Category: aiMSSP

XDR Threat Detection

XDR Threat Detection

Cyberattacks are becoming more sophisticated, distributed, and difficult to detect. Organizations today operate across endpoints, networks, cloud environments, applications, identities, email systems, and increasingly complex IoT and OT infrastructures. Each environment generates enormous amounts of security data, making it difficult for security teams to distinguish genuine threats from normal activity. Traditional cybersecurity tools can protect

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How Seceon aiEmail Closes the Gaps Legacy Filters Leave Open

How Seceon aiEmail Closes the Gaps Legacy Filters Leave Open

Across the first two posts in this series, we walked through why the two dominant email security architectures – the perimeter gateway and the post-delivery cloud AI plugin – each carry a structural blind spot, and four specific techniques (quishing, encrypted-archive abuse, free-webmail executive spoofing, and siloed alerting) that attackers use to operate inside those

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The Four Blind Spots Every Email Filter Shares – And Attackers Already Know Them

The Four Blind Spots Every Email Filter Shares – And Attackers Already Know Them

If you’ve read Part 1 of this series, you’ve seen the broad argument: the two dominant email security architectures were each built around an assumption that no longer holds. This post is about what that looks like in practice — four specific techniques attackers use today, each one aimed squarely at a gap that exists

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Top 10 SIEM Tools for 2026

Top 10 SIEM Tools for 2026

Security teams are managing an increasingly complex combination of cloud environments, endpoints, networks, identities, applications, APIs, and distributed infrastructure. Every part of this environment can generate security telemetry, creating enormous volumes of data that analysts must continuously monitor. Security Information and Event Management (SIEM) platforms help organizations bring this information together. Modern SIEM tools collect

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