Dark Reading is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Operational Security

// // //
9/18/2017
02:47 PM
Simon Marshall
Simon Marshall
Simon Marshall

Vigilance Brings Machines & Humans Together to Defeat Threats

Vigilance, from SentinelOne, ties the strengths of humans and machines together in a threat-resolution system.

People and machines together can be greater than the sum of their parts, and this is exemplified by SentinelOne, a Silicon Valley-based firm that secures endpoints, datacenters and the cloud.

Vigilance is the name of the game, and also happens to be the name of SentinelOne's new service, based on its existing endpoint security platform, which augments the power of computer threat detection with a team of human analysts and researchers based in Mountain View and Tel Aviv.

The platform detects the threats. The humans examine, discuss and then respond to them. Simple.

According to SentinelOne this is an optimal arrangement where detection, prioritization and responses are accelerated because there are more bodies and know-how on the job, apparently thereby reducing corporate risk. The Vigilance service provides the elasticity to call on additional eyeballs during a high threat period, or to provide more expertise in security analysis and research than might be found in a single enterprise team instance.

There's a strong reliance from the Vigilance team on the platform to provide primary threat information -- to be the eyes and ears -- and for the analysts and researchers to be the brains. "The service ingests threat information from the agent detection, and 80% to 90% of the analysts' tasks are based on that information," said Eran Ashkenazi, VP of services and field operations for SentinelOne.

Oddly enough, the more problems the SentinelOne platform needs to handle, the better. It learns how to handle unique incidents and then that knowledge is propagated to SentinelOne's entire customer base, theoretically lessening the impact a new threat can have and spreading the benefits. At the 50,000ft level, the platform's main role is to differentiate between false and true positives, and then hand off that information to the human team. But what happens if the humans then make mistakes?

"There are several safeguards, but in short if there is a doubt, issues will be escalated to a second tier of malware researchers or reverses, or we'll interact with the customer to learn more or get the actual file or payload," Ashkenazi told SecurityNow.


Want to learn more about the tech and business cases for deploying virtualized solutions in the cable network? Join us in Denver on October 18 for Light Reading's Virtualizing the Cable Architecture event – a free breakfast panel at SCTE/ISBE's Cable-Tec Expo featuring speakers from Comcast and Charter.

An interesting aspect of the service is the ability for enterprise security teams to bring online extra personnel when they're needed. In some cases, those companies may simply have underestimated how many members of a team are needed to handle threats. But also, the sheer number of tools out there can cause headaches too.

"There are simply too many solutions to manage, and an average security team needs to probably deal with dozens of different platforms and dashboards," said Ashkenazi. "[Plus] the endpoint was for many years considered to be something that just works, which we [now] know is not the case."

In the last five years, endpoint protection, and endpoint detection and response, platforms have become more resource-intensive as the range and number of attack vectors increases. Like bacteria on a petri dish, the threats multiply in number and diversity until the whole lab is crawling with infectious organisms. Yet the number of scientists and technicians remains the same.

In SentinelOne's lab, they're looking next to incorporate AI into the platform, once deep visibility capabilities have nee incorporated, proving more data into the Vigilance service, enabling proactive hunting capabilities, and making the security stance of the platform more proactive.

Related posts:

— Simon Marshall, Technology Journalist, special to Security Now

Comment  | 
Print  | 
More Insights
Comments
Newest First  |  Oldest First  |  Threaded View
Edge-DRsplash-10-edge-articles
I Smell a RAT! New Cybersecurity Threats for the Crypto Industry
David Trepp, Partner, IT Assurance with accounting and advisory firm BPM LLP,  7/9/2021
News
Attacks on Kaseya Servers Led to Ransomware in Less Than 2 Hours
Robert Lemos, Contributing Writer,  7/7/2021
Commentary
It's in the Game (but It Shouldn't Be)
Tal Memran, Cybersecurity Expert, CYE,  7/9/2021
Register for Dark Reading Newsletters
White Papers
Video
Cartoon
Current Issue
How Machine Learning, AI & Deep Learning Improve Cybersecurity
Machine intelligence is influencing all aspects of cybersecurity. Organizations are implementing AI-based security to analyze event data using ML models that identify attack patterns and increase automation. Before security teams can take advantage of AI and ML tools, they need to know what is possible. This report covers: -How to assess the vendor's AI/ML claims -Defining success criteria for AI/ML implementations -Challenges when implementing AI
Flash Poll
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2022-3296
PUBLISHED: 2022-09-25
Stack-based Buffer Overflow in GitHub repository vim/vim prior to 9.0.0577.
CVE-2022-41340
PUBLISHED: 2022-09-24
The secp256k1-js package before 1.1.0 for Node.js implements ECDSA without required r and s validation, leading to signature forgery.
CVE-2022-23463
PUBLISHED: 2022-09-24
Nepxion Discovery is a solution for Spring Cloud. Discover is vulnerable to SpEL Injection in discovery-commons. DiscoveryExpressionResolver’s eval method is evaluating expression with a StandardEvaluationContext, allowing the expression to reach and interact with Java classes suc...
CVE-2022-23464
PUBLISHED: 2022-09-24
Nepxion Discovery is a solution for Spring Cloud. Discovery is vulnerable to a potential Server-Side Request Forgery (SSRF). RouterResourceImpl uses RestTemplate’s getForEntity to retrieve the contents of a URL containing user-controlled input, potentially resulting in Information...
CVE-2022-23461
PUBLISHED: 2022-09-24
Jodit Editor is a WYSIWYG editor written in pure TypeScript without the use of additional libraries. Jodit Editor is vulnerable to XSS attacks when pasting specially constructed input. This issue has not been fully patched. There are no known workarounds.