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Atgal į BlogąAI Saugumas

Imones DI: Kuretojo Prieiga Be Rizikos

Bankai uzdraudze ChatGPT. Ju kurejjai namuose naudojo ji bet kokiu atveju. 27,4% viso turinio, paduodamo i imones DI pokalbiu robots, turi jautriu duomenu (Zscaler).

April 6, 20269 min skaityti
enterprise AI banAI governanceMCP Server enterpriseZscaler AI data riskdeveloper AI policy

DI Draudimas, Kuris Atsisuko

Didziosios imones uzdraudte viesas DI priemones. JPMorgan, Deutsche Bank, Wells Fargo, Goldman Sachs, Bank of America, Apple ir Verizon tai padarydavo. Draudimai atejo po tikriuju duomenu atskleidimo incidentu. Reguliuotojai ne rijojo del konfidencialiu duomenu, einanciu i isorine DI teikeju.

Draudimai problemos neissprende.

LayerX 2025 m. analize nustate, kad 71,6% imones DI prieigos dabar vyksta per ne-imones paskyras. Darbuotojai naudoja ChatGPT, Claude ir Gemini per asmenines paskyras. Jie tai daro imones irenginiuose. Jie taip pat naudoja asmeninius irenginus darbo tikslams. DI draudimas sukure sokio DI ekosistema. IT neturi matomumo i ja. DLP valdikliai jos nepasiekia. Atitikties stebesena negali jos sekti.

Zscaler 2025 m. Duomenu Rizikos Ataskaita pateike skaiciu zalos dydyje. 27,4% viso turinio, paduodamo i imones DI pokalbiu robots, turi jautriu duomenu. Tai yra 156% padidejimas lyginant su praejusiais metais. Padidejima turi dvi priezastys. DI priemoniu priemimas isplate. Sokio DI migracija aplenko bet kokia esamu stebejima.

Kodel Draudimai Blogina Situacija

Konkurencinis spaudimas paaiskinima sokio DI priemima. Kurejjai imoniuose, leidzeianciose DI, grescia problemas greiciau. Jie razo dokumentus greiciau. Jie prototipuoja greiciau. Kurejjai JPMorgan, kurie laikosi draudimo, susiduria su tikru nasumas atsilikimu.

Esant tokioms salygoms, atitinkantis kelias reikalauja pastangu. Naudoti DI is asmenines paskyros yra paprasta. Kiekvienas atskiras pasirinkimas yra racionalus. Zmogus taupo laika. Bendras poveikis yra priesinga tikslo. DI naudojimas tesiasi didesniu mastu. Jis vykdomas visipusiskai nestebimame kanale.

Tai yra imones DI paradoksas. Draudimas buvo skirtas apsaugoti jautriems duomenims. Vietoj to jis stumia DI naudojima i kanalus, kuriuose duomenu apsauga yra neimanova.

MKP Architektura Issprend ia Paradoksa

Sprendimas yra valdiklis, kuris leidzia DI naudojima vietoj jo blokavimo. MKP Serveris situa tarp DI kliento ir modelio API. Visi raginti pereina per anonimizavimo varikliu pries butu issiusti. Jautrus duomenis yra pakeiciami zzzetonais. Modelis gauna reikiama konteksta. Jis niekada nemato kredencialiu, AAS ar savitu identifikatoriaus.

Imkime CISO Vokietijos automobilio gamintojoje. Ji turi irodyti DI kodavimo priemones 500 kurejju. Ji taip pat turi laikytis BDAR. MKP Serveris perstverti savitins algoritmus pries jie pasiekia Claude arba GPT-4 serverius. Saugumo komanda gali patvirtinti DI priemoniu naudojima. Jautrus turinys nepalieka imones tinklo be anonimizavimo. Kurejjai naudoja Cursor kaip anksceiau. Audito zurnalas rodo, kas buvo persverti ir pakeista.

Imone issprend ia pasirinkima. DI priemones yra leidziamos. Techninis sluoksnis priverstinai vykdo duomenu apsauga. Sokio DI kripta, nes darbuotojai turi patvirtinta, stebima kanala. Tas kanalas suteikia ta pati nasumas pranasumo. CISO gauna valdiklius ir audito zurnalas. Kurejjai gauna DI prieiga.

Paradoksas dingsta. Imone gauna abu: kuretojo nasumas ir tikra duomenu apsauga.

Taip pat ziurekite: Kaip MKP Serveris tvarko AAS sauguma ir Samsung ChatGPT draudimo tyrimo atvejis del realiojo pasaulio konteksto apie imones DI draudimus.

Saltiniai

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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.
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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.