Last updated July 2026
The number is striking. Nearly three out of four cybersecurity vendors are completely invisible when a buyer types a category question into ChatGPT. Not ranked low. Not mentioned once in passing. Simply absent.
That absence costs deals. Buyers tend to shortlist only brands they have already encountered. If you are not in the AI-generated answer, you are not in the consideration set.
This teardown explains why the cliff exists, shows you how to baseline your share of voice against named rivals, and walks through a four-signal diagnostic for figuring out what to do about it. It is a share-of-voice and brand-mention measurement problem before it is anything else.
What the 73% figure actually means
The GrackerAI benchmark (published February 2026) tested 100 cybersecurity vendors using 250 buyer-intent prompts across six AI platforms. For ChatGPT specifically, 73% of those vendors received zero citations when buyers asked questions in their product category.
Note what this means precisely: it is not that buyers are uninterested in these vendors. It is that ChatGPT had no retrievable, citable source placing that vendor in a relevant answer. The model does not speculate. It returns what it can verify against sources it trusts, and for most cybersecurity brands in most sub-categories, no such source exists.
(GrackerAI is an AI visibility platform vendor, not an independent research firm. Treat the figure as directionally meaningful, not as a neutral industry census. The pattern it describes is real and consistent with how AI retrieval works.)
Why cybersecurity is especially exposed
Three structural features of the security market create this visibility gap.
Sub-category fragmentation. Cybersecurity has more named sub-categories than almost any other software vertical: EDR, XDR, CSPM, SSPM, SIEM, SOAR, ITDR, CAASM, CTEM, OT/ICS security, browser security, email security, cloud-native application protection platforms. Analyst coverage is concentrated on the largest categories. Buyers who ask about an emerging sub-category find that the AI has thin retrieval options.
Analyst-list dependence. AI engines weight Gartner Magic Quadrant, Forrester Wave, and G2 category pages heavily when constructing answers about vendor landscapes. A vendor absent from a relevant Magic Quadrant or Wave, or with thin G2 reviews in their primary category, loses the citation signal that the majority of cited vendors rely on.
Content complexity as a barrier. Security content is technically dense and often gated behind forms, requiring registration to access white papers and research. Gated content is not retrievable by AI. Technical blog posts written for practitioners rather than buyers produce citations inside practitioner communities but not inside buyer-intent AI responses.
The share-of-voice baseline table
Before diagnosing what to fix, you need to know where you stand. The table below shows the pattern across representative cybersecurity sub-categories. Fill in your own numbers using the prompt-testing approach described in the next section.
| Sub-category | Typical ChatGPT-cited vendors | Who gets cited | Zero-citation zone signal |
|---|---|---|---|
| Endpoint Detection and Response (EDR) | 4 to 8 brands | Gartner MQ leaders + G2 top-rated | High: sub-category is well-documented, but only top 5 to 8 appear |
| Cloud Security Posture Management (CSPM) | 3 to 6 brands | Gartner MQ + Forrester Wave leaders | High: strong analyst coverage concentrates citations on a short list |
| Identity Threat Detection and Response (ITDR) | 2 to 4 brands | Emerging category: Gartner peer insights + G2 | Very high: category is too new for full MQ coverage |
| SaaS Security Posture Management (SSPM) | 1 to 3 brands | G2 category leaders + editorial lists | Very high: thin analyst coverage, few editorial sources |
| OT/ICS Security | 0 to 2 brands | Niche: specialist editorial only | Extreme: AI has minimal retrieval sources for this sub-category |
| Browser Security | 0 to 2 brands | No MQ; sparse editorial | Extreme: emerging category with almost no third-party coverage |
The pattern: the more established the category, the more defined the citation hierarchy. Brands outside the top five on a Gartner or Forrester list in a well-covered category rarely appear. In emerging or niche categories, almost nobody appears. Both situations require different fixes.
How to run your share-of-voice baseline
You need real prompt data before any strategy makes sense. Here is the diagnostic process.
Step 1: Build a prompt set that mirrors buyer intent
Write 15 to 25 prompts the way a buyer would phrase them, not the way your marketing team writes. Use product categories, not product names. Examples for an EDR vendor:
- “What are the best endpoint detection and response tools for mid-sized enterprises?”
- “Compare EDR platforms for a team without a dedicated SOC”
- “Which EDR vendors do CISOs recommend?”
- “Alternatives to CrowdStrike for endpoint protection”
- “What endpoint security tools integrate with Splunk?”
Cluster prompts by buyer stage (awareness, evaluation, comparison) and by sub-category variant. That cluster is your prompt family for that category.
Step 2: Run five responses per prompt
Answer engines are probabilistic. One response is one sample. Run each prompt five times across ChatGPT and at least one other engine (Perplexity and Google AI Overviews are the highest-priority additions for B2B security buyers). Record every brand name that appears.
Step 3: Calculate raw citation rate and share of voice
For each prompt family, count how many of your five runs include your brand. Divide by five. That is your citation rate for that prompt. Then count competitor mentions across the same runs. Your share of voice is your citation count divided by the total citation count across all brands in that prompt set.
A citation rate of zero across all prompts in a category means you are in a zero-citation zone for that category.
Step 4: Flag zero-citation categories
Any sub-category where your citation rate is zero across all prompt variants is a zero-citation category. List them. These are your highest-priority gaps. A zero-citation category is not a content problem yet. It is an absence problem: the AI has no retrieval source that places you in that category.
Zero-citation category detection checklist
Run through this checklist for each zero-citation category you identify.
- Are you listed on the primary G2 category page for this sub-category? (Search G2 directly; confirm your profile exists and has a minimum of 10 reviews in the correct category.)
- Does a Gartner Magic Quadrant or Forrester Wave exist for this category, and are you named in it?
- Have any third-party editorial sources (analyst blogs, security news publications, independent review sites) published content that names you in this category in the past 12 months?
- Do the pages on your own site that describe this category use the exact category language buyers use in prompts (not your internal product naming)?
- Are your site pages accessible to AI crawlers? (Check your robots.txt and verify that your security headers do not block the user agents used by ChatGPT, Perplexity, and Google AI.)
- Do you have any structured schema markup on your primary category pages?
If you answer “no” to the first three items, content changes alone will not move the needle. You need source presence before content.
The 4-signal diagnostic
AI citation patterns in cybersecurity come down to four signals. Measure all four before deciding where to spend effort.
Signal 1: Analyst and review-platform presence
This is the dominant signal in cybersecurity. AI engines treat Gartner, Forrester, and G2 as authoritative category sources. If your brand is absent from those sources in a given sub-category, your citation probability for that category is close to zero regardless of how good your content is.
What to check: Search G2 for your exact sub-category. Confirm you have a minimum of 10 to 25 reviews, that your category tag is correct, and that you appear in the relevant G2 Grid report. For Gartner and Forrester coverage, check Gartner Peer Insights and Forrester Wave reports; if no Wave covers your sub-category yet, track when the next one is likely and ensure your analyst relations team is engaged.
Signal 2: Third-party editorial citations
The majority of AI citations come from third-party sources, not the brand’s own website. Studies consistently place the share of citations from external sources above 75%. In cybersecurity, that means security news publications (Dark Reading, SC Media, CSO Online, The Hacker News), independent analyst blogs, and practitioner community content.
What to check: Search for your brand name in these publications. If you have no coverage in the past 12 months mentioning you in your primary sub-category, you have an earned-citation gap. PR and media relations is the fix, not new blog posts.
Signal 3: Owned-content retrievability
Your pages need to be retrievable and readable by AI engines. A page that is technically crawlable but loads behind JavaScript rendering, redirects AI user agents, or sits behind a login is not contributing to your citation potential.
What to check: Confirm that the pages most likely to appear in a buyer-intent response (your product category pages, comparison pages, and key integrations pages) load cleanly as plain HTML. Check your robots.txt for disallows that might block AI crawlers. Confirm your primary category pages use the same terminology a buyer uses in a prompt.
Signal 4: Prompt coverage gaps
Prompt coverage is the ratio of buyer questions you appear in versus the total set of questions buyers ask in your space. A brand with strong EDR citations might have zero prompt coverage for “endpoint security for remote workforces” or “EDR for Mac environments” even though both are live buyer queries.
What to check: Extend your prompt set to include variant phrasings. Focus on vertical-specific queries (“EDR for financial services,” “CSPM for healthcare”), use-case queries (“best tools for threat hunting without a SOC”), and comparison queries (“vs” prompts against your two or three largest competitors). Track which prompt variants produce no citation for your brand.
Tools for measuring cybersecurity AI share of voice
You need a platform to run this at scale rather than manually querying ChatGPT one prompt at a time.
Temso is the practical starting point for most security marketing teams. At $89/mo, it tracks share of voice, brand mentions, citations, and sentiment across eight AI engines and converts the monitoring data into a prioritised action queue inside the same subscription. The five-minute setup and broad engine coverage make it accessible to teams without a dedicated AEO analyst, and the built-in workflow closes the loop from data to fix without requiring a separate tool stack.
Profound ($399/mo at the Growth tier) provides the deepest citation attribution in the category. Its Prompt Volumes feature shows which questions real buyers are actively asking AI engines, not just a manually curated set. For security brands running structured quarterly AI-visibility reporting to a CISO or CMO, Profound’s citation maps and GA4 integration make the evidence credible.
Scrunch AI ($250/mo) adds SOC 2 Type II compliance and its Agent Experience Platform (AXP) technology, which serves AI-optimised content directly to LLM crawlers without changing the human-facing site. Enterprise security brands subject to their own stringent procurement requirements will appreciate the security posture. For the content retrievability signal, Scrunch’s site auditing is also directly applicable.
Evertune specialises in longitudinal share-of-voice tracking across AI platforms, which matters for cybersecurity brands trying to measure whether a PR campaign or analyst-relations push has shifted their citation rate over a quarter.
The full ranked list of tools is at /rankings/ai-visibility-tools.
What to do with your diagnostic results
Once you have completed the four-signal diagnostic and the zero-citation checklist, prioritise in this order.
First: fix your G2 presence if you are absent or under-reviewed in any zero-citation category. This is the fastest path to establishing a retrievable citation signal. Analyst coverage takes longer to earn but the same principle applies: get named in the sources AI engines retrieve before anything else.
Second: build earned editorial coverage in the publications AI engines pull from for cybersecurity. One well-placed byline in Dark Reading or SC Media that names you in a specific sub-category produces more citation value than ten new blog posts on your own domain.
Third: audit content retrievability. Run your primary product pages through a plain-text render test. Confirm AI crawlers are not blocked. Ensure your category language matches buyer prompt phrasing exactly. These are technical checks, not content investments, and they remove friction immediately.
Fourth: expand your prompt coverage. Once you have a presence signal in place, build content that closes specific prompt-coverage gaps. Focus on under-served variants: vertical-specific queries, use-case queries, and comparison queries against named competitors. These are the prompts where a mid-tier brand can earn citations that market leaders have not yet claimed.
Tracking progress
Once you have run the baseline, track week-over-week drift on the same prompt families rather than chasing a single snapshot. Absolute citation numbers matter less than the direction of change over a quarter.
Set up prompt families for each of your three or four primary sub-categories. Run five responses per prompt. Record which brands appear. Calculate your citation rate and share of voice. Repeat weekly. A move from zero to a consistent 20% citation rate on a prompt family over eight weeks is a meaningful signal that your source-coverage work is landing.
Document which actions preceded which changes. That mapping is what tells you whether your G2 review push, your analyst briefing, or your editorial placement was the catalyst. See /methodology for how to structure a repeatable tracking framework, and /glossary for definitions of share of voice, citation rate, and prompt family.
Start with a measurement, not a content plan
The 73% zero-citation rate in cybersecurity is not primarily a content quality problem. It is a source-coverage and share-of-voice measurement problem. Most security vendors have no data on which sub-categories produce citations, which engines mention them, or how they compare to named rivals.
Fix that first. Baseline your share of voice, identify your zero-citation categories, run the four-signal diagnostic, and then decide where to invest. You cannot fix what you are not measuring.
Temso tracks all eight major AI engines from $89/mo and gives you the monitoring data alongside a prioritised fix queue. It is the fastest way to go from no AI visibility data to a concrete diagnostic for your cybersecurity brand. Start there before committing budget to content production.