Kaspersky Updates AI Features in Threat Intelligence Products, Simplifying Analysis With AI Summaries
TECHWORLD ·
✦ AI Summary
Kaspersky announced an update to the Kaspersky Threat Intelligence Portal on the 26th.
The update includes an AI-powered summary feature and support for the Model Context Protocol (MCP) for integration with external AI applications.
It will help SOC and threat analysts better understand large-scale threat intelligence, automate open-source intelligence searches, and enable access to real-time threat data.
As the threat posed by AI-powered cyberattacks accelerates, security teams continue to struggle to secure the time and expertise they need. Against this backdrop, Kaspersky has integrated AI features into its threat intelligence product line.
On the 26th, Kaspersky announced an update to the Kaspersky Threat Intelligence Portal. The update centers on two scalability-focused elements and includes support for an AI-powered summary feature as well as support for the Model Context Protocol (MCP) for integration with external AI applications.
This will allow customers to improve the efficiency of using Kaspersky Threat Intelligence, which is based on more than 25 PB of the company's own threat data. It will also automate open-source intelligence (OSINT) searches and help secure additional information related to potential security threats.
The update is intended to help SOC and threat analysts quickly understand and analyze threat intelligence at scale, and it is designed to help analysts rapidly grasp large volumes of human-readable threat data. It also makes it possible to use Kaspersky Threat Intelligence services in external AI-based applications.
The update also provides an AI summary feature. This feature helps reduce the time needed to review complex reports during ongoing security investigations, threat hunting, and tracking of threat actors and attack campaigns, allowing analysts to see concise summaries of vast amounts of data with a single click using the new AI summary feature.
The summary feature works by automatically processing available information and helps identify useful information such as indicators of compromise and detection rules. This significantly reduces the amount of information that analysts must review manually when examining each indicator of compromise, and helps analysts decide within minutes which items warrant deeper investigation.
Kaspersky said it deliberately selects the source data used to generate each summary block. This is a design choice intended to shorten review time while preserving the context needed to evaluate the information presented. The feature can also be applied to AI summary functions for indicators of compromise identified through open-source intelligence searches, as well as to search functions for indicators of compromise identified through open-source intelligence searches. This allows analysts to review the full data related to a search target, prioritize data related to that target, and understand the full picture by focusing on highly relevant information.
Kaspersky also supports the Model Context Protocol (MCP) for external AI integration. As a result, companies can connect their in-house AI applications directly to the Kaspersky Threat Intelligence Portal, and external AI applications can also connect directly to the Kaspersky Threat Intelligence Portal. Unlike existing APIs, which process requests according to predefined methods, MCP connections allow AI models to request data flexibly and dynamically according to their needs and access external threat data.
The company explained that enterprise AI applications can access Kaspersky global threat intelligence in real time. It added that this real-time access can be used to build intelligent automation workflows and enable threat analysis tailored to changing needs.
Alexander Maziukin, head of Kaspersky's threat intelligence product line, said the core value of the new AI features lies in reducing the time between receiving information and understanding what action is needed. He said the ultimate effects include maximizing the efficiency of companies' threat intelligence investments, reducing the time spent on complex analysis, and significantly improving the accuracy of security operations workflows.
Source: TECHWORLD · Kim Hye-jin
Original: https://www.epnc.co.kr/news/articleView.html?idxno=408731
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Source: TECHWORLD
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