Security and privacy at RankEcho

What RankEcho needs for a free audit

A free RankEcho audit starts with public-domain information. The user submits a domain, and RankEcho checks public pages, AI visibility signals, prompt outcomes, cited URLs, and source patterns that can be observed without connecting private systems.

This design keeps the first audit lightweight. A brand can see where AI systems cite, mention, ignore, or replace it without giving RankEcho access to CMS, analytics, CRM, or private customer records.

• Public domain name submitted for audit.
• Optional email address for results, login, or follow-up.
• Generated prompt results and cited URLs.
• Publicly observable source domains and source categories.
• Scorecard, gap map, and fix recommendations generated from the audit.

What RankEcho does not require

RankEcho does not need broad internal access to run an initial public-domain audit. The product is intentionally built around public visibility measurement first, not private data extraction.

That does not mean paid features never use account data. It means the core AI visibility audit does not require sensitive operational systems just to diagnose whether AI engines can see and cite a public brand.

• No CMS admin access required for the initial audit.
• No Google Analytics access required.
• No Search Console access required.
• No CRM, customer database, or sales pipeline access required.
• No website passwords required.
• No raw payment-card data stored by RankEcho.

What audit data is stored

RankEcho may store audit metadata and generated results so users can view reports, generate fixes, track proof-loop re-tests, and compare changes over time. The records described here support those product functions and aggregate measurement.

Audit data can include the submitted domain, optional email, audit status, prompt outputs, cited URLs, scorecard data, source breakdowns, and fix/proof metadata.

• Domain and audit ID.
• Optional email address if provided by the user.
• Prompt set, engine, result status, and generated scorecard.
• Cited URLs, source domains, and source-type classification.
• Gap diagnosis and fix package metadata.
• Proof-loop observations when tracking is enabled.

How RankEcho handles benchmark data

Public benchmark reporting uses aggregated and anonymized patterns rather than customer-level results. RankEcho reports citation rates or off-site source dependence only for a defined cohort with the unit, configuration, collection window, exclusions, and uncertainty disclosed.

Record count alone does not make unlike audit runs, repeat domains, or a convenience sample representative of a market.

• Aggregate counts and rates, not private customer-level rows.
• Industry rows require the stated cohort, comparability, sampling, and disclosure requirements; minimum counts alone are not enough.
• Identifiable customer data is not published without permission.
• Benchmark methodology is presented separately from sales claims.
• Limitations are stated when samples are small or directional.

How RankEcho handles service credentials

RankEcho reads AI-provider, email, and Stripe credentials from server-side environment bindings. Audit and checkout forms do not request those service credentials, and browser responses do not expose them.

Stripe webhook signatures are verified before billing events can update account state.

• Service credentials are server-side inputs.
• Public configuration remains separate from private credentials.
• Browser code does not receive server API keys.
• Billing webhook events require signature verification before account updates.

Billing and payment security

RankEcho creates paid checkout and billing-portal sessions through Stripe. Its application records billing status plus Stripe customer and subscription identifiers; raw card-entry fields are not part of RankEcho's own forms.

Paid access depends on verified billing status and signed session state. Stripe webhook signatures are checked before subscription events update an account.

• Paid checkout and billing management use Stripe.
• RankEcho forms do not collect raw card details.
• Webhook signatures are verified before plan status is updated.
• Paid feature access requires an eligible billing state.

Abuse prevention and safe domain handling

RankEcho validates audit targets before making network requests. The hostname check rejects localhost, raw IP addresses, internal-name suffixes, bare host labels, and invalid hostname characters.

The application also includes request limits for public audit and tool endpoints. These controls reduce abuse risk and unnecessary provider traffic.

• Localhost, raw IP addresses, internal-name suffixes, and invalid hostnames are rejected.
• Public domain format is validated before an audit starts.
• Public audit and tool endpoints include request limits.
• Recent audit results can be reused to reduce duplicate provider calls.
• API routes are excluded from crawler discovery where appropriate.

Responsible AI visibility measurement

RankEcho measures public AI-search behavior. It should not be used to generate deceptive content, fabricate third-party support, spam communities, or manipulate AI systems with hidden claims that do not match visible page content.

Responsible GEO focuses on making truthful, useful, crawlable, and corroborated information easier for AI systems and humans to understand.

• Use schema only when it matches visible content.
• Avoid fake reviews, fake citations, or fabricated benchmark claims.
• Do not publish hidden text meant only for machines.
• Do not claim guaranteed AI placement.
• Prioritize accurate brand representation over gaming answers.

What customers should review before publishing fixes

RankEcho fix packages can make recommendations, but customers should review any content, schema, source outreach, or technical changes before publishing them. The customer remains responsible for accuracy, brand voice, compliance, and claims made on their site.

This review step is especially important for regulated industries, legal claims, health claims, financial claims, testimonials, and competitor comparisons.

• Review generated answer blocks for factual accuracy.
• Confirm schema reflects visible page content.
• Check competitor comparisons for fairness and accuracy.
• Avoid unsupported performance or revenue claims.
• Have legal or compliance review where required.

Security limitations

No public SaaS can make absolute security guarantees. The responsible position is to minimize data collection, avoid unnecessary credentials, protect secrets, verify payment events, rate-limit sensitive endpoints, and be transparent about what the product does and does not need.

Security controls and risks change with the product and threat environment. This page documents the current application safeguards and known limits.

• No system is risk-free.
• Audit outputs can include public URLs and generated text that should be reviewed.
• AI provider behavior and third-party source availability can change.
• Customers should avoid submitting confidential information into public-domain audit fields.
• Security questions should be directed to RankEcho support.

Security FAQ

Last updated 2026-09-06. RankEcho is operated by Nexus Decision Systems LLC.