Review of the main opportunities, the features and technical specifications of Nemesida WAF.
A feature of Nemesida WAF is the accuracy of detecting attacks with a minimum number of false positives, the presence of a virtual patching system, a high-quality signature database, scalability and pricing policy, allowing you to ensure the safety of online stores, portals, API and other web-applications in enterprises of any size.
|Documentation language||Russian, English|
|Availability of a research center in Russia||lab.pentestit.ru|
|Operation mode||IPS, IDS, Combined|
Clustering, SSL, standards
- Termination SSL
- Passive decoding SSL
- Support of sessions established on client certificates
- Support of Active-Active clustering
- Support of Active-Passive clustering
- Support of balancing of loading between the protected web applications
- Support of WebSockets
- Support of XML
- Support of JSON
Detection of attacks
|Class of blocked attacks||
|The presence of a reputation base||Own reputation and GeoIP base.|
|Detection of bots on the basis of values of query fields||Based on their signatures and behavioral analysis.|
Machine learning (Nemesida AI)
|Accuracy of identification of the attacks||Nemesida AI ≈ 30% more efficient than signature analysis.|
|Machine learning method||The classical algorithm of machine learning is used. Key features of Nemesida AI are the accuracy of identification of anomalies, the minimum quantity of false operations and lack of high requirements to hardware resources.|
Nemesida WAF is able to detect brute-force attacks, including distributed ones used Levenshtein distance and fuzzy logic.
- Integration with vulnerability scanners, including the Nemesida WAF Scanner
- Antivirus analysis
- Simply SIEM integration
- Firewall Integration
- Lack of traffic and virtual hosts limitation for the Standalone-version
- Nemesida WAF Cabinet
- Nemesida WAF Scanner
- Virtual patching
Filtering and notifications
- Cabinet for dealing with incidents
- Flexible filtering of security log entries by specified criteria
- Manual and automatic aggregation of security log entries by attack type, parameter name, URL, IP address
- Attack verification using the built-in dynamic scanner
- Automatic aggregation of events with intense character
- Possibility of setting up reporting for obtaining summary information about safety events
- Existence of the interface with information on network loading of WAF
- The recorded events contain inquiry in full (entirely)
- The recorded events contain the description of the worked rule of security policy
- Export and import of the security event log in full amount
- E-mail and Syslog notifications
Combined analysis Nemesida WAF based on signatures and machine learning allows to provide the security of Internet stores, portals, API and other web-applications from hacker attacks with the minimum of false positives.
Machine learning module Nemesida AI blocks zero day and brute-force attacks without increasing of the response time. The module is well scalable and doesn't have high requirements to hardware resources.
Moreover, software Nemesida WAF includes vulnerability scanner, virtual patching system and a lot of additional components which is promotive of increasing of the web-application security level.