Como encobrir dados sensíveis usando a API DLP avaliações

Yevhen P. · Revisado há almost 7 years

5

narongsak s. · Revisado há almost 7 years

5

narongsak s. · Revisado há almost 7 years

Shakti M. · Revisado há almost 7 years

Vicente C. · Revisado há almost 7 years

Click on the dlp-input.png file to display the image doesn't actually show you the image in the new cloud shell editor. I had to download the .png file to view it locally instead.

Michael T. · Revisado há almost 7 years

the instructions should cover on how to view the redacted image. Like go to downloads, copy the file name and download it to view the redacted part

Sunderson S. · Revisado há almost 7 years

Thomas C. · Revisado há almost 7 years

Richard F. · Revisado há almost 7 years

Manoj N. · Revisado há almost 7 years

Stacy V. · Revisado há almost 7 years

Image was rendering in binary in the code editor as opposed to what the exam was dictating

Nikolas K. · Revisado há almost 7 years

LTI S. · Revisado há almost 7 years

Akshaye K. · Revisado há almost 7 years

Rakesh T. · Revisado há almost 7 years

Orlando J. · Revisado há almost 7 years

Alexander L. · Revisado há almost 7 years

Cloud Shell old version works with dlp-input.png, new one does not: �PNG  IHDR�
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Walter A. · Revisado há almost 7 years

Eric M. · Revisado há almost 7 years

Punith L. · Revisado há almost 7 years

Lab bombs out (Listed commands error out, do not function) beginning @Task2. step 6: Run the following command to install the required dependencies. npm install @google-cloud/dlp npm install yargs npm install mime Task 3. Inspecting and redacting sensitive data Inspect a string for sensitive information In Cloud Shell run the following command: node inspect.js string "My email address is joe@example.com." You should receive the following output: Findings: Quote: joe@example.com Info type: EMAIL_ADDRESS Likelihood: LIKELY The result shows what sensitive data was found, what type of information it is, and how certain the API is about that info type. In Cloud Shell run the following command: node inspect.js string "My phone number is 555-555-5555." You should receive the following output: Findings: Quote: 555-555-5555 Info type: PHONE_NUMBER Likelihood: VERY_LIKELY

Brian M. · Revisado há almost 7 years

Julio Q. · Revisado há almost 7 years

Gaurav S. · Revisado há almost 7 years

good lab

Andrew G. · Revisado há almost 7 years

Great!

Jean-Remi P. · Revisado há almost 7 years