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Silicon Flash > Blog > AI > Uncovering the Vulnerabilities: How Gen AI Attack Chains Exploit Telemetry Lag – Part 1
AI

Uncovering the Vulnerabilities: How Gen AI Attack Chains Exploit Telemetry Lag – Part 1

Published May 9, 2025 By Juwan Chacko
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Uncovering the Vulnerabilities: How Gen AI Attack Chains Exploit Telemetry Lag – Part 1
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In the wee hours of a Sunday morning, the worst nightmares of SOC teams are about to unfold. A full-scale attack is underway on a company’s infrastructure by attackers located on the other side of the globe. Exploiting multiple unpatched endpoints that haven’t been updated since 2022, the attackers breached the company’s perimeter in less than a minute.

With the skills of a nation-state team, the attackers are targeting Active Directory to gain control of the entire network, creating new admin-level privileges to prevent shutdown attempts. Simultaneously, other members of the attack team are deploying bots to extract massive amounts of customer, employee, and financial data through an API left enabled after the last major product release.

Alerts are flooding the SOC consoles, reminiscent of a high-paced video game, while SOC analysts are jolted awake from their sleep by their cell phones. The CISO receives a call around 2:35 a.m. from the company’s MDR provider, alerting them to a significant breach originating from Asia.

The rise of generative AI has introduced new challenges in the cybersecurity landscape, including insider threats fueled by job insecurity and inflation. These pressing issues, coupled with the rapid evolution of AI security, have placed a heavy burden on CISOs, leading to increased burnout among these professionals.

According to Gartner, a significant percentage of organizations are already implementing gen AI solutions, but many security leaders admit to gaps in effectively managing AI risks. Gen AI is predominantly deployed in infrastructure security, security operations, and data security, with a focus on improving cybersecurity and reducing risks as demanded by boards of directors.

See also  The Power of Machine Learning in Deception Detection: Uncovering the Truth

Insider threats have become more autonomous and insidious due to the proliferation of AI technologies. Shadow AI poses a significant challenge for CISOs, as employees unknowingly adopt unsanctioned AI solutions that can compromise security. Traditional rule-based detection models are no longer sufficient, prompting leading security teams to adopt gen AI-driven behavioral analytics for real-time threat identification and containment.

Vendors like Prompt Security, Proofpoint Insider Threat Management, Varonis, and Microsoft Purview Insider Risk Management are at the forefront of innovating AI-powered detection engines to mitigate insider threats effectively.

As SOC teams combat evolving cyber threats, integration of systems and optimization of existing security measures are crucial to effectively respond to attacks. With attackers leveraging gen AI to refine their tactics, businesses must enhance their cybersecurity strategies and adapt to the changing threat landscape to stay ahead of adversaries.

TAGGED: attack, Chains, Exploit, Gen, Lag, part, Telemetry, Uncovering, Vulnerabilities
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