Under the hood: what artificial intelligence looks like on the terminal


In light of a recent Cybereason research report, Organizations at Risk: Ransomware Attackers Don’t Take Holidays, regarding the prevalence of ransomware attacks that occur during off-peak hours, it is imperative that we turn to solutions. robust AI security systems, so you can know your organization is protected even when none of your employees are online.

An effective defense against the global ransomware problem is much more than just a technological problem. At its highest level, the fight against ransomware is a race against time. From the moment an attacker enters your environment, it stays there for as long as needed by engaging in subtle but detectable activity long before you encrypt any of your data.

The reason is that ransomware is financially motivated, which means attackers want to exfiltrate enough sensitive information and infiltrate as many systems as possible in order to demand the highest possible ransom, making their attack operations very methodical and intentional.

Predictive Ransomware Protection, a revolutionary AI-powered endpoint protection solution, detects attacks from early stages in real time by bringing artificial intelligence to every endpoint.

For your organization to effectively defend against complex ransomware (or RansomOps) attacks, sophisticated and artificially intelligent endpoints are needed. An effective solution uses a combination of AI-powered NGAV engines and file manipulation detection.

AI powered NGAV engines

It’s no secret that the old AV no longer holds. Ransomware attackers themselves use artificial intelligence and highly sophisticated tools to automate certain aspects of their attacks, and new strains of ransomware or repackaged binaries are continually being developed, rendering traditional antivirus solutions useless.

The next-generation antivirus goes beyond just monitoring known Indicators of Compromise (IOCs) to detect Behavior Indicator-based (BIO) attacks, the most subtle chains of potentially malicious behavior.

This is essential because today’s complex RansomOps, as mentioned above, are multifaceted operations that take place in distinct phases that only AI-based behavioral analysis solutions like NGAV can prevent and detect at the start of the attack chain.

NGAV includes multiple layers of protection to deal with each of the following types of threats:

    • Known and unknown malware
    • Polymorphic and repackaged malware
    • Ransomware
    • Fileless malware, out-of-territory and in-memory attacks
    • Zero-Days and Exploits Kits
    • Other advanced techniques

All strains of ransomware are forms of malware (however, not all malware is ransomware); Highly effective malware prevention, such as that provided by AI-powered NGAV engines, has proven to be a formidable preventative control against unseen and unseen strains of ransomware.

File manipulation detection

In some new cases, attackers will be able to bypass the advanced NGAV’s multi-layered defenses. When an attacker is able to go far enough in their campaign to begin performing encryption, it is important that a solution provides built-in security to prevent large-scale encryption and thus eliminate the attacker’s ability to demand a ransom.

File manipulation detection provides a way to predict and respond to an attack before it spreads enough to disrupt business operations. This technique scans files at the kernel level, under the operating system, so that it can detect the initiation of the process of encrypting a file at the most fundamental level.

With this deep visibility extending down to the binary level of each file, machine learning algorithms offer a combination of new and sophisticated techniques such as natural language detection, binary similarity analysis and identification of changes. extension and other advanced approaches to combat encryption.

By evaluating the structural makeup of document content, Natural Language Detection identifies when sentences written in a file become scrambled, indicating the first signs of encryption.

Binary similarity analysis exploits a technique known as fuzzy matching, which means that it calculates a significant level of difference between the contents of files that helps identify malicious tampering. Binary-level file monitoring allows this scan to detect when file contents are randomized, indicating malicious activity.

Modern cybersecurity solutions, such as Predictive Ransomware Protection, offer a significant advantage over other endpoint protection approaches by using global file manipulation detection to protect local and network files. Solutions that cannot deliver artificial intelligence to the endpoint leave an organization vulnerable to mass encryption. With visibility at the kernel level, a large-scale ransomware attack can be predicted and prevented, ensuring that business operations can continue without disruption.

Cybereason Predictive Ransomware Protection is unmatched in the industry, which is why Cybereason remains undefeated in the fight against ransomware. Learn more about ransomware defense here or schedule a demo today to see how your organization can go undefeated.


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