Editorial Standards & Corrections

Why this page exists

Trust Onion publishes safety-sensitive content: scam alerts, case studies of real fraud incidents, and protection guides that families may act on. You deserve to know exactly who is behind that content, where the facts come from, how AI tools are involved, and what happens when we get something wrong. This page explains all of it, plainly.

How we source stories

Our blog posts and case studies are based on published news reporting from established outlets. We do not invent incidents, victims, dollar amounts, or quotes.

• Every story links to its original source. Articles and case studies display an "Originally reported by" citation at the top with a direct link to the source article, so you can verify the underlying facts yourself.
• Facts vs. analysis. Details of an incident (what happened, when, who was targeted, losses) come from the linked reporting. Sections such as "How Trust Onion Helps," "Lessons Learned," and "Key Takeaways" are our own analysis and prevention advice — they are opinion and guidance, not reported fact.
• Unknowns stay unknown. When a detail was not reported — such as the financial loss in a case — we label it "undisclosed" or omit it rather than estimating.

How we use AI

We are an AI-safety company, and we are transparent about using AI ourselves. Our editorial workflow uses large language models to help draft articles and case studies from the source reporting, and AI image tools to create the editorial illustrations on our pages. Every piece of content:

• starts from a real, linked news story — the AI drafts from that reporting, it does not invent incidents;
• passes automated checks (including filters for off-topic or low-quality stories) before publishing; and
• is published under the review and accountability of our founders, who read published output and remove or correct anything inaccurate.

Illustrations on our articles are AI-generated editorial art. They are conceptual images, not photographs of the people or events described.

Fact checking and updates

Before and after publishing, we check content against its source article. If the underlying story develops — an arrest, a correction by the original outlet, new loss figures — we update our coverage. Each article and case study shows its publish date, and an "Updated" date whenever it has materially changed after publishing.

Corrections policy

When we get a fact wrong, we fix it and say so.

• Report an error: email jt@trustonion.io with a link to the page and what you believe is wrong. We review every report.
• Factual errors are corrected in the article as soon as we confirm them, and the article's "Updated" date reflects the change.
• Serious errors — anything that misidentifies a person, misstates who was responsible for a scam, or could cause harm if acted on — result in the content being corrected immediately or unpublished while we re-verify it.
• Typos and formatting fixes are made silently; they do not change the substance of an article.

Who writes and reviews this site

Trust Onion is built and run by its two co-founders. We are not journalists, doctors, or lawyers, and we do not claim to be — we are the builders of a family verification app who track AI impersonation scams every day, and our content reflects that hands-on vantage point. Nothing on this site is legal or financial advice.