Running the sample application

A sample application to use Developer Edition.

In the Developer Edition, a user uploads a file using the sample application, which is processed by the Data Discovery container. The containers detect sensitive data. A Python module then redacts, masks, or protects and unprotects the data. The sanitized file is saved to a configured location. For more information about the sample application, refer to Sample application.

Use the steps provided here to run the application end-to-end. If required, run the APIs and functions provided for performing specific tasks. For more information about the identification APIs, refer to Data Discovery API.

Running the applications

Applications are provided out-of-the-box to test and understand the capabilities of Developer Edition.

Running the sample find application

Open a command prompt.
Navigate to the directory where Developer Edition is cloned.
Run the sample application using the following command.
```
python samples/sample-app-find.py
```
View the output of the files processed on the screen. The output displays a list of sensitive items in the source file.

“Sample application output”

View the processed output file in the output directory.

Running the sample find and redact application

Open a command prompt.
Navigate to the directory where Developer Edition is cloned.
Run the sample application using the following command.
```
python samples/sample-app-find-and-redact.py
```
View the output of the files processed on the screen. The output displays a list of sensitive items in the source file. It also displays the location and name of the output file with the redacted output.

“Sample application output”

View the processed output file in the output directory.

Running Semantic Guardrail

Open a command prompt.
Navigate to the directory where Developer Edition is cloned.
Run the following command to test Semantic Guardrail. The following command submits a multi-turn conversation for analysis. One for semantic and a second one for PII processing.

python semantic-guardrail/sample-guardrail-python.py

“Sample application output”

Running the sample find and protect application

Ensure that the required credentials are obtained and environment variables specified, using the steps from Optional - Obtaining access to the Developer Edition API Service.
Open a command prompt.
Navigate to the directory where Developer Edition is cloned.
Run the sample application using the following command.
```
python samples/sample-app-find-and-protect.py
```
View the output of the files processed on the screen. The output displays the protected data and unprotected data.

“Sample application output”

View the processed output file in the output directory. The samples/sample-data/output-protect.txt file is generated with the protected, that is tokenized-like, values.
To obtain the original data, run the following command.
```
python samples/sample-app-find-and-unprotect.py
```
This reads the samples/sample-data/output-protect.txt file and produces the samples/sample-data/output-unprotect.txt file with original values.

Running the script for protecting data

The sample-app-protection.py showcases the various scenarios for protecting, unprotecting, and reprotecting data.

Understanding Users and Roles

The users and roles are built-in for impersonate testing. Leverage any of the preconfigured users to showcase Protegrity’s Role-Based Access Controls. Using a different user will result in distinct views over sensitive data. Some users will only be able to protect data but will not be able to reverse the operation. Some users will only be able to re-identify selected attributes.

To use any of the roles, simply pass the chosen value to the payload in the user attribute during the protect or unprotect operation. If the user is not specified, the request will default to superuser.

The following roles and users have been configured and are available for use:

Role	User	Description
ADMIN	`admin`, `devops`, `jay.banerjee`	The role can protect all data but cannot unprotect. Upon an unprotection attempt they will be displayed protected values.
FINANCE	`finance`, `robin.goodwill`	The role can unprotect all PII and PCI data. The role cannot protect any data. When attempting to unprotect data without authorization, they will be displayed nulls.
MARKETING	`marketing` , `merlin.ishida`	The role can unprotect some PII data that is required for analytical research and campaign outreach. When attempting to unprotect data without authorization, they will be displayed nulls. The role cannot protect any data.
HR	`hr` , `paloma.torres`	The role can unprotect all PII data but cannot view any PCI data. When attempting to unprotect data without authorization, they will be displayed nulls. The role cannot protect any data.
OTHER	`superuser`	The role can perform any protect and unprotect operation. The role has been made available for testing only – we strongly advise against creating superuser roles in your environments.

Additionally, you may type in any user name to simulate unauthorized user behavior.

Understanding the Data Elements

A list of supported data element is provided here. For a mapping of the Data Element and the Entity Type, refer to Supported Sensitive Entity Types.

Name	Description
name	Protect or unprotect name of a person
name_de	Protect or unprotect name of a person in the German language
name_fr	Protect or unprotect name of a person in the French language
address	Protect or unprotect an address
address_de	Protect or unprotect an address in the German language
address_fr	Protect or unprotect an address in the French language
city	Protect or unprotect a town or city
city_de	Protect or unprotect a town or city name in the German language
city_fr	Protect or unprotect a town or city name in the French language
postcode	Protect or unprotect a postal code with digits and characters
zipcode	Protect or unprotect a postal code with digits only
phone	Protect or unprotect a phone number
email	Protect or unprotect an email
datetime	Protect or unprotect all components of a datetime string date, month, year, and time
datetime_yc	Protect or unprotect a datetime string. Year will be in clear.
int	Protect or unprotect a 4-byte integer string
nin	Protect or unprotect a National Insurance Number UK
ssn	Protect or unprotect a Social Security Number US
ccn	Protect or unprotect a Credit Card Number
ccn_bin	Protect or unprotect a Credit Card Number. Leaves 8-digit BIN in the clear.
passport	Protect or unprotect a passport number
iban	Protect or unprotect an International Banking Account Number
iban_cc	Protect or unprotect an International Banking Account Number. Leaves letters in the clear.
string	Protect or unprotect a string
number	Protect or unprotect a number
text	Protect or unprotect text using encryption

Testing the sample file

Ensure that the required credentials are obtained and environment variables specified, using the steps from Optional - Obtaining access to the Developer Edition API Service.
Open a command prompt.
Navigate to the directory where Developer Edition is cloned.

Protect data using the following command.

python samples/sample-app-protection.py --input_data "John Smith" --policy_user superuser --data_element name --protect

Unprotect the data obtained from the earlier step using the following command.

python samples/sample-app-protection.py --input_data "<protected_data>" --policy_user superuser --data_element name --unprotect

View the protected and unprotected output.

Encrypt data using the following command.

python samples/sample-app-protection.py --input_data "John Smith" --policy_user superuser --data_element text --enc

Decrypt the data obtained from the earlier step using the following command.

python samples/sample-app-protection.py --input_data "<encrypted_data>" --policy_user superuser --data_element text --dec

View the encrypted and decrypted output.
Use the help command for more information about using the sample file.
```
python samples/sample-app-protection.py --help
```

Additional use cases for user role behavior for data protection

This section demonstrates the expected behavior of various user roles when running the sample-app-protection.py. Each section describes the permissions and restrictions for a role, followed by example commands and their outputs.

ADMIN

Users: admin, devops, jay.banerjee

This role can protect all data but cannot unprotect. When attempting to unprotect, protected values are displayed.

python sample-app-protection.py --input_data "4321567898765432" --policy_user admin --data_element ccn --protect --unprotect

Protected Data: 2839874358655598
Unprotected Data: 283987435865559

python sample-app-protection.py --input_data "4321567898765432" --policy_user devops --data_element ccn --protect --unprotect

Protected Data: 2839874358655598
Unprotected Data: 283987435865559

python sample-app-protection.py --input_data "4321567898765432" --policy_user jay.banerjee --data_element ccn --protect --unprotect

Protected Data: 2839874358655598
Unprotected Data: 283987435865559

FINANCE

Users: finance, robin.goodwill

This role can unprotect all PII and PCI data. The role cannot protect any data. When attempting to unprotect data without authorization, the value Null is displayed.

python sample-app-protection.py --input_data "Protegrity$" --policy_user finance --data_element name --protect

Error: 3, The user does not have the appropriate permissions to perform the requested operation.

python sample-app-protection.py --input_data "Protegrity$" --policy_user robin.goodwill --data_element name --protect

Error: 3, The user does not have the appropriate permissions to perform the requested operation.

python sample-app-protection.py --input_data "1998/10/11" --policy_user finance --data_element datetime  --unprotect

Unprotected Data: None

python sample-app-protection.py --input_data "1998/10/11" --policy_user robin.goodwill --data_element datetime  --unprotect

Unprotected Data: None

MARKETING

Users: marketing, merlin.ishida

This role can unprotect some PII data that is required for analytical research and campaign outreach. The role cannot protect any data. When attempting to unprotect data without authorization, the value Null is displayed.

python sample-app-protection.py --input_data "Washington, D.C." --policy_user marketing --data_element city --protect

Error: 3, The user does not have the appropriate permissions to perform the requested operation.

python sample-app-protection.py --input_data "Washington, D.C." --policy_user merlin.ishida --data_element city --protect

Error: 3, The user does not have the appropriate permissions to perform the requested operation.

python sample-app-protection.py --input_data "DnZQHKcpVJ, J.G." --policy_user marketing --data_element city --unprotect

Unprotected Data: Washington, D.C.

python sample-app-protection.py --input_data "DnZQHKcpVJ, J.G." --policy_user merlin.ishida --data_element city --unprotect

Unprotected Data: Washington, D.C.

Users: hr, paloma.torres

This role can unprotect all PII data but cannot view any PCI data. The role cannot protect any data. When attempting to unprotect data without authorization, the value Null is displayed.

python sample-app-protection.py --input_data "John Doe" --policy_user hr --data_element name --protect

Error: 3, The user does not have the appropriate permissions to perform the requested operation.

python sample-app-protection.py --input_data "John Doe" --policy_user paloma.torres --data_element name --protect

Error: 3, The user does not have the appropriate permissions to perform the requested operation.

python sample-app-protection.py --input_data "CIF123654987" --policy_user hr --data_element passport --unprotect

Unprotected Data: None

python sample-app-protection.py --input_data "CIF123654987" --policy_user paloma.torres --data_element passport --unprotect

Unprotected Data: None

OTHER

User: superuser

This role can perform any protect and unprotect operation. The role is only made available for testing. It is strongly advised against creating superuser roles in an environment.

python sample-app-protection.py --input_data "4321567898765432" --policy_user superuser --data_element ccn --protect --unprotect

Protected Data: 2839874358655598
Unprotected Data: 4321567898765432

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Last modified : September 26, 2025

Running the sample application

Running the applications

Running the sample find application

Running the sample find and redact application

Running Semantic Guardrail

Running the sample find and protect application

Running the script for protecting data

Understanding Users and Roles

Understanding the Data Elements

Testing the sample file

Additional use cases for user role behavior for data protection

Data Discovery API

Semantic Guardrail APIs

Application Protector Python APIs

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