How to Prevent Zero Day Attacks

Zero-day attacks are unknown threats that easily circumvent signature-based security solutions and therefore pose an exceptionally dangerous risk to businesses. In this article we will explore how Check Point uses artificial intelligence and machine learning to prevent these attacks.

What is Zero-Day Attack?

Zero-day attacks are attacks that exploit recently-discovered vulnerabilities for which no patch is available. By attacking on “day zero”, a cybercriminal decreases the probability that an organization will be able to detect and respond appropriately.

Many organizations’ security models are based on detection, which requires the ability to identify an attack as malicious. With the novel exploits used in zero-day attacks, security based on signature detection is completely ineffective because the required signatures have not yet been developed.

Therefore, managing the risk of zero day attacks requires prevention, not just detection.

How to Prevent Zero Day Attacks

Preventing zero day attacks is a multistage process. Organizations need the threat intelligence required to identify a potential campaign, tools for acting on this intelligence, and a unified platform that supports rapid, coordinated threat response.

• Threat Intelligence Platforms
  Modern cyberattacks are widespread and automated. A zero day attack will target many different organizations, taking advantage of the narrow window between vulnerability discovery and patch release.

Protecting against this type of large-scale attack requires access to high-quality threat intelligence. As one organization experiences an attack, the data that it collects can be invaluable for other organizations attempting to detect and block the attack. However, the speed and volume of modern attack campaigns makes manual threat intelligence sharing too slow to be effective.

Check Point’s ThreatCloud AI is the world’s largest cyber threat intelligence database. ThreatCloud AI leverages artificial intelligence (AI) to distill the data provided to it into valuable insights regarding potential attacks and unknown vulnerabilities. Analysis of over 86 billion daily transactions from more than 100,000 Check Point customers provides the visibility required to identify zero day attack campaigns.

• Threat Prevention Engines
  Threat intelligence provides the information required to effectively detect zero day attacks. Protecting against them requires solutions that can translate this intelligence into actions that prevent the attack from succeeding.

Check Point has developed over sixty threat prevention engines that leverage ThreatCloud AI’s threat intelligence for zero day prevention. Some key threat prevention capabilities include:

• CPU Level Inspection:
  Cyberattackers commonly use return oriented programming (ROP) to bypass defenses built into CPUs. CPU level inspection identifies attempts to overcome executable space protection and code signing, blocking the attack before malicious code can be downloaded and executed.

  • Threat Emulation and Extraction:
    Analysis of suspicious content within a sandboxed environment can help to detect malware before it is delivered to a target system. This enables the malware to be blocked or malicious content to be excised from a document before delivery.

  • Malware DNA Analysis:
    Malware authors commonly build on, borrow from, and tweak their existing code to develop new attack campaigns. This means that novel exploits often include behavior and code from previous campaigns, which can be used to detect the newest variation of the attack.

  • Anti-Bot and Anti-Exploit:
    Modern cyberattacks often rely heavily upon compromised machines being used as part of a botnet. After identifying a compromised machine, an organization can isolate it and block bot-related traffic to stop the spread of the malware.

  • Campaign Hunting:
    Malware is reliant upon the attacker’s backend infrastructure for command and control. Using threat emulation and extraction, Check Point can identify new command and control domains used by malware and leverage this information to detect other instances of the attack campaign.

  • ID Guard:
    Account takeover attacks have become increasingly common with the growing use of Software as a Service (SaaS) applications. Behavioral analysis and anomaly detection can identify and block attempted attacks even if the attacker has the correct credentials.

• Security Consolidation
  Many organizations are reliant upon a wide array of standalone and disconnected security solutions. While these solutions may be effective at protecting against a particular threat, they decrease the effectiveness of an organization’s security team by overwhelming them with data and forcing them to configure, monitor, and manage many different solutions. As a result, overworked security personnel overlook critical alerts.

A unified security platform is essential to preventing zero-day attacks. A single solution with visibility and control across an organization’s entire IT ecosystem has the context and insight required to identify a distributed cyberattack. Additionally, the ability to perform coordinated, automated responses across an organization’s entire infrastructure is essential to preventing fast-paced zero-day attack campaigns.

Protecting Against Zero Day Attacks with Check Point

Check Point’s prevention-first approach is the only way to effectively protect against unknown threats. Legacy solutions that rely upon incident detection and response miss novel attacks and respond too late to minimize the damage of a cyberattack campaign.

A crucial first step in preventing cyberattacks is identifying vulnerabilities within your network, which is why Check Point offers a free security checkup service. To learn more about preventing novel cyberattacks using artificial intelligence, check out this whitepaper.