2026 ZKast #153 - AI vs. AI Cyber Attacks: How Frontier Models Change SecOps | Zscaler at BlackHat
Published August 20, 2026
At a glance
Views
36,887
Likes
1
Comments
0
Performance vs. channel
All-time outlier score
Engagement rate
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About
At Black Hat 2026, Zeus Kerravala (ZK Research) sits down with Deepen Desai, EVP of Cybersecurity at Zscaler, to discuss the sudden rise of agentic AI in cybersecurity and how frontier models are fundamentally altering threat landscapes. Deepen shares findings from Zscaler Threat Labs' testing on frontier models lik…
- Published
- August 20, 2026
- Made for kids
- No
More features coming
We're working on new analytics and tools. Stay tuned.
How 2026 ZKast #153 - AI vs. AI Cyber Attacks: How Frontier Models Change SecOps | Zscaler at BlackHat is doing
It has 36.8K views in total. It ranks #13,280,020 among tracked YouTube videos by views.
Key facts about 2026 ZKast #153 - AI vs. AI Cyber Attacks: How Frontier Models Change SecOps | Zscaler at BlackHat
- Total views
- 36.8K
- Total likes
- 1
- Total comments
- 0
- Published
- August 20, 2026
- Global rank by views
- #13,280,020
Frequently asked questions
How many views does 2026 ZKast #153 - AI vs. AI Cyber Attacks: How Frontier Models Change SecOps | Zscaler at BlackHat have?
2026 ZKast #153 - AI vs. AI Cyber Attacks: How Frontier Models Change SecOps | Zscaler at BlackHat has 36,887 views, 1 likes, ranking #13,280,020 among tracked YouTube videos by views.
How accurate are these YouTube video analytics?
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What is the outlier score?
How this video's views compare to the channel's usual Shorts or long-form video. A 2x score means double the usual views for that channel, 0.5x means half.
What is engagement rate and how is it calculated?
Likes and comments per view, compared to this channel's typical engagement rate — shown as above or below what's usual for the channel.
How is the revenue estimate calculated?
It's a rough public estimate based on a $0.7–$2.0 CPM (revenue per 1,000 views) applied to view count — not actual creator earnings, which depend on ad rates, audience geography, and monetization settings YouTube doesn't expose publicly.
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