Defending Against AI-Powered Attackers

2026-06-24 · Source: Tomasz Tunguz · Field: Technology & Digital — Cybersecurity & Data Privacy, Artificial Intelligence & Machine Learning · Depth: Intermediate, quick

Summary

Office Hours will host Sunil Agrawal, CISO at Glean, on Thursday, July 9th at 9 AM Pacific / 12 PM Eastern, for a 15-minute online conversation on security readiness against AI-powered attackers. The discussion will cover how AI compresses the time needed to understand targets, map attack surfaces, and personalize initial moves. It will also address the disappearance of traditional attack indicators like grammar and tone, and the impact of deepfake calls and synthetic media on approval, payment, and trust control planes. The session emphasizes the need for security teams to develop new processes, tools, and organizational capabilities to respond effectively to model-driven attacks.

Key takeaway

For CISOs and security teams evaluating their defenses against evolving AI-powered threats, you must prioritize adapting your processes and tools to counter AI-accelerated attacks and synthetic media manipulation. Focus on developing new organizational muscle to respond at the pace of model-driven attacks, as traditional indicators are rapidly disappearing and trust control planes are shifting.

Key insights

AI significantly accelerates and obfuscates cyberattacks, demanding new security paradigms.

Principles

• AI reduces attack surface mapping and personalization time.
• Traditional attack indicators like grammar and tone are disappearing.
• Synthetic media alters trust and approval control planes.

In practice

• Anticipate AI's speed in attack surface mapping.
• Prepare for deepfake impact on approval workflows.
• Develop new security response capabilities.

Topics

• AI-powered Attacks
• Cybersecurity Readiness
• Deepfakes
• Synthetic Media
• Attack Surface Mapping
• Security Operations

Best for: AI Security Engineer, Security Engineer, CTO

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Editorial summary, takeaway, and curation by AIssential. Original article published by Tomasz Tunguz.