UltraProbe
9 articles about "UltraProbe".
Crypto Narrative Hype Is Not Search or AI Visibility: Use AVS to Find the Gaps, Not to Call the Next Cycle (2026)
Narrative hype and KOL reposts do not mean search or AI answers can see you. Use AVS to find the gaps. Correlation is not causation; no ChatGPT recommendation is guaranteed.
UltraProbe vs TWTools: Choosing a Free AI and SEO Website Scanner (2026)
Both are rule-based website scanners, not Semrush-style brand-mention trackers. TWTools: SEO / GEO / AEO across 18 sub-indicators, Taiwan-local signals, side-by-side comparison of up to 10 sites, PDF / CSV export. UltraProbe: SEO + AEO + AAO combined into AVS with a published formula, plus Prompt Security scanning and an npm CLI. The two scores cannot be compared, and a high score does not guarantee ChatGPT will recommend you.
Choosing an AI Visibility Tool: Brand-Mention Tracking vs Website Technical Scanning (AVS)
Products sold as "AI visibility tools" fall into at least two categories: tracking whether AI answers mention your brand, and scanning whether your website can be read by AI at all. They measure different things and their scores cannot be compared. This post gives a comparison table, three situations and which to choose, what Google and OpenAI's own documentation actually says, and where two things both called an AI Visibility Score turn out not to be the same thing.
Uploading a Selfie to ChatGPT Is Not a Filter: Your Face Is a Credential You Cannot Reset
Social feeds are full of "ask ChatGPT what I would look like as a Japanese gangster": upload a selfie, get a generated image back, then tag someone with "your turn". This is not a filter. A face is a credential that cannot be reset, consumer accounts by default allow content to be used to improve models, turning the setting off is not retroactive, and deleting a chat does not pull it back out of a training batch. With the original text of the terms, the full pipeline, the line between what can go to the cloud and what should never be uploaded, and the two paths in our own products that touch faces.
If Your Product Takes Photo Uploads, You Are Already Building a Biometric System: Four Questions for Every Image Endpoint
For people building AI products: once there is a path where a user uploads a photo and another face is generated from it, the data category is already identity material, whether the feature copy calls it a dress-up or a filter. Every upload endpoint that takes images needs four answers fixed before launch: default, scope, retention and revocation. Includes a full checklist, plus the two paths in our own products that touch faces and the work we have not finished yet.
We Defined an AI Security Standard: AASS v1.0, We Don't Sell Security, We Define It
AI Application Security Standard (AASS) is the first open standard covering AI system defense, website AI visibility, and data protection in a single framework. All tools free and open source.
We Validated AVS With 816 AI Citations: Score 75 Is the Threshold for Getting Recommended by AI
We sent 155 queries to AI search engines, collected 816 citations, and scanned 721 websites for AI Visibility Score. Finding: 60% of cited sites score B or above. Recommendation queries demand AVS 80+. What we believe is the first empirical study of AI search citation behavior.
I Scanned 25 Major Taiwan Brands: 0 Scored A, 0 Scored B, Average AEO Was 40/100
AI Visibility Score scan of 25 major Taiwan enterprises (104 Job Bank, ASUS, PChome, Cathay Bank...). Shocking: the highest score was C-grade. Average AEO was 40/100 (E-grade). Taiwan brands are nearly invisible to ChatGPT.
Prompt Injection Isn't Your Biggest Risk: We Scanned 517 AI System Prompts and Found 11 Undefended Attack Vectors
Everyone talks about Prompt Injection, but it's just 1 of 12 LLM attack vectors. We scanned 517 AI system prompts with UltraProbe and found they defend against only 3.2 of the 12 on average. Here are the other 11 you're ignoring.