PISIGuard: Protect your personal and sensitive info when you chat with AI
PISIGuard Protect your personal and sensitive info when you chat with AI demo.webm I built PISIGuard because I've been horrified at how much personal & sensitive information people (including myself) are feeding AI on daily basis. It is cumbersome to censor information by hand, so obviously very few do that at varying degrees of consistency. I wanted something practical that will hide personal & sensitive data, and of course without routing them through yet another server.
- ▪PISIGuard Protect your personal and sensitive info when you chat with AI demo.webm I built PISIGuard because I've been horrified at how much personal & sensitive information people (including myself) are feeding AI on daily basis.
- ▪It is cumbersome to censor information by hand, so obviously very few do that at varying degrees of consistency.
- ▪I wanted something practical that will hide personal & sensitive data, and of course without routing them through yet another server.
Hacker News (AI / LLM) files mainly under ai. We currently carry 3,317 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/mohamed--abdel-maksoud/pisiguard |
| Publication time | Mon, 03 Aug 2026 08:54:00 +0000 |
| Retrieval time | 2026-08-03T09:00:40.934Z |
| Last seen | 2026-08-03T09:00:40.934Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | TCm5thNNhS6u · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
PISIGuard Protect your personal and sensitive info when you chat with AI demo.webm I built PISIGuard because I've been horrified at how much personal & sensitive information people (including myself) are feeding AI on daily basis. It is cumbersome to censor information by hand, so obviously very few do that at varying degrees of consistency. I wanted something practical that will hide personal & sensitive data, and of course without routing them through yet another server. So PISIGuard runs entirely in your browser. It spots names, email addresses, phone numbers, credit card numbers, passwords, API keys, and more, replaces them with safe placeholders, then puts the real values back into the AI’s reply.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.