Detecting account compromise with SIEM
Detecting attacks related to compromised accounts with AI and other updates in Kaspersky SIEM.
82 articles
Detecting attacks related to compromised accounts with AI and other updates in Kaspersky SIEM.
Using anomalies in the behavior of users, devices, applications, and other entities to detect cyberthreats.
While open-source projects let you build almost any infosec solution, it’s crucial to realistically assess your team’s resources and the time it would take to achieve your goals.
How to estimate what and how much hardware will be needed for a SIEM system to assess the costs before deployment?
Rules for detecting atypical behavior in container infrastructure at the data collection stage, and other updates to our SIEM system.
Detection of techniques for disabling or modifying a local firewall, and other enhancements to the Kaspersky Unified Monitoring and Analysis Platform.
Medium-sized businesses increasingly find themselves on the receiving end of targeted attacks. What tools does one need when basic security proves inadequate?
We’re expanding the capabilities of the Kaspersky Unified Monitoring and Analysis SIEM system by adding new normalizers and correlation rules.
What’s new in Kaspersky Unified Monitoring and Analysis Platform 3.0.3.
How a threat-intelligence platform helps SOC analysts.
Using the Machine-Readable Threat Intelligence Platform fits well with our general position on security: multilayeredness everywhere.
Kaspersky SIEM got a set of correlation rules for detecting attempts to exploit vulnerabilities for authentication bypass in Fortinet products.
Why is it useful to attribute malware to a specific hacker group?
The top-10 risks of deploying autonomous AI agents, and our mitigation recommendations.
How to eliminate the threat posed to organizations by ownerless servers and services, outdated libraries, and insecure APIs.
Identifying threats to embedded devices, and how the updated Kaspersky Embedded Systems Security can help in tackling them?
Systematic measures and tools that organizations can use to defend against malicious browser extensions.
We examine how popular Canon printers could become a foothold for attackers within an organization’s network.
Our experts trained an ML model to detect attempts to use DLL hijacking, and integrated it into the Kaspersky SIEM system.