In the face of complex and sophisticated cyber threats, enterprises struggle to stay ahead. Addressing this core challenge, Check Point introduces ThreatCloud Graph, focused on proactive prevention of emerging threats.
This groundbreaking feature within ThreatCloud AI, the brain behind all of Check Point´s products, offers a novel approach to cyber security.
Contextualizing ThreatCloud Graph within ThreatCloud AI. Check Point leverages AI technology extensively in its cybersecurity solutions.
ThreatCloud AI, the backbone of Check Point's security infrastructure, uses over 40 AI engines to process and analyze massive amounts of data.
With ThreatCloud Graph, Check Point extends these capabilities to analyze the complex web of relationships between digital entities, offering a multi-dimensional perspective on cyber threats.
ThreatCloud Graph is tailored for enterprise needs, addressing the increasing complexity and sophistication of cyber attacks.
Proactive Zero-Day Threat Prevention: Utilizing ThreatCloud AI's knowledge to identify and mitigate emerging threats.
ThreatCloud Graph delves into the interconnected web of relationships between these entities, unveiling a multi-dimensional perspective on cyber threats.
Traditionally, threats have been identified based on malicious content detected by However, ThreatCloud Graph recognizes that threats never operate in isolation: they are part of larger networks and campaigns, often traceable to entities like name servers and registrars.
By highlighting relationships between URLs, IPs, name servers, and more, ThreatCloud Graph identifies patterns and links common entities, allowing the prevention of zero-day threats even in the absence of detected malicious content.
One of the key features of ThreatCloud Graph is its ability to store and index the entire threat landscape within a graph database.
ThreatCloud Graph introduces a holistic perspective on threat indicators, shifting from a single Indicator of Compromise to a multi-dimensional view based on attack patterns.
By leveraging ThreatCloud AI's powerful knowledge of attack patterns, ThreatCloud Graph aims to prevent zero-day IOCs, such as URLs, domains, and Ips, by establishing their reputation through relations to previously known malicious artifacts.
The working mechanism of ThreatCloud Graph involves analyzing the relationships of URLs with domain hosts.
ThreatCloud Graph can identify potential threats by examining the shared relations of known malicious domains.
An illustrative example of the ThreatCloud graph capability is the recent prevention of a phishing campaign targeting 'Telegram'.
ThreatCloud's proactive analysis of registered domains combined with the new ThreatCloud Graph capability within ThreatCloud AI, enabled us to identify this campaign as malicious, long before the domains became active and before other security vendors categorized the domains as malicious.
ThreatCloud Graph is ideal for enterprises due to its multi-dimensional approach to cybersecurity.
Its integration with ThreatCloud AI's extensive knowledge base allows for the proactive prevention of emerging threats, including zero-day attacks.
This makes ThreatCloud Graph a powerful tool in an enterprise's cybersecurity arsenal, offering advanced, AI-driven protection in an increasingly complex threat landscape.
This Cyber News was published on blog.checkpoint.com. Publication date: Thu, 21 Dec 2023 17:13:05 +0000