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American Focus > Blog > Tech and Science > What SOC tools miss at 2:13 AM: Gen AI attack chains exploit telemetry lag-Part 1
Tech and Science

What SOC tools miss at 2:13 AM: Gen AI attack chains exploit telemetry lag-Part 1

Last updated: May 10, 2025 1:05 pm
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What SOC tools miss at 2:13 AM: Gen AI attack chains exploit telemetry lag-Part 1
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Cybersecurity’s growing challenges: gen AI, insider threats, and CISO burnout

In the wee hours of a Sunday morning, the SOC teams find themselves facing a nightmare scenario. Attackers from across the globe are launching a coordinated assault on the company’s infrastructure. Exploiting unpatched endpoints and outdated security measures, they breach the perimeter within minutes.

The attackers, equipped with the skills of a nation-state cyber warfare team, target Active Directory to gain control of the network. Simultaneously, they deploy bot armies to steal sensitive data through an overlooked API. Alerts flood the SOC consoles, signaling a major breach in progress.

The CISO receives a call from the MDR provider, confirming the severity of the situation. It’s not an internal threat but a large-scale attack originating from Asia. The pressure mounts as the SOC team scrambles to contain the breach and mitigate the damage.

Generative AI emerges as a game-changer in the cybersecurity landscape, empowering attackers and defenders alike. Insider threats, fueled by job insecurity and economic uncertainty, pose a significant challenge to organizations. The burden falls on the CISO to navigate this complex terrain while combating burnout.

AI’s rapid advancement in cybersecurity presents both opportunities and risks. According to Gartner, a majority of organizations are deploying gen AI solutions, yet many struggle to manage AI-related risks effectively. Infrastructure security, security operations, and data security emerge as key areas for gen AI adoption.

Insider threats, driven by shadow AI and unsanctioned AI applications, demand a proactive response. Traditional rule-based detection models are no longer sufficient, prompting a shift towards gen AI-driven behavioral analytics. Leading vendors are innovating with AI-powered detection engines to identify and mitigate insider threats in real-time.

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As SOC teams race against time to thwart cyber attacks, integration and collaboration become crucial. Maximizing the value of existing security systems and streamlining alert management can enhance response capabilities. With attackers constantly evolving their tactics, organizations must adapt and innovate to stay ahead of the curve.

In conclusion, the cybersecurity landscape is evolving rapidly, driven by gen AI, insider threats, and increasing pressure on CISOs. By leveraging AI technologies effectively and fostering a culture of proactive security, organizations can strengthen their defenses against emerging threats.

TAGGED:AttackChainsExploitGenlagPartSOCtelemetrytools
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