Machine Relations Index

Cybersecurity · Machine Relations Index category

Which sources AI engines cite for Cybersecurity questions

Vendor-owned sources earn 44.6% of classified citations in Cybersecurity answers (2,791 of 6,263), as of November 2, 2026.

In the November 2026 release of the Machine Relations Index, these are the sources AI answer engines cited most often for each of the 7 Cybersecurity question shapes, each ranked on that shape's own observed runs. This category has 7 observed question-shape segments in the current public release. Each segment keeps its own observed-run denominator and dates; this page does not average rates across shapes. Observed runs are answer runs, not questions: every segment repeats a small set of distinct questions across engines and dates, so a run count is not a count of independent questions.

Top sources by question shape

The sources engines cite most, shape by shape

A rate is the share of the shape's observed answer runs that cited the source; rank is the source's place on that shape's full leaderboard.

Best tools

Example pattern: best cybersecurity tools. 238 observed runs across 13 dates.

RankSourceSource roleCitation rateCited runs
#1 of 307Huntress.comVendor-owned source43.70%104 of 238
#2 of 307Expert InsightsEditorial publication26.05%62 of 238
#3 of 307Cyber Security NewsEditorial publication24.37%58 of 238
#4 of 307G2Market and company database22.69%54 of 238
#5 of 307Kaseya.comOther observed source20.59%49 of 238

Full Best tools leaderboard, 307 sources

How buyers choose

Example pattern: how to choose cybersecurity tools. 277 observed runs across 12 dates.

RankSourceSource roleCitation rateCited runs
#1 of 434Microsoft.comVendor-owned source18.05%50 of 277
#2 of 434Expel.comOther observed source11.19%31 of 277
#3 of 434Kaseya.comOther observed source10.83%30 of 277
#4 of 434Jumpcloud.comOther observed source9.75%27 of 277
#5 of 434Soc2auditors.orgOther observed source9.75%27 of 277

Full How buyers choose leaderboard, 434 sources

Is it worth it

Example pattern: is cybersecurity software worth it. 278 observed runs across 12 dates.

RankSourceSource roleCitation rateCited runs
#1 of 323Paloaltonetworks.comVendor-owned source22.66%63 of 278
#2 of 323Cyware.comOther observed source18.71%52 of 278
#3 of 323Microsoft.comVendor-owned source14.39%40 of 278
#4 of 323Swimlane.comOther observed source12.23%34 of 278
#5 of 323TechTargetEditorial publication12.23%34 of 278

Full Is it worth it leaderboard, 323 sources

News-driven citations

Example pattern: recent cybersecurity news. 599 observed runs across 54 dates.

RankSourceSource roleCitation rateCited runs
#1 of 1,338Paloaltonetworks.comVendor-owned source13.52%81 of 599
#2 of 1,338Sentinelone.comVendor-owned source12.52%75 of 599
#3 of 1,338Microsoft.comVendor-owned source9.52%57 of 599
#4 of 1,338Gartner.comAnalyst and consulting research9.35%56 of 599
#5 of 1,338Crowdstrike.comVendor-owned source8.51%51 of 599

Full News-driven citations leaderboard, 1,338 sources

Problem-first research

Example pattern: how to solve cybersecurity problems. 264 observed runs across 12 dates.

RankSourceSource roleCitation rateCited runs
#1 of 414Github.comCommunity and social platform18.18%48 of 264
#2 of 414Nhimg.orgOther observed source13.26%35 of 264
#3 of 414Microsoft.comVendor-owned source10.98%29 of 264
#4 of 414MediumCommunity and social platform8.33%22 of 264
#5 of 414Huntress.comVendor-owned source7.95%21 of 264

Full Problem-first research leaderboard, 414 sources

Top lists

Example pattern: top cybersecurity platforms. 267 observed runs across 12 dates.

RankSourceSource roleCitation rateCited runs
#1 of 397Hoxhunt.comOther observed source23.60%63 of 267
#2 of 397Adaptivesecurity.comOther observed source22.47%60 of 267
#3 of 397Expert InsightsEditorial publication21.72%58 of 267
#4 of 397Usecure.ioOther observed source18.73%50 of 267
#5 of 397Knowbe4.comOther observed source15.73%42 of 267

Full Top lists leaderboard, 397 sources

Comparisons

Example pattern: cybersecurity platform A vs B. 212 observed runs across 12 dates.

RankSourceSource roleCitation rateCited runs
#1 of 272Vectra.aiVendor-owned source25.47%54 of 212
#2 of 272Exabeam.comOther observed source21.23%45 of 212
#3 of 272Sentinelone.comVendor-owned source21.23%45 of 212
#4 of 272Cynet.comVendor-owned source16.98%36 of 212
#5 of 272Crowdstrike.comVendor-owned source15.09%32 of 212

Full Comparisons leaderboard, 272 sources

Observed shapes7

Canonical segment URLs exist only for observed category/shape pairs.

Published7

Published segments met the release evidence floor.

Collecting0

Collecting segments expose sample progress, not mature leaderboards.

ReleaseNovember 2, 2026

Methodology v2.1.

Question shapes

Separate denominators by segment

Question shapeStateObserved runsDistinct questionsRun datesDistinct cited domainsCanonical segment
Best toolsPublished2387 (5 paraphrase groups)13307Open leaderboard
How buyers choosePublished2777 (5 paraphrase groups)12434Open leaderboard
Is it worth itPublished2787 (5 paraphrase groups)12323Open leaderboard
News-driven citationsPublished59933541,338Open leaderboard
Problem-first researchPublished2647 (5 paraphrase groups)12414Open leaderboard
Top listsPublished2677 (5 paraphrase groups)12397Open leaderboard
ComparisonsPublished2127 (5 paraphrase groups)12272Open leaderboard

By answer engine

Whole-window rates on each engine

Each link ranks sources with a published Cybersecurity segment by that source's citation rate on one engine across the whole window. It is not a rate inside Cybersecurity alone. A collecting engine has no published ranking for this category.
Cite this
Citation
Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai. Cybersecurity, observed Machine Relations Index category, 2026-05-10 to 2026-11-02. Release mri_score_v2.1+2026-11-02+f9aaeca0db15. https://machinerelations.ai/index/categories/cybersecurity. CC BY 4.0.
APA
Parrott, J. (2026). Cybersecurity in the Machine Relations Index (Version mri_score_v2.1+2026-11-02+f9aaeca0db15) [Data set]. Machine Relations Research. https://machinerelations.ai/index/categories/cybersecurity https://doi.org/10.5281/zenodo.23652423
BibTeX
@misc{parrott2026mricybersecurity,
  author = {Parrott, Jaxon},
  title = {Cybersecurity in the Machine Relations Index},
  year = {2026},
  version = {mri\_score\_v2.1+2026-11-02+f9aaeca0db15},
  publisher = {Machine Relations Research},
  url = {https://machinerelations.ai/index/categories/cybersecurity},
  doi = {10.5281/zenodo.23652423},
  license = {CC-BY-4.0},
  note = {Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai}
}

CITATION.cff

Release and boundary

No pooled category score

Published November 2, 2026. The observation window runs May 10, 2026 to November 2, 2026. Methodology v2.1.

Use the data
curl -fsSL "https://machinerelations.ai/data/machine-relations-index.json" -o machine-relations-index.json
curl -fsSL "https://machinerelations.ai/data/mri-release-manifest.json" -o mri-release-manifest.json
curl -fsSL "https://huggingface.co/datasets/machine-relations/machine-relations-index/resolve/main/domains.csv" -o domains.csv
curl -fsSL -L "https://doi.org/10.5281/zenodo.23652423" -o mri-zenodo.html
import json
from urllib.request import urlopen

index_url = "https://machinerelations.ai/data/machine-relations-index.json"
with urlopen(index_url) as response:
    index = json.load(response)
print(index["generated"], index["total_domains"])

This page is a directory of observed segments. A domain's overall citation rate is not a category rate, and MRI does not publish an averaged category score in this slice.

Cybersecurity buyers on AuthorityTech’s publication intelligence is a downstream practitioner projection of these segments. It is not source evidence, citation provenance, or an identity link for the neutral dataset.