A CISO evaluating an identity platform does not start with a sales call. They start with a prompt.

Long before a security buyer fills out a demo request, they have asked ChatGPT to compare vendors in the category, asked Perplexity which platforms meet a specific compliance requirement, and checked whether Microsoft Copilot surfaces a vendor they are already considering. By the time they talk to a human, the AI-curated shortlist is already formed. If a vendor is not on it, the sales team never knew the opportunity existed.

In part one of this series, I made the architectural argument for why GEO has to be vertical. This article is the proof by example. I am going to walk through what GEO actually looks like for cybersecurity buyers specifically – drawing on what we have learned building a GEO platform for this exact audience – because the gap between generic GEO advice and what works for security buyers is wide enough to lose deals through.

How Security Buyers Actually Use AI to Research Vendors

Security buyers are unusually heavy users of AI research tools, and they use them in a distinctive way. Three patterns stand out.

They research before they reveal themselves. Security teams operate with a default posture of not tipping their hand. They do not want a dozen vendor sales reps in their inbox the moment they start evaluating a category. AI research lets them do most of the evaluation anonymously. They build a shortlist, narrow it, and develop pointed questions before a single vendor knows they are in market. This makes AI visibility more consequential in security than in categories where buyers engage sales earlier.

They research with precision, not breadth. A marketer might ask “best email tools.” A security buyer asks something with five embedded constraints: deployment model, compliance framework, integration requirements, scale, and threat model. The prompts are dense with technical and regulatory specificity because the buyer is technical and the requirements are non-negotiable. Vague positioning content cannot satisfy a precise prompt.

They cross-check across models and sources. Security professionals are, by training, skeptical. They do not take a single AI answer at face value. They run the same question across ChatGPT, Perplexity, and Copilot, and they check whether the AI’s claims hold up against sources they independently trust. This means a vendor needs consistent presence across platforms and credible third-party validation, not just one strong channel.

The practical consequence: in cybersecurity, the buyers using AI for vendor research are exactly the buyers you most want, asking exactly the questions that reveal whether you belong on their shortlist. Getting GEO right here is not a marketing nicety. It is upstream of the entire pipeline.

The Prompt Patterns That Matter in Security

The single biggest difference between generic GEO and cybersecurity GEO is the prompts. Security buyers ask questions that a keyword tool would never surface, because they are not keywords. They are precise, constraint-laden queries that reflect how security people think.

Consider the difference between these two ways of asking about the same product category:

A generic prompt: “best identity management platform”

A security buyer’s prompt: “CIAM platform with FIDO2 passkey support and SCIM provisioning that meets SOC 2 Type II and supports FedRAMP for a healthcare SaaS handling PHI”

The second prompt is the one that actually gets typed by the buyer you want. It carries five distinct constraints, each of which the AI system has to satisfy from its sources. A vendor optimizing for the generic version will be invisible for the specific version, which is the version that converts.

The prompt patterns in security cluster around recognizable axes:

Compliance-anchored prompts. “Which CIAM vendors are FedRAMP authorized?” “Identity platform that supports HIPAA and GDPR for a multi-region deployment.” Compliance is often the first filter a security buyer applies, and AI systems answer these prompts by pulling from compliance documentation, certification listings, and vendor trust pages.

Architecture-anchored prompts. “Zero-trust identity solution that integrates with existing SIEM and supports SAML and OIDC.” Security buyers think in architecture. They want to know how a solution fits their stack and their security model before they care about features.

Threat-model-anchored prompts. “Authentication solution resistant to phishing and session hijacking.” The buyer is reasoning from the attacks they need to prevent backward to the solution, not from the feature list forward.

Comparison prompts with constraints. “Compare Okta vs Ping vs ForgeRock for a regulated financial services environment.” The comparison is never abstract. It is always scoped to the buyer’s specific situation.

A GEO approach that generates and tracks these prompt patterns is doing something a horizontal tool structurally cannot, because surfacing these prompts requires knowing how security buyers reason. That knowledge has to be encoded into the system, not derived from search volume.

Which Sources LLMs Actually Trust in Security

When an AI system answers a cybersecurity prompt, the sources it pulls from are not the sources it pulls from for a general business query. This is the crux of why authority is domain-specific, and it has direct consequences for what content actually earns citations.

Across the cybersecurity domain, AI systems weight a recognizable set of source types more heavily:

Primary research and original data. Security practitioners trust original research – threat reports, vulnerability analyses, original benchmark data. A vendor that publishes genuine primary research on, say, the prevalence of a specific attack pattern earns citations that a vendor recycling generic content never will. Models learn which sources produce findings that get referenced by other credible sources, and in security, original research is the strongest such signal.

Framework and standards documentation. Content that engages seriously with NIST frameworks, OWASP guidance, ISO standards, and compliance requirements gets cited because these are the reference points security answers are built on. A vendor whose content maps clearly to recognized frameworks is more citable for the compliance-anchored prompts that dominate security research.

Named technical experts. Security is a field where individual credibility matters enormously. Content published under the byline of a named, credentialed security expert carries more weight than anonymous corporate content. This is part of why thought leadership from identifiable practitioners outperforms faceless content marketing in this vertical specifically.

Technical community presence. Security buyers validate vendors in specific communities, and AI systems increasingly pull from them. The research consistently shows community and forum content carries real citation weight, but in security the communities that matter are specific ones, not general forums.

The implication for content audit is sharp. A generic audit would tell a security vendor their content needs better structure and more FAQ schema. Those are not wrong, but they are not the binding constraint. The binding constraint for most security vendors is that they have no primary research, no named experts publishing under their own names, and no credible engagement with the frameworks their buyers care about. An audit calibrated to security surfaces those gaps. A generic audit never sees them.

A Worked Example: Auditing a Security Vendor for GEO

To make this concrete, consider how a vertical content audit differs from a generic one for a hypothetical CIAM vendor.

A generic GEO audit produces findings like: pages lack FAQ schema, paragraphs are too long for extraction, comparison tables are missing, content is not updated frequently enough, headings are not phrased as questions.

All true. All worth fixing. None of it touches the reason the vendor is losing AI citations to competitors.

A security-calibrated audit produces different findings: the vendor has no published primary research that security practitioners cite, so models have no original work to attribute to them. Their content discusses features but does not map to NIST or compliance frameworks, so they are invisible for compliance-anchored prompts. No content is published under named expert bylines, so the vendor has no individual-authority signal in a field where that matters. They have no presence in the technical communities where security buyers cross-validate, so the third-party signal is absent. Their content answers “what does our product do” rather than the threat-model and architecture questions buyers actually ask.

These two audits describe the same website and reach almost completely different conclusions about what to fix. The generic audit optimizes the packaging. The vertical audit identifies that the substance, judged by what security buyers and the models serving them actually value, is the problem. Fixing the packaging while ignoring the substance moves the needle slightly. Fixing the substance is what gets a vendor cited.

This is the entire argument of this series, made concrete. The same content, audited against two different rubrics, yields two different roadmaps. For a vendor selling to CISOs, only one of those roadmaps reflects what their buyers respond to.

What Security Vendors Should Do About It

If you sell security or identity products to technical buyers, the path to AI visibility runs through becoming genuinely more citable to the audience and the models serving them. A few concrete priorities:

Publish primary research. Original data and analysis is the highest-impact content a security vendor can produce for GEO. It earns citations, it gets referenced by other credible sources, and it signals to models that you produce work worth attributing. One genuine research piece outperforms ten generic blog posts.

Map content to frameworks explicitly. Make the connection between your solution and the standards your buyers care about explicit and structured. This makes you citable for the compliance-anchored prompts that dominate security research.

Put named experts forward. Have credentialed people publish under their own names. Individual authority is a real and underused signal in security, and it compounds over time as those experts get cited and recognized.

Build presence where security buyers validate. Engage credibly in the technical communities your buyers actually use. The third-party signal matters, and in security it comes from specific places, not generic ones.

Track the prompts your buyers actually ask, across models. Given the low citation overlap between platforms, you need to know where you stand on the specific, constraint-laden prompts that matter in security, on each model independently. Aggregate visibility numbers hide the platform-specific reality.

None of this is achievable with a generic optimization checklist, because the checklist optimizes for the average buyer and the average buyer does not exist in security. The buyer is a specific CISO with specific constraints asking a specific model a specific question. GEO that works in this vertical is GEO calibrated to that reality.

Part three of this series turns this into a practical evaluation tool: a checklist for assessing whether any GEO solution actually fits your vertical, so you can tell the difference between deep domain fit and generic monitoring with a vertical label.

• Why GEO Has to Be Vertical: part one, the architectural argument
• FIDO2 Implementation Guide: the kind of technical depth security buyers expect
• Password Hashing Comparison: primary technical content that earns citations
• SHA-2 Family Explained: framework-anchored technical reference
• Top 5 GEO Tools of 2026 Compared: the platform landscape

The post What GEO Looks Like for Cybersecurity Buyers: CISOs, CIOs, and Security Teams appeared first on Deepak Gupta's notebook.

*** This is a Security Bloggers Network syndicated blog from Deepak Gupta's notebook authored by Deepak Gupta. Read the original post at: https://guptadeepak.com/what-geo-looks-like-for-cybersecurity-buyers-cisos-cios-and-security-teams/