# Fortinet FortiDeceptor alternatives: what AI models name instead, October 2026

IT AI Recommendation Index, October 2026 Edition. 236 of the 252 answers in the 1 category where Fortinet FortiDeceptor holds a standing named it neither first nor as an alternative; these are the first choices those answers made. Page: https://it-ai-index.com/vendors/fortinet-fortideceptor/alternatives/

## Named instead, most often (every category and segment added)

- Thinkst Canary: 47
- Acalvio ShadowPlex: 37
- OpenCanary: 11
- HoneyWire: 8
- Trapster: 6
- Morphisec: 4

## Deception technology

**Small business**: 82 of 84 answers did not name Fortinet FortiDeceptor.

- Thinkst Canary: first choice in 26 of those 82
- OpenCanary: first choice in 9 of those 82
- HoneyWire: first choice in 5 of those 82
- Morphisec: first choice in 4 of those 82
- Trapster: first choice in 4 of those 82
- Canarytokens: first choice in 3 of those 82
- CyberTrap: first choice in 2 of those 82
- Acalvio ShadowPlex: first choice in 1 of those 82

**Mid-market**: 76 of 84 answers did not name Fortinet FortiDeceptor (Fortinet FortiDeceptor is #5 of 11 at 2%).

- Thinkst Canary: first choice in 15 of those 76
- Acalvio ShadowPlex: first choice in 9 of those 76
- HoneyWire: first choice in 3 of those 76
- Canarytokens.org: first choice in 2 of those 76
- Illusive Networks: first choice in 2 of those 76
- OpenCanary: first choice in 2 of those 76
- Tracebit: first choice in 2 of those 76
- Trapster: first choice in 2 of those 76

**Enterprise**: 78 of 84 answers did not name Fortinet FortiDeceptor.

- Acalvio ShadowPlex: first choice in 27 of those 78
- Thinkst Canary: first choice in 6 of those 78
- Zscaler Deception: first choice in 4 of those 78
- Attivo Networks ThreatDefend: first choice in 3 of those 78
- Fidelis Deception: first choice in 3 of those 78
- Rapid7 Incident Command: first choice in 3 of those 78
- SentinelOne Singularity: first choice in 3 of those 78
- Attivo Networks: first choice in 2 of those 78

Published under CC BY 4.0. The output is the models' output; nothing here is a recommendation by the index.