Deep Instinct Prevention for Endpoints.
Deep Instinct’s proactive security approach improves your overall cybersecurity effectiveness and efficiency to reduce risk and lower overall TCO. With a uniquely architected deep-learning based solution we prevent >99% of unknown threats, like zero day and ransomware, before they execute and land inside your environment.
The Deep Instinct Advantage.
Speed. Scale. Efficacy.
To stay ahead of attacks, organizations need to stop threats faster — and with greater accuracy — without slowing down their business. Through the power of deep learning, Deep Instinct prevents >99% of known and unknown attacks, pre-execution.
Deep Instinct for Endpoint advantages:
- Extremely lightweight agent
- False positive rate <0.1%
- Eliminates frequent cloud checks and agent updates
- Maps to MITRE ATT&CK for faster investigations
- Improves compliance standards for GDPR, PCI, and CCPA
- Increases analyst productivity and efficiency to fight threats
- Lowers TCO and increases ROI of your entire security stack
- Provides extensive support across Windows, macOS, Android, ChromeOS, and Linux
Static and Dynamic Analysis.
Predict and Prevent: Pre-execution Static Analysis
Deep Instinct has pioneered the use of deep learning in cybersecurity to prevent an infection before malware executes on the endpoint. Deep Instinct prevents known and unknown malware, zero-day exploits, ransomware, and common script-based attacks faster and with fewer false positives compared to security tools that rely on signatures, heuristics, or basic machine learning.
Integration with SIEM, EDR, SOAR.
All prevented events are sent to the Deep Instinct console and malware is instantly classified to provide context to the attempted attack. From within the console organizations can enact a manual or automated response to achieve the following:
- Isolate the machine
- Update policy: allow & restore (Hash, Certificate, Folder, Script, Process)
- Terminate the process
- Clean the registry to remove persistence
- Send prevented events to a sandbox for further analysis