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Վերադառնալ բլոգինAI Անվտանգություն

Տekhnikakan Verahskoghoutyounits Zourgatsvats AI Quaghaqakanutounydzakhogvum e

Ashkhatakazneri 77%-n AI gortsiknerov kazum e zgayun ashkhatankayin tvyal shabat-ar-shabat, angage argeloch quaghaqakanutounnerun: Petakan kapalary FEMA-i jrhegheloutyan ognutyan dimumneri tvyaln kptstrets:

April 4, 20268 րոպե կարդալ
AI data governancetechnical controlsChatGPT policy failureChrome Extension DLPenterprise AI security

Yerp Quaghaqakanutouny Handipnoum e Irakal Varky

Petakan kapalary tchapin ner: Ayn ouner FEMA-i jrhegheloutyan ognutyan dimumnerum ushan avatskoum: Ayn ChatGPT-oum kptstrets anunner, hastseagrer yev bzhishkayin grarounner aveli shoutapest sharjvelou hamar: Nra metkoum vor voch mek orens chi khakhtel: Oonjaky ogtagertsnoum er dzerk-n ners lavaguyn gortsiky:

Ardyounky: Petakan hetaqnnoum yev hayrapetakan batsahoum:

Sa e miayn-quaghaqakanutyan AI kavaroumani himnayin ankaroughoutouny: Quaghaqakanutounner-n ashkhatakatsineri assoum en te inch anel: Drain vark-n chen kastsnoum:

Entserapetakan ashkhatakatsineri 77%-n AI gortsiknerov kazum e zgayun ashkhatankayin tvyal shabat-ar-shabat — nuyniski yerp quaghaqakanutounn-n argeloum e (eSecurity Planet/Cyberhaven 2025): Sarank bavakar ashkhatakatsynner chen: Zhamanakayin chapanin ner arshtpantsogh mardik en, ov shoutapestum en amsena arjnagoy gortsik-n kiredsneloum:

Inch Amou Quaghaqakanutounner-n Khochtum en

AI-i karoghoutyoun quaghaqakanutounner-n apeloom en mardkoutyan djoukhoutyoun-n moutkagri kadetsoum: Ayd punts artshag e: Ashkhatakatsin karogi e chhishar quaghaqakanutounn-n: Ayn karogi e bovandaloutyouny "zgayun" chi tesnel: Karogi e risky entounel vorovic yamanakayin pashtoum shrounakneri mets e toum:

Cyberhaven-i Q4 2025 verloutsoutyouny parzel e, vor ChatGPT-i bolor moutkagnouteri 34.8%-n poutsoom e gakhtnavayr biznesayin teghekouytyoun: Ayd ogtataghner-i shaterin gitein quaghaqakanutounn-n: Kptstretsn amena-yevs:

Moutkagi quaghaqakanutounner-n ashkhatum en, vorovic hamakargern-n kaghkararooum en: E-posti DLP-n ashkhatum e, vorovic hamakargern-n kaghkararooum en: AI-i karoghoutyoun quaghaqakanutounner-n kptsoumy kadetsum kaghkararoutyoun chunen: Mardkoutsayin qndasoutyoun-n letsnoum e ayd bachn: Mets masshtabov mardik skhaloum en:

FEMA-i kapalary ayd skhaloumneri meden ares: Ayn vat droyak char: Gortsik-n hartsets, vorovic quaghaqakanutounn-n nran khndrets yntrel dandaghoutyoun-n arjandoutyouni poxharen: Tchapin ner-en, yntrets artshagoutyounn:

Teknikakan Verahskoutyounner-n Kastsnoum en Ayn Inch Quaghaqakanutounn-n Chi Karogi

Mets masshtabov ashkhataghoghe miak oushrjoumy teknikal shartoom e ashkhatum, voch te ousoutsankayin shartoom:

Browser-i erkaratsman-n karogi ndhat clipboard-i bovandaloutyounn veb-hasnvats AI-i araj chhasneli: Yerp kapalary patouhatsum yev ChatGPT-oum kptstroum e dimumchi anunner yev hastseagrer, erkaratsman-n haytnabernoum e PII-n, ananounovum ayn yev ugharkoum mak tarbarake: AI-n tesnoum e [NAME_1] yev [ADDRESS_1] irakal arazhekhneri poxharen: Ayn amena-yevs katarooum e ardyounky: Dimumchi andznakin tvyaln yerbeq ChatGPT-i servernerum chi haraghenoum:

Sa avtomatik e: Ayn ogtataghits voch mi dzev hishel chi patahoom:

Cursor kam GitHub Copilot-n kortsatsogh tsragravorneri hamar MCP Server-n apaminarekooum e nooyn shartn: AI-i hamtekstooum kptstats kody antsnoum e ananounatsman sharjchov: Credential-nery yev sorovakan nshanoghichner-n darnoum en tokens: AI-n stanoum e mak moutkagir yev amena-yevs tar yev ardiounkaberoutyoun e tarooum:

Tesek te inch es tarbakakoum e argelooumits: Argeloum ynddim Ananounatsman — Browser DLP Hamapokhvatsvats:

Inch e Pokhokhvoom Teknikakan Verahskoutyounnerov

Browser-i erkaratsmanov FEMA-i kapalary-i stsenarow ayls kes e antsnoum:

  1. Kapalary patouhatsum e dimumchi grarounner gortsagranin hamakargits
  2. Erkaratsman-n clipboard-oum haytnaberooum e PII
  3. Nakhatatesi modal tsuyts e tarooum te inch ke pokhokhvi
  4. Ananoum tarbarake ugharkoum e ChatGPT
  5. ChatGPT-n mshakooum e hartsoumn yev vandrooum ardiounknern
  6. Kapalary stanoum e anhraje ognooutyounn — voch mek hetaqnnoum chi sksvoum

Quaghaqakanutounn-n pokhokhel karios chegav: Ousoutsoumy antskatsel karios chegav: Ndhatayin shartny kararavel e:

Quaghaqakayin ousoutsoumy-n nvazetsoum e risky seranich-seranich: Teknikakan verahskoutyounner-n veriatsnoum en dzakhoghoum-i rezim: FEMA-i depqy quaghaqakayin dzakhoghoutyoun er: Ayn voch-depq kel er, ete ayd kapalary-i sarkooum tarkarvarats ler mek Chrome Extension:

Tesek nayev:

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About this page

We update this page when our platform or the law changes.

Read our founder note for how we work.

Each change shows up in the timestamp at the top.

Related reading

We follow these rules

  • GDPR (EU 2016/679).
  • ISO/IEC 27001:2022.
  • NIS2 (EU 2022/2555).
  • HIPAA safe harbor under 45 CFR § 164.514(b)(2).

Our promise

We do not sell your data.

We do not train models on your text.

We store your files in Germany.

You can delete your account at any time.

You own your work.

Where we run

Our servers live in Falkenstein, Germany.

We use Hetzner. They hold ISO 27001 certification.

All data stays in the EU.

Backups run every day.

Need help?

Email support@anonym.legal.

We reply within one business day.

How we test

We run a full check suite on every release.

Each surface gets its own sweep script and report.

Human reviewers spot-check the output each week.

We track recall and precision on a labelled set.

Bad runs block the deploy.

What we never do

  • We never sell your information to third parties.
  • We never train models on what you upload.
  • We never keep your work after you delete it.
  • We never share keys with any outside firm.
  • We never run ads inside the product.

Plans in plain words

We sell credits, not seats.

One credit covers one short job.

Long jobs use a few credits each.

You can top up at any time.

Unused credits roll over each month.

Read the plans page for current rates.

Who built this

A small team of engineers and lawyers built this.

We ship from Europe and work in the open.

Our founder note spells out why we started.

Where to start

How the parts fit

A browser add-on cleans text inside Chrome.

A Word plug-in handles drafts in Office.

A small desktop tool works on whole folders.

An agent protocol link feeds large models safely.

All four share one core engine and one rule set.

Words from our team

We started this work after a lunch about cookies.

One friend kept getting odd ads on her phone.

We asked why a court file leaked through a draft.

We sketched the first build on a napkin that week.

By month three we had a tiny demo for a friend.

She used it on her first case the next day.

Common questions we hear

Can the tool read scanned PDFs? Yes, with OCR.

Does it work on long files? Yes, in small chunks.

Can I roll my own rule set? Yes, save it as a preset.

Does it run offline? The desktop build runs offline.

Do you keep my files? No, the cloud build wipes after each run.

Will it learn from my work? No, we never train on inputs.

A short tour of the workflow

Upload a file or paste a snippet of prose.

Pick the entities you want gone from the draft.

Choose a method: replace, mask, hash, encrypt, or redact.

Press run and watch the side panel show each hit.

Skim the result and tweak any rule that misfired.

Save the cleaned file or send it to a teammate.