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Debunking Common Myths About XDR
XDR reduces the time it takes to detect, investigate and respond to attacks; improves performance, security
Security challenges are growing for organizations as agile, well-funded, and sophisticated adversaries find new ways to compromise networks, underscoring the importance of automation and end point protection to fortify the ecosystem.
Today’s attacks have progressed into live scripts, direct live attacks, or use existing administrative tools on machines to compromise networks. To fill in the security gaps, many agencies have embraced a complex stack of technology equipment that is difficult to manage.
“The challenge is you wind up with a ton of different systems, all generating alerts, but they are not talking to each other,” said Jared Phipps, SVP of Worldwide Sales Engineering at SentinelOne. “So now it’s on the human response team to figure out what those different puzzle pieces are and try to reassemble the puzzle and react to it faster than a breach can occur.”
Agencies have put an increased emphasis on Endpoint Detection and Response (EDR) solutions to help them more proactively detect and respond to cyberthreats; however, many are still rely on “a time- and manually-intensive process,” he said.
With more automation, organizations can make better use of EDR solutions to protect against ransomware, rapidly contain threats, accelerate resolution and remediation, and provide broad platform support, among other tasks.
EDR lays the foundation for an emerging cloud-native technology dubbed Extended Detection Response (XDR), which is a solution that uses AI and automation to help organizations address cybersecurity from a unified standpoint.
Cloud transformation has created cybersecurity blind spots and organizations don’t have enough time to triage and respond to alerts at scale. Siloed tools are leading to missed detections and slower responses.
XDR allows them to pull data from all products, automate a storyline of what is happening, and respond faster.
“We need to start thinking of this in terms of AI and automation because the attackers are doing the same thing to rapidly speed up their target acquisition,” Phipps said. “If we are not ready to deflect those attacks, we will see our risk increasing at an even higher rate.”
XDR cannot exist without a solid EDR foundation, he said, because the devices on the endpoint are the targets for attack. “What we are looking to do is take vital non-endpoint telemetry and fuse that with the endpoint telemetry.”
That will help organizations to turn three to four billions of telemetry events into six actionable events over three months, which is what SentinelOne has achieved with its Fortune 10 customers. “That is a real use case about deflecting alert fatigue,” Phipps said.
XDR does not replace Security Information and Event Management (SIEM), but rather augments it, he said. XDR is threat-centric, cloud native, and has an open and flexible architecture. “Where you need to script out your playbooks, you will keep your SOAR automations at the SIEM level.”
XDR takes the “instantaneous response motion” beyond the endpoints to focus on the other products that are sustained by the product vendors, not by the customer, he added.
XDR relies on automation, but keeps humans in the loop, helps them synthesize data to speed decision making, and reduces costs. “Automation takes away so much noise and pain that you are now in the driver’s seat,” Phipps said.
However, more data doesn’t always mean better results, and data lakes can often turn into data swamps. Data ingestion is difficult and data storage and transport are expensive. XDR, however, should help an agency democratize its data.
SentinelOne’s Singularity XDR data analytics platform operates at speed and scale, offers complete visibility into data from many sources, and provides cross-stack correlation of data as well as built-in integrations. It also automates and orchestrates unified response and remediation, and offers one console for prioritized alerts and response.
“We are taking automation and AI to synthesize large amounts of data, ingesting unstructured data from multiple sources, and congesting that into a single streamlined story event,” he said.
This content is made possible by our sponsor SentinelOne. The editorial staff was not involved in its preparation.
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