- Cloud / On-Premise
- Online / Offline
Using deep learning, Deep Instinct offers a predictive threat prevention platform. The multi-layer protection is provisioned across pre, on, and post-execution stages. It is based on a prevention first approach, followed by detection & response, automatic analysis and remediation.
Unlike detection and response based cybersecurity solutions, which wait for the execution of the attack to react, our advanced preventative approach proactively keeps our customers protected by preventing the attack from entering and causing any damage.
Learn more about advanced malware prevention vs. detection
Predict & Prevent
Detect & Automatically Respond
Automatically Analyze & Remediate
By using deep learning, we are able to predict and prevent any kind of threat – known and unknown – anywhere in zero-time. Every endpoint, server, mobile device, network and operating system is protected against any type of attack, be it fileless or file-based. This advanced approach to threat prevention ensures that attacks are identified and blocked before any damage can be caused.
Email attachments are scanned whenever they are accessed and files are scanned when they are accessed from removable devices.
Yes,all you need to do is define the Syslog Server from the General Configuration screen (Settings > General Configuration), and select which type of events are send to the Syslog Server from the Event Notification screen (Settings > Notification).
Deep Instinct delivers an endpoint protection solution that saves your time and money.
For each event, many insights are gathered that provides a big picture of the malicious event and save you time by not requiring you to run the threats under a different platform such as a sandbox.
Deep Classification saves you even more time by providing an understanding of the kind of malware prevented.
No threat hunting operations are needed.
D-Client is unobtrusive in terms of endpoint system resources and updates are seamless, requiring no reboots.
Management Console is web-based and provides an intuitive and informative view of your complete system.
The training process using deep learning is used to train the prediction model (D-Brain). This process includes many legitimate files from all over the world (from trusted vendors, small vendors, and from many aspects). Using such diversity for the benign training set, combined with deep learning, our false positive rate is extremely low.
Deep Instinct also provides a service for intelligence and malware analysis research. This service provides a detailed analysis to better understand whether a file is malicious or a false positive, which is performed by Deep Instinct Threat Intelligence Team.
Whitelists and blacklists can easily be imported into the cybersecurity solution from the Management Console. Open the relevant whitelist or blacklist and click Import CSV to import your list.
When an event occurs, detailed event reports are generated, which is displayed on the Event Detail screen. Here you will find a significant amount of file information including file hash, file path, Deep Classification of the file (to which malware type the file belongs), static analysis, sandbox analysis (what could happen if you run the file), process chain for the execution of the file, and general information about the device affected (such as device name, user name, IP & MAC addresses, etc.)