Phishing attackers often use well-known brands, such as Microsoft and Apple, to deceive employees into divulging their login credentials and other sensitive data. Phishing sites based on these brands are prolific, with hundreds of thousands of new phishing sites appearing each month. AI-assisted attacks enable cybercriminals to rapidly create spoof sites that appear identical to the real ones. A DNS filter is used to prevent employees and others from navigating to these malicious websites.
When someone navigates to a website, they enter a domain name, such as www.thecompany.com. However, this name is not machine-readable. Instead, a service called the Domain Name System (DNS), often referred to as the internet’s phonebook, translates the domain name into machine-readable numbers, such as 168.62.128.16. This system is the basis for the security provided by a DNS filter. A DNS filter intercepts the DNS query process, checking to see if the queried website is on an allowed or blocked list.
A DNS filter is used to:
Prevent employees and others from navigating to malicious websites.
Reduces the chance of a malware or ransomware infection.
Prevents access to unsanctioned websites.
Protects company reputation and avoids legal risk by preventing access to hate, gambling, and adult sites.
Improves productivity.
Improves network performance.
Phishing attacks are becoming increasingly successful with the help of AI, which is empowering attackers with speed, agility, believability, and scalability. Cyber criminals use AI to craft persuasive phishing emails and corresponding phishing websites. Spoof websites can be created quickly and multiple and dynamic domain addresses can be generated. The dynamic and rapid nature of phishing websites makes it challenging for conventional DNS filters to keep pace with the changes.
The existential threat posed by AI requires a proactive and dynamic response. Conventional DNS filters utilize static blocklists based on manually configured policy lists, which are not dynamic enough to effectively handle AI-assisted phishing threats. Advanced DNS filtering utilizes AI to fight AI. Advanced DNS filtering uses machine learning algorithms, trained on avast corpus of data points. Machine learning utilizes its training to identify emerging attack patterns and signals, enabling it to spot potentially malicious or unsanctioned websites. The DNS filter uses this intelligence to build category lists of suspicious websites. A human operator can work with the intelligence to fine-tune the blocklist.
A RESTful API allows deep integration into existing environments. A centralized dashboard enables authenticated administrators to onboard and manage customers and locations, as well as create and manage blocklists and allowlists.
Employees must be protected whether they work from home, in the office, or travel. DNS queries must be routed through the DNS filter, even off-network. The filter must work on guest Wi-Fi to cover remote and travelling workers.
Scales to accommodate all sizes of organizations, from small businesses to large enterprises.
A cloud-based DNS filter enables fast deployment and straightforward ongoing management.
Used to streamline reporting on a per-user basis.
Comprehensive and granular reporting from a centralized dashboard.
Set policies and enforce on a per-user, per-IP, per-agent, and per-group basis.
Machine learning algorithms are trained on a vast corpus of threat data that powers the AI with the intelligence to identify emerging threats. Continuous sampling ensures that the training data is current and reflects the state of the threat landscape.
DNS queries are processed in real-time to identify malicious content and prevent navigation to dangerous sites.
AI is used to generate a domain classification database. Categories include ad fraud, botnets, malware distribution, spam, phishing, cryptocurrency mining, and other malicious activities. Administrators can choose to block or restrict identified sites.
Cybercriminals often use C2C to send stolen data and information to a hacker. AI can help identify malicious C2C traffic that uses DNS to alert a security team of an ongoing or impending attack.
The AI must be able to differentiate threat metrics at the URL, domain, and path levels.
Malicious URLs are constantly evolving and changing. AI-powered DNS filtering solutions must be able to rapidly inspect and detect URLs to check if the malicious category persists. Policies should be set to test malicious URLs on a set schedule.
Combined with phishing simulations, educates and empowers users to prevent cyberattacks. Emails that slip through the net can be identified by the recipient and reported before they become an incident.
Advanced email security uses machine learning and natural language processing (NLP) to detect and prevent phishing emails. DNS filters and ICES are complementary solutions.
Secure email backup enables the fast and accurate recovery of emails and attachments in the event of a disaster, for example, during a ransomware attack. Email backup is essential for business continuity and disaster recovery.
A centralized, cloud-based console that lets MSPs manage all customers in one place, reducing administrative overhead.
Fast, automated onboarding to quickly add new accounts without manual complexity.
Seamless bundling withMicrosoft 365, Azure Blob, and Entra ID to increase value and margins.
