The plans, the main opportunities, the features and technical specifications of Nemesida WAF.
|WAF operation mode||IPS, IDS and combined|
|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, DDoS L7, flood and other malicious traffic|
|Scalability and fault tolerance: supports Active-Active and Active-Passive clustering||Yes|
|Bot protection: detection of DDoS L7, account takeover (ATO), flooding and other malicious traffic||Yes|
|Detecting attacks by signature method||Yes|
|Getting extended IP address information*||Yes|
|Attack detection by the AI/ML||n/a||Yes|
|Blocking attempts to exploit zero-day vulnerabilities||n/a||Yes|
|Centralized collection of events||n/a||Yes|
|Vulnerability detection using Nemesida WAF Scanner||n/a||Yes|
|Generating of virtual pathching rules||Manually||Manually and automatically|
|Configuration using the web interface and API||Yes|
* Obtaining extended information about the IP address allows you to determine the geographical location based on the IP address, check the presence of the address in the lists of proxy servers: Tor, VPN, Mobile or hosting sites, etc. The functionality is included in the software price and does not require the connection of third-party databases.
🔗 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.|
* Test result of Nemesida WAF using only signature analysis and AI/ML (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%.
|Additional behavioral model||n/a||$300
|The number of free behavioral models included in the plan||n/a||1||5|
|Basic technical support||
Included in plan price
* 30% discount on renewal of the annual subscription) from the current cost of the plan at the time of renewal.
** The price is available on request.
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.