Check Point Harmony

Check Point Harmony uses a combination of Artificial Intelligence (AI) and Machine Learning (ML) techniques to detect email threats

Check Point Harmony Portal Showcasing the number of threats detected where the other leading email security solution deployed failed to detect threats

Checkpoint Harmony E1717059387142

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Check Point is configured in detection mode & will only report threat seen in your Microsoft 365 data (email, OneDrive, Teams (Channel) & SharePoint) or Google Workspace data (Gmail and Google Drive)

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    Following are the techniques that help Check Point Harmony to provide a robust and comprehensive defense against various email threats.

    Behavioral Analysis

    AI tools monitor email traffic and learn normal communication patterns. Phishing emails often deviate from these patterns, enabling AI to pick up on the anomaly.

    Natural Language Processing (NLP)

    NLP enables AI to read and understand the content of an email. With this understanding, AI can identify warning signs of phishing content, such as an attempt to create a sense of urgency or drive the recipient to click on a link or open an attachment.

    Attachment Analysis

    Infected attachments are a common method for delivering malware to a target computer. AI can be used in sandbox analysis to determine whether an attachment contains malicious content before allowing it to continue to its destination.

    Malicious URL Detection

    AI also has the ability to identify malicious sites linked to phishing emails. Once identifying a URL in an email, AI can analyze the indicated site to determine whether it is likely to be a phishing site.

    Threat Intelligence

    Organizations can subscribe to threat intelligence feeds to receive indicators of compromise (IoCs). AI can use these IoCs to identify malicious attachments, URLs, and phishing campaigns or can generate its own based on newly detected phishing campaigns.

    Machine Learning Algorithms

    Harmony Email & Collaboration intercepts attackers using machine-learning algorithms, which analyze user behavior and feed off sources like mobile and endpoint on-device detection of OS exploits, malware and network attacks, SaaS native APIs, and Check Point’s ThreatCloud.

    Threat Emulation

    Check Point’s advanced sandbox (Threat Emulation) is used to detect the evasive zero-day malware.

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