# Zscaler Deception: how AI models rank it, October 2026

IT AI Recommendation Index, October 2026 Edition. Named in 12 judge labels across 1 categories by 8 of 14 models. Page: https://it-ai-index.com/vendors/zscaler-deception/

## Standing by category

| Category | Share | Rank | Negative rate | Labels |
|---|---|---|---|---|
| Deception technology | 0% | 31 | 33% | 12 |

## What the models said for it

- "You already use Zscaler and want deception closely integrated with its Zero Trust platform." (GPT-6 Luna, Deception)
- "Companies already using Zscaler | Integrated with existing Zscaler infrastructure" (Kimi K2, Deception)
- "Already standardized on Zscaler? Start with Zscaler Deception" (GPT-6 Luna, Deception)
- "Zscaler Deception (good for cloud-heavy environments)" (DeepSeek V4 Flash, Deception)

## And against it

- "one listed dislike says endpoint decoys created unnecessary network noise. That's a reason to test the feature in your own network—not, by itself, a reason to reject the product." (GPT-6 Luna, Deception)
- "platforms like SentinelOne, Zscaler, and Fortinet may include deception as a light feature, but they are not designed primarily for deception" (Mistral Small, Deception)
- "These outperform "deception features" in XDR (e.g., SentinelOne's own lite version, Zscaler)" (Grok 4.1 Fast, Deception)
- "Overkill and likely over budget" (GLM 4.7 FlashX, Deception)

## In its own words

What Zscaler Deception's own pages state, read 2026-10-05. Stated by the vendor, not checked by the index.

- Positioning: Allows you to configure and deploy decoys to disrupt active attacks, create fake attack paths, and gain high-fidelity threat intelligence. (https://help.zscaler.com/deception/about-deceive)
- For: security teams (https://help.zscaler.com/deception/about-investigate)

## Record

- Method: https://it-ai-index.com/methodology/
- Raw judge labels and full responses: https://it-ai-index.com/data/
- License: CC BY 4.0. Cite as IT AI Recommendation Index, October 2026 Edition, it-ai-index.com.