| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Endpoint detection and response | Security operations | 15% | 3 of 55 | 9% | 56 | accepted challenger | ▲+5Since September 2026: 8% → 13%, +5 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| AI security platforms | Security operations | 11% | 1 of 233 | 8% | 25 | accepted challenger | |
| Extended detection and response | Security operations | 8% | 4 of 58 | 10% | 51 | accepted challenger | ▲+2Since September 2026: 5% → 7%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Endpoint protection | IT operations and endpoint | 5% | 6 of 86 | 0% | 25 | accepted challenger | ▲+2Since September 2026: 4% → 6%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Deception technology | Security operations | 0% | 34 of 94 | 33% | 9 | under 10 labels · led by Thinkst Canary at 37% | |
| Cloud-native application protection | Cloud and infrastructure | 0% | 22 of 70 | 0% | 3 | under 10 labels · led by Wiz at 37% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| AI SOC agents | Security operations | 0% | 77 of 104 | 0% | 2 | under 10 labels · led by Dropzone AI at 24% | |
| Attack surface management | Security operations | 0% | 59 of 100 | 0% | 2 | under 10 labels · led by Intruder at 49% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Client-side protection | Security operations | 0% | 36 of 120 | 0% | 2 | under 10 labels · led by cside at 13% | |
| Threat intelligence platforms | Security operations | 0% | 107 of 119 | 50% | 2 | under 10 labels · led by MISP at 12% | newNew since September 2026: not ranked then, 0% now. |
| Container and Kubernetes security | Cloud and infrastructure | 0% | 47 of 77 | 0% | 1 | under 10 labels · led by Trivy at 22% | newNew since September 2026: not ranked then, 0% now. |
| Digital employee experience | IT operations and endpoint | 0% | 106 of 219 | 0% | 1 | under 10 labels · led by ControlUp at 13% | |
| Network detection and response | Security operations | 0% | 61 of 102 | 0% | 1 | under 10 labels · led by ManageEngine NetFlow Analyzer at 21% | |
| SIEM platforms | Security operations | 0% | 48 of 61 | 0% | 1 | under 10 labels · led by Microsoft Sentinel at 38% | newNew since September 2026: not ranked then, 0% now. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| AI security | 0% | 11% | newNew since September 2026: not ranked then, 11% now. | New this edition | Rank 1 of 233, unchanged |
| EDR | 8% | 13% | ▲+5Since September 2026: 8% → 13%, +5 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 6 → 3 of 55 |
| XDR | 5% | 7% | ▲+2Since September 2026: 5% → 7%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 3 → 4 of 58 |
| Endpoint protection | 4% | 6% | ▲+2Since September 2026: 4% → 6%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 7 → 6 of 86 |
| Deception | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 34 of 94, unchanged |
| CNAPP | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 31 → 22 of 70 |
| AI SOC agents | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 77 of 104, unchanged |
| ASM | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 79 → 59 of 100 |
| Client-side protection | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 36 of 120, unchanged |
| Threat intel | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 107 of 119, unchanged |
| Container security | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 47 of 77, unchanged |
| DEX | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 106 of 219, unchanged |
| SIEM | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 48 of 61, unchanged |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 1 | 3 | 5 | 1 | 10 |
| GPT-5.4 mini | 0 | 6 | 2 | 0 | 8 |
| Gemini 3.5 Flash | 3 | 10 | 2 | 1 | 16 |
| Perplexity Sonar | 2 | 5 | 5 | 0 | 12 |
| Grok 4.20 | 2 | 12 | 5 | 2 | 21 |
| Mistral Small | 3 | 2 | 5 | 2 | 12 |
| DeepSeek V4 Flash | 4 | 11 | 4 | 1 | 20 |
| Llama 4 Maverick | 0 | 0 | 5 | 1 | 6 |
| Qwen 3.7 Flash | 2 | 7 | 4 | 2 | 15 |
| Kimi K2 | 5 | 8 | 3 | 1 | 17 |
| GLM 4.7 FlashX | 0 | 6 | 3 | 2 | 11 |
| MiniMax M2.5 | 2 | 7 | 5 | 0 | 14 |
| GPT-6 Luna | 0 | 4 | 1 | 1 | 6 |
| Muse Glimmer 30B | 4 | 4 | 3 | 2 | 13 |
Verbatim evidence the judge attached to positive labels.
“Have an in-house security team and want top autonomous response: SentinelOne Singularity Complete about $179.99 per endpoint per year or CrowdStrike Falcon Pro/Enterprise.” Muse Glimmer 30B · EDR · direct prompt · first choice
“For most mid-market B2B companies, SentinelOne Singularity offers the best balance of autonomous protection, reasonable pricing, and minimal management overhead.” Kimi K2 · EDR · direct prompt · first choice
“start with SentinelOne Singularity or Microsoft Defender for Endpoint—they offer the best balance of AI-native protection, manageability, and price.” Kimi K2 · AI security · direct prompt · first choice
“If you're early-stage and just need a solid answer — start with SentinelOne. It's the most accessible, most automated, and most forgiving for lean teams.” Muse Glimmer 30B · AI security · budget prompt · first choice
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“overly aggressive blocking of legitimate tools... agent duplication issues have been reported in the management console during large-scale deployments” Claude Haiku 4.5 · XDR · negative prompt · soft negative
“platforms like SentinelOne, Zscaler, and Fortinet may include deception as a light feature, but they are not designed primarily for deception” Mistral Small · Deception · negative prompt · soft negative
“These outperform "deception features" in XDR (e.g., SentinelOne's own lite version, Zscaler)—purpose-built yield better realism/scale.” Grok 4.20 · Deception · comparative prompt · soft negative
“Two distinct classes of caution have been raised recently: a service provider vulnerability advisory and BYOEDR abuse research.” Muse Glimmer 30B · EDR · negative prompt · soft negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 534 of the 569 answers that named SentinelOne Singularity and are not a share of its labels.
1,260 of the 1,487 domain citations in answers naming SentinelOne Singularity came from somebody else's page.
Pages are listed as the models cited them.
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
What SentinelOne Singularity's own pages state, read September 28, 2026: sentinelone.com/platform/singularity-core, sentinelone.com/platform/singularity-mobile, sentinelone.com/platform/singularity-control, sentinelone.com/platform/singularity-complete, sentinelone.com/platform/singularity-cloud-cspm. A claimed page can correct any of them.
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when SentinelOne Singularity's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as SentinelOne Singularity, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
A new claim receives the current edition's vendor brief for SentinelOne Singularity by email, built from the raw record of the edition. It shows:
SentinelOne Singularity is among the products AI models recommend first in Endpoint detection and response this edition. Each badge says so in the buyer's words, names the edition, and links to the standing. The next edition issues a new badge; this one stays true as a record of October 2026.
AI models recommend SentinelOne Singularity first in AI security platforms this edition. Each badge says so in the buyer's words, names the edition, and links to the standing. The next edition issues a new badge; this one stays true as a record of October 2026.
Badges read on light and dark pages. Alt text carries the claim, the category, the edition and the index, so it stays a citation where the image does not load.