Deep Instinct

Deep Instinct extended its core deep learning model from endpoint prevention into Prevention for Applications, an agentless API scanner for cloud storage and SaaS, showing continued platform expansion beyond its original product.

The company's deep learning model is purpose-built for malware prevention rather than a generic classifier layered onto signature detection, and it now covers both endpoint and API-based scanning of files in transit through cloud apps.

Deep Instinct raised over $300M through 2021-2022 with BlackRock as lead investor, but no major funding round has been reported since, and Israeli tech press has reported staff reductions amid strategic shifts, suggesting momentum has cooled from its 2021-2022 peak.

Building a cybersecurity product around deep learning specifically, rather than shallow ML or heuristics, was a genuinely distinct architectural bet when Deep Instinct introduced it, though other vendors have since added deep learning components of their own.

A 100% prevention score in the 2022 MITRE Engenuity ATT&CK Evaluations for Enterprise, emulating Wizard Spider and Sandworm Team techniques across 30 vendors, is an independently administered, named benchmark result rather than a vendor-reported figure.

Prevention-first defense against ransomware and novel malware remains a core CISO priority, and extending that model to scan files moving through cloud storage and SaaS apps addresses a growing part of the modern attack surface.