and the Department of Defense, MixMode's Third-Wave AI eliminates the need for human training, allowing it to establish a baseline for your network within just seven days, achieving an impressive 95% accuracy in alerts while also minimizing and identifying zero-day attacks. Additionally, this innovative approach ensures that security teams can respond rapidly and effectively to emerging threats, enhancing overall network resilience.
API Access
Has API
API Access
Has API
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Malcolm
Country
United States
Website
malcolm.fyi/
Vendor Details
Company Name
MixMode
Founded
2012
Country
United States
Website
mixmode.ai/
Product Features
Network Traffic Analysis (NTA)
Anomalous Behavior Detection
High Bandwidth Usage Monitoring
Historical Behavior Data
Identify High Network Traffic Sources
Network Transaction Visibility
Stream Data to IDR or Data Lake
Traffic Decryption
Product Features
Network Security
Access Control
Analytics / Reporting
Compliance Reporting
Firewalls
Internet Usage Monitoring
Intrusion Detection System
Threat Response
VPN
Vulnerability Scanning
Network Traffic Analysis (NTA)
Anomalous Behavior Detection
High Bandwidth Usage Monitoring
Historical Behavior Data
Identify High Network Traffic Sources
Network Transaction Visibility
Stream Data to IDR or Data Lake
Traffic Decryption
