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Deception technology · October 2026 Edition

OpenCanary vs T-Pot

Zero of fourteen models named OpenCanary first on the direct prompt; zero named T-Pot. OpenCanary was named by ten of the fourteen models and T-Pot by nine and OpenCanary carries 17 labels and T-Pot 11, so the shares are not directly comparable.

OpenCanary

accepted challenger

Named in one category this edition.

T-Pot

accepted challenger

Named in one category this edition.

First-choice share4%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%9%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#6A position in a field of 11; printed, not drawn.
Labels1711A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, OpenCanary reading right to left. Rank and label count are printed, not drawn.Acalvio ShadowPlex was named alongside these two in nine of the fourteen direct answers. Thinkst Canary vs OpenCanary · Thinkst Canary vs T-Pot · Acalvio ShadowPlex vs OpenCanary

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the deception technology page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
OpenCanaryFirst choices, of fourteen modelsT-Pot
Direct00
Paraphrase001 against T-Pot
Comparative00
Budget-constrained21
Scale-constrained00
Negative00
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the October 2026 Edition, OpenCanary and T-Pot were named in the same answer nineteen times, of the 40 answers naming OpenCanary and the 31 naming T-Pot. In those answers T-Pot took the first choice zero times and OpenCanary seven.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where OpenCanary and T-Pot stood in it.
ModelDirectOPTPParaphraseOPTPComparativeOPTPBudget-constrainedOPTPScale-constrainedOPTPNegativeOPTP
Claude Haiku 4.5OP
GPT-5.4 miniTP
Gemini 3.5 FlashOPOPTP
Perplexity SonarOPOP
Grok 4.1 FastOPTPOP
Mistral SmallOP
DeepSeek V4 FlashOPOP
Llama 4 MaverickTP
Qwen 3.7 FlashTP
Kimi K2OP
GLM 4.7 FlashXTPOPTP
MiniMax M2.5
GPT-6 LunaOPOPTP
Muse Glimmer 30BTPOP
OP OpenCanaryTP T-PotOP first choiceOP named as an alternativeOP argued againstblank: not namedEach cell is one answer, OpenCanary on the left and T-Pot on the right.

The direct prompt

The plain question, one answer per model, grouped by where OpenCanary and T-Pot stood in it.

Neither was named

14 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Deceptive Bytes alternatives: Acalvio 360 Deception, Illusive, Thinkst Canary
GPT-5.4 miniThinkst Canary alternatives: Acalvio ShadowPlex
Gemini 3.5 FlashThinkst Canary alternatives: SentinelOne Singularity Hologram, Tracebit
Perplexity SonarAcalvio ShadowPlex alternatives: Fortinet FortiDeceptor, Thinkst Canary
Grok 4.1 FastAcalvio ShadowPlex alternatives: Fortinet FortiDeceptor, Thinkst Canary
Mistral SmallAcalvio ShadowPlex, Attivo Networks ThreatDefend
DeepSeek V4 FlashTracebit alternatives: Acalvio ShadowPlex, Fidelis Deception, FortiDeceptor
Llama 4 Maverickno first choice
Qwen 3.7 FlashHoneypot.io alternatives: Attivo Networks, Cymulate, Microsoft Defender XDR
Kimi K2Thinkst Canary alternatives: TrapEye, Trapster
GLM 4.7 FlashXRapid7 InsightIDR alternatives: Acalvio ShadowPlex, Fortinet FortiDeceptor
MiniMax M2.5Acalvio ShadowPlex, Illusive Networks
GPT-6 LunaTracebit alternatives: Acalvio ShadowPlex, Thinkst Canary, Zscaler Deception
Muse Glimmer 30BFortinet FortiDeceptor, Rapid7 Incident Command alternatives: Acalvio ShadowPlex, Proofpoint, Thinkst Canary

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
OpenCanary leads by eighteen points.
OpenCanary18%#2 of 9
T-Pot0%#8 of 9
The full small business standing →
Mid-marketThe figures above
OpenCanary leads by two points.
OpenCanary4%#4 of 11
T-Pot2%#6 of 11
The full mid-market standing →
Enterprise
Level: the same share of first choices.
OpenCanary0%#– of 8
T-Pot0%#– of 8
The full enterprise standing →

What the models said about OpenCanary

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“Start with Canarytokens.org (free) + OpenCanary (free)” Kimi K2 · budget prompt · first choice
“For a genuinely limited budget, start with OpenCanary.” GPT-6 Luna · budget prompt · first choice
“Another strong open-source option is OpenCanary, also from Thinkst, which is free and supports multiple protocols.” Mistral Small · paraphrase prompt · alternative

What the models said about T-Pot

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.

“High maintenance (Docker-heavy); better for labs than production.” Grok 4.1 Fast · paraphrase prompt · soft negative
“Pick `T-Pot` if you have ≥1 person who knows Linux, Docker, and log analysis, and you want maximum detection surface for $0.” Qwen 3.7 Flash · budget prompt · first choice
“2. T-Pot - an open-source honeypot platform that combines multiple protocol-specific honeypots and analytics tools.” Llama 4 Maverick · paraphrase prompt · alternative
“T-Pot is a strong option... but it has higher operational overhead and infrastructure requirements” GPT-5.4 mini · paraphrase prompt · alternative
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.