The plans, the main opportunities, the features and technical specifications of Nemesida WAF.
- On-premises software
- Does not use cloud computing
- Does not transmit traffic and other sensitive data outside the perimeter
||IPS, IDS, Combined
Pricing and options
|Type of software delivery
||Full on-premises software
|Types of blocked attacks
||SQLi, RCE, OS Injection, SSTI, LDAP, NoSQL, XSS, XXE, Information Leakage, Path Traversal, Open Redirect, Web Shell, RFI/LFI, SSRF, Account Takeover, Brute-force, abuse of SMS functionality, DDoS L7 etc.
|Scalability and fault tolerance: supports Active-Active and Active-Passive clustering
|Bot protection: detection of DDoS L7, account takeover (ATO), flooding and other malicious traffic
|Detecting attacks by signature method
|Attack detection by the machine learning module
|Blocking attempts to exploit zero-day vulnerabilities
|Vulnerability detection using Nemesida WAF Scanner
|Generating of virtual pathching rules
||Manually and automatically
|Number of behavioral models included in the basic license
|Configuration using the web interface and API
||Nemesida WAF Cabinet
Basic technical support
(basic consultations, Nemesida WAF bug fixes)
Included in the price
* Due to the specifics of licensing, the price of this product is available on request. License renewal (annual subscription) is made with 30% discount from the cost of the plan and is calculated from the current cost at the time of renewal. For more information, please contact us by email@example.com.
🔗 Nemesida® AI – a machine learning module
|Accuracy of identification of the attacks
||Nemesida AI is about 53.04%* more efficient than signature analysis.
|Machine learning method
||The Nemesida WAF operation is based on classical machine learning algorithm «Random Forest», that is able to detect attack with minimum response time, nearly without false positives.
|Hardware resource requirements
||Unlike training models using neural networks, classical machine learning algorithms do not require much processing power, so the processor of the Intel Core i3 family or higher will be sufficient for calculations.
- Adaptation of WAF to a mutable application
- Automatic creation of behavioral models
- Detection of anomalies and assessment of their severity level
- Identification of new signs of attacks, including the identification of «zero day» attacks
- Behavioral models management interface (additional training of models)
- Ability to change the training period of behavioral models
- Additional training of models using a backup copy of the training sample
* Test result of Nemesida WAF using only signature analysis and machine learning (detection accuracy: 46.62% and 99.66%, respectively). The testing was performed using the specialized WAF Bypass Tool. Based on the test results, the use of machine learning improves detection accuracy by 53.04%.
The result of testing Nemesda WAF
Diagram of Nemesida WAF modules interaction
1 Includes Nginx, the Nemesida WAF dynamic module and the Nemesida AI MLA machine learning agent.
- Nemesida WAF dynamic module carries out a signature analysis of requests coming to the server and, based on the behavioral models built by Nemesida AI MLC, makes a decision to block them or transfer them to other modules.
- Nemesida AI MLA machine learning module applies behavioral models built by Nemesida AI MLC to requests received from the dynamic module and sends a blocking command.
- Nemesida AI MLC machine learning module is designed to build behavioral models and detect other anomalies (for example, Brute-force, Flood, DDoS L7).
- The Nemesida WAF API is designed to receive information about attacks and identified vulnerabilities, as well as transmit information about blocked requests and the results of the Nemesida AI and Nemesida WAF Scanner modules to the PostgreSQL DBMS.
- Nemesida WAF Cabinet is designed for visualization and analysis of the events of the components from the PostgreSQL DBMS, management of Nemesida WAF settings, management of OpenAPI query schemes, configuration of the use of behavioral models built and applied by the Nemesida AI module, as well as systematization of information about anomalies and identified vulnerabilities.
- The Nemesida WAF Scanner Vulnerability Scanner is designed to detect vulnerabilities in a protected web application.
- Blocking an individual request
- Temporarily blocking requests from the source by IP address
- No artificial restrictions on traffic, RPS and the number of virtual hosts
- Validate HTTP Transactions for RFC Compliance and Best Practices
- Categorization by the type of activity (type of attack) of sources
- Detection of bots based on their traits and behavioral analysis
- Creation of signatures and their exclusions based on a set of criteria (for example: method, URL, parameter value, headers) and regular expressions
- Using machine learning to minimize false positives and detect unknown attacks, easy management of the learning or retraining process via a web interface
- Support for WebSockets, XML, JSON
- Integration with ClamAV antivirus, SIEM systems and firewalls
- Analysis of web application vulnerabilities using Nemesida WAF Scanner
- Noncommercial version with limited functionality Nemesida WAF Community Edition with basic protection of web applications from OWASP attacks based on signature analysis
- Own GeoIP base
Filtering and notifications
- Comfortable in use Nemesida WAF 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 (attack timeline, detailed reports in PDF and CSV format)
- 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 notifications
Try Nemesida WAF for free
Nemesida WAF is well-scalable, does not have any limitations of virtual hosts or traffic and auxiliary modules such as vulnerability scanner, virtual patching and cabinet will make your work with Nemesida WAF easy and transparent. Now it is not required to make exclusion rules – machine learning module will adapt to any web application. You can inspect incidents in Nemesida WAF Cabinet and enjoy the work with Nemesida WAF.