Are you aware of the fact that a data API can be a great tool for mitigating DNS attacks? Here we’ll explain you the four major DNS attack types and tell you how you can keep them away!
In a Domain Name System (DNS) assault, a malicious actor either attempts to hack a network’s DNS or makes use of its built-in advantages to launch a more extensive attack. A well-planned DNS strike has the power to destroy an organization. The DNS infrastructure is the target of a DNS attack. Attacks can be made to target authoritative or recursive servers. The four basic kinds of DNS assaults are as follows.
DoS: One machine and one internet connection are used in a straightforward DoS attack to bombard a remote server. They don’t do a great job of overpowering the high-capacity systems of today.
DDoS: A site is the target of a DDoS assault, which involves several computers and internet connections. DDoS assaults frequently enlarge a botnet of hacked computers that silently execute malicious queries.
Attackers have access to the computing power of numerous devices that can simultaneously query the target network. DDoS assaults do, in fact, frequently target certain OSI model layers. The concept breaks down network communication into seven abstract layers, each of which
DNS amplification: An instance of a DDoS assault known as a DNS amplification uses open DNS servers that are publicly accessible to bombard a target with DNS answer traffic. An attacker spoofs the source address of a DNS lookup request to be the address of the target and delivers it to an open DNS server. The target receives the DNS record response when the DNS server transmits it.
DNS tunneling: DNS tunneling uses the DNS protocol, which typically resolves network addresses, to transfer data. Normal DNS requests merely provide the data required for client and server communication. DNS tunneling adds an extra string of information to that path. It creates a channel of communication that gets past the majority of firewalls, filters, and packet capturing programs.
APIs for mitigating attacks and which to use
It’s definitely possible to mitigate all of these attacks in a simple and automated way by employing a data categorization API. These solutions often handle all currently provided domains and almost all worldwide languages, making them ideal for internet filtering and security applications. One example of this is Klazify, a tool created by Zyla Labs.
A machine learning (ML) engine is used by Klazify’s Website Categorization and Social Media Scanner API to scan a website’s content and meta tags. It collects text from the website, uses natural language processing to categorise it, and assigns up to three categories (NLP).
In accordance with an IAB V2 Standard classification taxonomy, Klazify navigates to the requested domain name or URL, gathers its content, and determines the most appropriate categories. These categories can then be used for 1-1 personalization, marketing segmentation, online filtering, and other purposes. As a result, a certain category can now be given to the URL or domain.
You should try Klazify to improve your cybersecurity! It won’t deceive you!