We’re thrilled to announce our inclusion in the 2022 Gartner Magic Quadrant for Endpoint Protection Platforms (EPP).
As the only new vendor recognized in the Magic Quadrant for EPP last year, we believe our inclusion reinforces our position that the EPP status quo is ripe for disruption in a market that has over-rotated towards a reactive detection and response approach.
Deep Instinct’s innovative deep learning approach is filling a gap in the market to prevent unknown threats missed by other solutions. Our mission is to prevent-first and augment EDR solutions to reduce the overall events that need investigation, lower risk, and improve the lives of SOC teams everywhere.
With the continued climb in breaches, zero-days, and successful ransomware attacks, we believe EPP solutions must adopt a prevention-first mindset with proactive AI to turn the tides on bad actors.
The start of a revolution: Prevention-first
Deep Instinct takes a different approach to EPP: preventing unknown malware before it can get inside your environment, with the only native deep learning-based solution.
To underscore the need for a more proactive approach to cybersecurity you don’t have to look further than the IBM 2022 Cost of Data Breach Report
- The average cost of data breaches is now $4.35 million globally – up 2.6% from the previous year.
- The United States incurred the highest costs, with an average total of $9.44 million.
- 60% of businesses had to the increase in cost of their products in response.
The Unknowns and Assume Breach challenges
The industry is seeing ransomware and other threats continuing to increase is great part because today’s solutions are built to detect, not prevent, and are therefore too reactionary.
The focus over the last decade has been mainly focused on assume breach/detection-first and has not stopped attacks from succeeding. There are a few reasons to point to as an explanation:
- Attackers are learning new ways to evade the controls meant to stop them.
- Ransomware and zero-day attacks are being missed.
- Overworked and understaffed security teams have too many alerts to handle and triage.
- A high rate of false positives impacts a solution’s effectiveness.
- It takes too long to detect a threat and time is not on our side.
Case in point is the more recent XDR movement. While XDR has the amiable goal of a more integrated ecosystem, with more telemetry there will also be more data to sift through post detection, delaying decisions. This post-execution analysis will prove to be a challenge especially in a large enterprise. XDR will be useful for remediation and response, but not where the biggest problem lies – preventing the attack from getting inside in the first place.
The market is calling for greater protection and needs true prevention capabilities. Deep Instinct expects to see a shift in priorities as SOC organizations realize they can truly prevent more events to minimize business disruption and lighten their workload by reducing the need to chase alerts and react to false positives.
How Deep Instinct is changing outcomes with prevention-first
Deep Instinct is the only EPP vendor that is laser-focused on a prevention-first approach and the only vendor to natively develop a deep learning framework dedicated to cybersecurity. We believe our unique approach is the key to changing the game against attackers and providing dramatically different outcomes.
Deep Instinct is helping our customers combat these challenges:
- Prevent threats before they can fully execute and land inside your environment
- Prevent ransomware, zero day, and other unknown threats in <20ms
- Increase SOC efficiency by reducing false positives to <0.1%
- Improve SOC effectiveness with fewer events to react to
- Provide time to focus on what really matters to the organization
- Lower the volume of telemetry threat hunters must parse to string together related events
- Improve efficacy without relying on cloud checks for threat intelligence
- Lower total cost of ownership with reduced remediation efforts and minimal maintenance
Prevention-first outcomes
Unit 221B, a cybersecurity consultancy, tested and evaluated Deep Instinct’s claims. This team of ex-hackers and self-described skeptics put Deep Instinct through the wringer and came away with proof of the efficacy of the solution. Unit 221B validated Deep Instinct by several methods, including creating its own unique malware to bypass our prevention. The results speak for themselves.
“Deep Instinct was able to showcase why deep learning is a revolutionary technology for fighting and predicting the attacks of tomorrow, while maturing your security posture today.”
- Lance James, CEO, Unit 221B
Unit 221B Key findings include the following:
- 99.78% Accuracy - Deep Instinct exhibited a combined 99.78% accuracy rate for detection and prevention across unknown and custom attacks. Unit 221B tested Deep Instinct with a recommended configuration suitable for a mature customer’s hardened environment.
- 100% of Unknown Attacks - Deep Instinct successfully prevented 100% of unknown attacks and 96.4% of Unit 221B’s customized attacks.
- 60% Reduction - In events/alerts recorded to SIEM/EDR solutions with Deep Instinct installed compared to Microsoft Defender alone. This results in less strain on staffing and lowering of alert fatigue levels, allowing staff to be more focused on strategic and critical tasks such as patching and system hardening.
It’s time for a change.
Deep Instinct set out to drive better outcomes and improve security for organizations of all sizes as an agent on the endpoint or deployed with our REST API to protect file uploads.
The status quo reactionary approach is taking a toll on cybersecurity leaders and their staff with many thinking of leaving the industry altogether at a time when staffing shortages are growing worse. We must think differently about the problem if we expect different outcomes. Taking a prevention-first approach to stopping more attacks, earlier and faster, is possible due to Deep Instinct’s innovation steeped in deep learning.
The Only New Vendor
2022 Gartner Magic Quadrant for Endpoint Protection Platforms
Gartner, Magic Quadrant for Endpoint Protection Platforms, Peter Firstbrook, Chris Silva, 31 December 2022.
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