Highlights
- The dataset: This report draws on over 230,000 AI source citations, collected with prompts specific to the cybersecurity software industry. The underlying AI responses, from four AI models, were gathered in 12 countries throughout Q2 2026.
- Reddit climbed from #3 to #1 in the window (+216%): With techradar.com leaping from #15 to #3.
- Reddit alone makes up 16% of ChatGPT's citations: That makes ChatGPT the most concentrated model.
- 55% of Google AI Overview's citations are from commercial domains: Vendor pages, making it the most vendor-heavy model.
- 87% of top sources differ between any two models: Roughly seven in eight cited domains are exclusive to one engine's top tier.
Which sources should you target to get cited as a cybersecurity software brand?
The single most-cited domain is different for every model, and the concentration varies widely. ChatGPT is the most concentrated, Reddit alone accounts for 15.9% of its citations, while Grok spreads its citations thinly across a long tail (its #1 source is just 3.4%).
| Model | #1 | #2 | #3 | #4 | #5 |
|---|---|---|---|---|---|
| ChatGPT | reddit.com (15.9%) | techradar.com (5.8%) | uinat.com (2.1%) | cincodias.elpais.com (2.1%) | eset.com (2.0%) |
| Microsoft Copilot | thectoclub.com (6.8%) | f6s.com (3.0%) | ensun.io (2.9%) | ehlist.ca (2.6%) | sourceforge.net (2.6%) |
| Grok | sentinelone.com (3.4%) | gartner.com (3.0%) | reddit.com (2.5%) | youtube.com (1.9%) | deepstrike.io (1.8%) |
| Google AI Overview | youtube.com (5.6%) | sentinelone.com (5.3%) | microsoft.com (2.9%) | fortinet.com (2.2%) | reddit.com (2.0%) |
The character of each list is distinct: Microsoft Copilot reads like a SaaS comparison directory, ChatGPT like a forum-plus-tech-press digest, Grok like an analyst-and-vendor briefing, and Google AI Overview like a video-and-vendor blend.
How have AI source rankings changed over time in the cybersecurity software industry?
We split the observation window at its midpoint (early May 2026) and compared each top domain's share of citations in each half.
The standout mover is Reddit, which climbed from #3 to #1 by share (+216%), and techradar.com, which leapt from #15 to #3 (+301%). Both gains reflect ChatGPT's growing concentration on forum and tech-press content. On the other side, analyst and directory sites lost ground: gartner.com (#4 → #9), deepstrike.io (#5 → #13), and pcmag.com (#7 → #12) all roughly halved their share. We report the movement as directional, not as a forecast.
What type of content do AI models cite for cybersecurity software?
We classified every cited domain by its content category and measured the mix per model. The split is stark: the two highest-volume models (Grok and Google AI Overview) send more than half their citations to commercial vendor sites, while ChatGPT and Microsoft Copilot spread more evenly into editorial and user-generated content.
For a vendor, the read is direct: Google AI Overview and Grok reward owned vendor content most heavily, while ChatGPT and Microsoft Copilot demand presence on editorial tech press and community sites, reviews, forums, comparison guides, to be cited at all.
Do AI models cite local-language content for cybersecurity software?
Across the six non-English markets we measured (German, French, Italian, Dutch, Swedish, Spanish), only 23.7% of citations point to a local-country domain, a .de, .fr, .it, .nl, .se, or .es site. The clear majority go to English-language or global .com-type sources. Cybersecurity is a globally branded category, vendors, analysts, and the major tech press publish in English, and the AI models reflect that.
Spanish is the outlier on the low end, despite being the largest non-English market in the dataset, Spanish-language cybersecurity prompts pull heavily from global .com vendor and review sites rather than .es domains. French is the most locally grounded.
Which AI model relies most on local sources for cybersecurity software?
The same prompt, asked in the same language, produces very different localization behavior depending on the model. Google AI Overview and Microsoft Copilot cite local sources at roughly twice the rate as ChatGPT.
Google AI Overview cites local domains over half the time in the Dutch market and over 40% in German and Italian. ChatGPT, by contrast, cites local sources only 5.6% of the time in Spanish and 14% on average, it reaches for global English sources almost everywhere. (Google AI Overview returned no French-market cell in this dataset, so its French figure is shown as n/a; its average covers the five languages with data.)
Should cybersecurity software optimize for each AI model separately?
Barely any common ground exists to share. We built each model's top-20 most-cited domains and compared every pair, measuring the share of domains two lists hold in common. The average overlap is 12.9%, lower than the cross-industry benchmark, and a sign that cybersecurity-software answers are unusually fragmented across engines.
Only one domain, SentinelOne, appears in all four models' top-20 lists. It is the closest thing the cybersecurity-software category has to a universally trusted source. Everything else is contested. A brand visible on one model can be absent from ~87% of the sources another model cites.
How many sources does each AI model cite per answer?
The four models differ substantially in how many sources they cite in a single answer. Grok is the most source-hungry by far, averaging 28.3 sources per response; Microsoft Copilot is the most economical at 7.0, a 4x gap.
For a vendor, source count is opportunity: Grok's wide net means more chances to be cited per answer, but each citation carries less weight; Microsoft Copilot's narrow net means fewer slots and higher stakes for each one.
Context
This report covers how four AI search and answer engines, ChatGPT, Microsoft Copilot, xAI Grok, and Google AI Overview, cite web sources when answering cybersecurity-software questions. The data spans twelve markets (US, UK, Canada, Australia, Germany, France, Italy, Netherlands, Sweden, Spain, Mexico, Argentina) and seven languages, collected over roughly fifteen weeks from mid-March to late June 2026.
It measures what AI models cite, not the accuracy of any answer, the traffic value of a citation, or causation behind any ranking movement. These findings reflect citation behavior for cybersecurity-software prompts in the monitored markets, and may not generalize to all products, prompt types, or other industry verticals.
Methodology
How we measured this
We tracked four AI models responding to cybersecurity-software prompts across twelve countries and seven languages. Each response was parsed to extract source citations: the URLs, domains, and metadata referenced, counting only sources flagged as actually cited rather than merely retrieved. Domain categories (commercial, editorial, UGC, institutional, reference) were assigned from a global domain registry. Cross-model overlap was measured on each model pair's top-20 most-cited domains. Temporal analysis split the observation period at its midpoint and compared domain rankings in each half.
The analysis covers over 230,000 cited sources from 22,066 AI responses. Sample sizes exceeded recommended thresholds for every reported finding. Localization is measured by a country-code-domain (ccTLD) proxy, the source records carry no detected content language, so those figures are directional and exclude English-language prompts, which sit overwhelmingly on generic domains. Temporal movement is a single before/after split over a short window, and model coverage varied across it, so shifts are reported as within-half shares and read as directional.
Frequently asked questions
Do different AI models cite the same cybersecurity sources?
No, overwhelmingly not. Any two of the four models share on average just 12.9% of their top-20 domains, so about 87% of the sources one model trusts are absent from another's top tier. Only sentinelone.com appears across all four lists.
Which AI model cites the most sources per answer for cybersecurity?
Grok, by a wide margin, about 28 sources per cybersecurity response, versus roughly 10 for Google AI Overview and about 7 for ChatGPT and Microsoft Copilot. That is a 4x spread between the most and least source-hungry models.
Which single domain matters most in cybersecurity AI answers?
It depends on the model. ChatGPT concentrates nearly 16% of its citations on reddit.com; Microsoft Copilot leads with thectoclub.com; Grok with sentinelone.com; Google AI Overview with youtube.com. sentinelone.com is the only domain trusted by all four.
What type of content gets cited most for cybersecurity software?
Commercial vendor sites lead overall, but the mix differs sharply. Grok and Google AI Overview send 52–55% of citations to commercial domains, while ChatGPT and Microsoft Copilot spread more evenly into editorial tech press (28–30%) and community/UGC sites (22–30%).
Do AI models cite local-language content in non-English cybersecurity markets?
Only partly. Across six non-English markets, about 24% of citations use a local-country domain; the rest lean on English and global sources. French markets are the most local (40%), Spanish the least (13%).
Which model is best for reaching non-English cybersecurity audiences?
Google AI Overview and Microsoft Copilot rely most on local sources, about a third of their citations in non-English prompts are local-domain, roughly double ChatGPT's rate (14%). A brand targeting German, Dutch, or Italian buyers gets the most local-source visibility through Google AI Overview.
Did the cybersecurity source rankings change over the period studied?
Yes. reddit.com climbed from #3 to #1 by citation share and techradar.com from #15 to #3, while analyst and directory sites like gartner.com, deepstrike.io, and pcmag.com lost roughly half their share. We read the shift as directional rather than a firm trend.
What should a cybersecurity vendor do with this?
Optimize per model, not in general. Winning Google AI Overview and Grok rewards strong owned vendor content; winning ChatGPT and Microsoft Copilot requires presence on editorial tech press, review platforms, and community sites. Because the models overlap so little, a single-channel strategy leaves you invisible to most of the AI search surface.
