Home Top

• Overview of the Document Classification System
• Understanding Classification vs key Word Searching
• Best Practise (Content or Data Classification)
• Starting a Data Classification Project? Start here first
• Advantages of Data Classification
• Tag aware Indexing process
• How Classification and Tagging Works
• Regex Syntax to Follow
• Classification Use Cases
• How to enable Classification Tagging without Content Indexing
• How to Configure a Classification Rule
• How to list classification rules
• How to add a new classification rule
• How to modify an existing classification rule
• How to remove a classification rule
• How to View the rules file
• How to test a file with your Classification rules before production Role out
• How to Use Test data and commands to use to Experiment with Data Classification
• Common Compliance Standards Overview
• PII and Sensitive PII Defined
• Security Classification Schema For PII
• How to use RegEx Expressions to Locate Compliance Data
• Regex Expression Testing Tools
• Basic Regex Syntax for Most Scenarios
• Tested RegEx Expressions
• Identify Executable Files
• Files with URL's
• Document Security Classification
• Name
• Address
• Street Address
• North American Street Address
• German Street Address
• State, Region or Province
• State, Region or Province Key Words
• French Province
• Italian Region or Province
• Spain
• UK
• Canadian Province
• US State
• US Zip Code
• Telephone Number Key Words
• French Telephone Number
• Italian Telephone Number
• Spanish Telephone Number
• UK Telephone Number
• North American Telephone Number
• Social Insurance Number
• Social Insurance or Social Security Key Word
• French Social Insurance Number
• Italian Codice Fiscale
• Spanish Social Insurance
• NIE (Número de Identificación de Extranjero) for non Spanish Citizens
• DNI (Documento Nacional de Identidad) for Spanish citizens
• UK NINO
• Canadian Social Insurance Number
• US Social Security Number
• Date of Birth
• Email
• IBAN: Europe Only
• Bank Account Numbers
• Germany
• France
• Italy
• Spain
• Bank Account Numbers: Canada and US only
• Account Numbers Canada and US
• Bank Account Number US (10 - 12 digits) and Canada (7- 12 digits)
• US
• Canada
• Bank Routing Numbers
• US Routing Number
• Canadian Routing Numbers
• Routing and Bank Account Numbers
• US
• Canada
• Credit Card Number
• ACH Format Compliance Check
• Credit Card CVV
• Expiration Date
• Medical Data
• Medical Record Number (MRN)
• Weight
• Height

Overview of the Document Classification System

This guide covers different classification types that can be located in documents and the ability to configure the classification feature to read documents and match to classification types that are configured and apply a tag to the custom classification attribute in the search schema. This allows simple easy searches and scheduled reporting on compliance data. This allows aggregate reports and file lists for data that has been tagged by the classification system

Once the tagging configuration is in place, full scan index can tag existing data and incremental mode can detect new documents or modified documents and scan the documents for compliance data. This feature automates the whole process and reduces the complexity and time spent classifying data.

This feature can be used with custom tags for internal document classification for any vertical industry that has specific document types. This system is flexible to tag documents based on regex syntax matching that supports substitution and wild card for letters numbers in documents.

Understanding Classification vs key Word Searching

Key word searching is typically used for legal discovery to locate files needed for a specific investigation. It can also be used for end user search solution where users are locating documents based on key words. This includes adhoc searches for key words.

Data Classification focuses on locating well known data types within documents to ensure it has been secured correctly and the correct users have access to the information. Data Classification solutions search for well known data types such as credit cards for PCI, personal information such SIN number, drivers license, email address, addresses, health records. The data is typically employee data or customer data. Data classification is often alpha numeric patterns and this is best addressed with regex pattern matching.

Data Classification requires reading the content of the files and locating matching patterns for well known data types based on the specific compliance requirements. Solutions must be able to read many different file types, Search & Recover supports over 1500 file types. As business requirements change it is necessary to update the classification pattern matching policies.

Data Classification requires reading files each time a new classification tag is added, this requires rescanning the path in the file system. The data remains in the file system and is not copied into the index. This would require too much disk space to store the data in the index, an index does not store the documents themselves and only stores pointers to words in specific documents. All Data Classification systems must scan files in the file system itself to save space in the index and not duplicate the files in the index.

Search & Recover allows incremental scanning for new or modified files to be scanned quickly due to integration with Powerscale change list feature. For cold data a path scan is required and can be targeted anywhere in the file system with an index job that specifies a path to start the scan for new Data classification tags add to the system.

Best Practise (Content or Data Classification)

1. Full Content indexing for adhoc unknown search requirements
2. Data Classification to tag documents for compliance data identification or any alpha numeric pattern matching.  

Starting a Data Classification Project? Start here first

1. Data classification requires a list of PHI or specific data tags needed before you start creating production rules in Search & Recover. As per above explanation scanning the file system should be done once all rules are created and tested with test data.
2. List all data types needed
3. Map out tags for reporting on each type of data
4. Create test rules using examples in this guide
5. Create test data with good and bad matches for testing.
6. Follow the rules test feature to test matching logic quickly and easily.  Link here.
7. You can also test with our test data and rules.  Link here.
8. Modify your rules and test until you are ready to move into production.
9. Once you are in production, we suggest copying your test data to a path that is covered by a full index path policy in Search & Recover. Then use the index on demand command to index your data without waiting for the next scheduled index job.
   1. searchctl folders list (to get the folder id)
   2. searchctl folders index --id xxxx --incremental
   3. Then watch the job
   4. searchctl jobs view --id xxxx (user the job name provided from the index command)
   5. Wait for the job to complete
   6. Search in the GUI using the quick report "Data Classification" See guide link 
      

Advantages of Data Classification

1. Reduction in disk space vs full content indexing
2. Faster producing of content to locate data based on pattern matching
3. Supports more complex pattern matching and number aware matching syntax with regex

Tag aware Indexing process

1. Tag aware processing allows dynamic tracking of files and determines if a file has been scanned against the tag classification filters. The system will determine if any new classification filters have been created and will determine if a file needs a rescan.
2. Full scan or incremental jobs both enable dynamic classification tag detection to intelligently scan files that have not been scanned for a new classification filter.

How Classification and Tagging Works

1. The classification uses regex to process all the text that is provided by the content indexing engine when a full or incremental folder scan runs with content ingestion enabled in classification mode.
2. The text of each document is decoded and sent to the classification engine.
3. The classification engine is configured with regex rules below to locate compliance data and apply a tag to the document in the index.
4. The tag name is specified in the classification rule.
5. A document can match more than one classification rule and will have more than one tag applied.
6. The text of the document is not indexed or stored in the index which reduces the space needed in the index. NOTE: no key word searches will be possible unless full content indexing is enabled in addition to classification mode.
7. Once a document is tagged you can use the classification option in advanced search or quick reports to narrow your search results to documents that match a specific tag.
8. See example below, the list of tags will be available with the option to combine them with AND/OR search logic with multiple tags and can multi select tags.
9.  

Regex Syntax to Follow

1. Regex engines can vary.   The rule set to follow is the Java regex engine.  This table shows syntax and escape characters to use.
2. https://gist.github.com/CMCDragonkai/6c933f4a7d713ef712145c5eb94a1816#feature-comparison
   

Classification Use Cases

1. New Search & Recover Deployment
   1. Index metadata and leverage content aware data classification without storing indexed content in the database. This option does not require expanding disk space to store classification tags. Disable full content index storage following steps here.
2. Existing Deployment with Content Indexing Enabled
   1. In the initial release of 1.1.5 tags can not be applied unless data is re-indexed and stored in the database. The presence of a classification tag configuration will trigger the re-index process to force a full re-index of content to be scanned for tags and the file will be re-added to the index even if the file on disk has not changed since it was last indexed. This will take time to re-index. This requirement should be considered before using this feature.
      

How to enable Classification Tagging without Content Indexing

1. Use this option to enable classification when full content indexing is not required. This option has no additional disk space requirements other than the metadata index sizing guidelines.
2. Login to node 1
3. nano /opt/superna/eca/eca-env-common.conf
4. paste this to the file
5. export ADD_CONTENT_TO_INDEX=false 
6. control+x to save
7. ecactl cluster down
8. ecactl cluster up
9. done

How to Configure a Classification Rule

1. Each classification rule is added to a single file and evaluated against the text of each file processed for content and classification processing.

2. Login to Search & Recover node 1 as ecaadmin

3. searchctl CLI commands will be added to edit this file and live update the ingestion engine to start using the new rules file. The below information is information to validate your rules file.

4. How to list classification rules

   1. searchctl classification list

5. How to add a new classification rule

   1. searchctl classification add --name NAME --regex REGEX | [--regex-file /home/ecaadmin/regex.txt]

      1. --name - this is the name of the tag that will appear in the GUI when searching. Use single quotes at the beginning and end of the tag name. 

      2. --regex - this is the regex value used to match text for this tag. See examples in this guide or create your own regex matching string. Use single quotes at the beginning and end of the regex pattern.

      3. (optional) --regex-file  <path to file > This flag should be used for any complex regex with special characters that cannot be passed into the CLI command due to bash shell restrictions.  The regex in the file can use any special characters needed. 

   2. example

      1. searchctl classification add --name 'email' --regex '[\\w-\\.]+@([\\w-]+\\.)+[\\w-]{2,4}'

6. How to modify an existing classification rule

   1. searchctl classification modify --name NAME --regex REGEX

   2. Enter an existing tag name and new regex value to replace the matching logic.

7. How to remove a classification rule

   1. This command will start a job that searches the index for the files matching the tag and will place these files in a queue to re-index the files. This second re-index will no longer be tagged with the removed tag. This job can add a lot of files to be processed and will take time to remove them from the index. Once the command is executed the GUI will no longer display the tag for searching.

   2. searchctl classification remove --name NAME

      1. NOTE: A job is launched to submit all matching files to be re-indexed, this will re-read the content of these files and run match rules for all remaining tags. This can generate read bandwidth to re-process these files and re-read all files to retag the files based on remaining data classification rules.

8. How to View the rules file

   1. cat /opt/superna/eca/data/classifiers.json

{

"email":"[\\w-\\.]+@([\\w-]+\\.)+[\\w-]{2,4}",

"phone":"(\\+\\d{1,2}\\s)?\\(?\\d{3}\\)?[\\s.-]\\d{3}[\\s.-]\\d{4}",

"ipv4":"(([0-9]|[1-9][0-9]|1[0-9]{2}|2[0-4][0-9]|25[0-5])\\.){3}([0-9]|[1-9][0-9]|1[0-9]{2}|2[0-4][0-9]|25[0-5])"

}

How to test a file with your Classification rules before production Role out

1. This feature allow testing your classifiers easily with a single command
2. Example:
   1. searchctl classifications test --isilon <cluster name> --path /ifs/data/search/filetotest.txt 
   2. Retrieves the file over the rest API.
   3. Tests the content of the file against all configured classifications
   4. Prints to the console which classifications matched and which string was found
   5. See example below that shows which tags matched and which strings in the file matched the regex
      1. 
         
         

How to Use Test data and commands to use to Experiment with Data Classification

1. Download test file data and Excel sheet inside the zip file.
2. Unzip the file and copy the word documents to a test SMB share
3. Configure indexing on this folder path
4. Open the Excel file from the zip file named Regex Tag and Test File Map.xlsx
5. Use column A to copy and paste any of the classification commands to your search appliance based on which classifications you want to test with.  Each row shows which files will match this classification tag.
6. Start an index job on the test path.
7. Login to the GUI and click on the quick reports tab.
8. Run the "Classification  Report"
9.  
10. In the table below the graph you can select a tag and chose the show me the files option to locate the tagged files.
11. 
    
12. Done

Common Compliance Standards Overview

Businesses are collecting and storing more and more individuals’ PII. As a result, various jurisdictions have passed legislation to limit the use, distribution, and accessibility of PII, while allowing companies who need it to manage the data safely. GDPR in the European Union, HIPAA (Health Insurance Portability and Accountability Act ) and PCI DSS  (Payment Card Industry Data Security Standard) in the United States, along with state laws, other data breach laws, and other regulations control what defines PII. 

The most common compliance standards covered below provides background on the key requirements to locating and protecting data that falls into one of these categories.

PCI DSS Data

PCI DSS provides standards for the processes and systems that merchants and vendors use to protect information. This information includes: Cardholder data such as the cardholder's name, the primary account number, and the card's expiration date and security code.

PHI Data:

PHI is any health information that can be tied to an individual, which under HIPAA means protected health information includes one or more of the following 18 identifiers. If these identifiers are removed the information is considered de-identified protected health information, which is not subject to the restrictions of the HIPAA Privacy Rule.

1. Names (Full or last name and initial)

2. All geographical identifiers smaller than a state, except for the initial three digits of a zip code if, according to the current publicly available data from the U.S. Bureau of the Census: the geographic unit formed by combining all zip codes with the same three initial digits contains more than 20,000 people; and the initial three digits of a zip code for all such geographic units containing 20,000 or fewer people is changed to 000

3. Dates (other than year) directly related to an individual

4. Phone Numbers

5. Fax numbers

6. Email addresses

7. Social Security numbers

8. Medical record numbers

9. Health insurance beneficiary numbers

10. Account numbers

11. Certificate/license numbers

12. Vehicle identifiers (including serial numbers and license plate numbers)

13. Device identifiers and serial numbers;

14. Web Uniform Resource Locators (URLs)

15. Internet Protocol (IP) address numbers

16. Biometric identifiers, including finger, retinal and voice prints

17. Full face photographic images and any comparable images

18. Any other unique identifying number, characteristic, or code except the unique code assigned by the investigator to code the data

GDPR Data:

The data subjects are identifiable if they can be directly or indirectly identified, especially by reference to an identifier such as a name, an identification number, location data, an online identifier or one of several special characteristics, which expresses the physical, physiological, genetic, mental, commercial, cultural or social identity of these natural persons. In practice, these also include all data which are or can be assigned to a person in any kind of way. For example, the telephone, credit card or personnel number of a person, account data, number plate, appearance, customer number or address are all personal data.

Classifying and Securing PII

PII and Sensitive PII Defined 

PII: NIST 800-122 defines PII (Personally Identifiable Information) as any information that permits the identity of an individual to be directly or indirectly inferred, including any other information that is linked or linkable to that individual, regardless of whether the individual is a U.S. citizen, legal permanent resident, visitor to the U.S., or employee or contractor to a government agency or corporation. 

Sensitive PII (SPII): According to the US Department of Homeland Security  Handbook for Safeguarding Sensitive PII is Personally Identifiable Information, which if lost, compromised, or disclosed without authorization, could result in substantial harm, embarrassment, inconvenience, or unfairness to an individual. Sensitive PII includes:

• Social security numbers

• Bank account numbers

• Passport information

• Healthcare related information

• Medical insurance information

• Student information

• Credit and debit card numbers

• Drivers license and State ID information

Security Classification Schema For PII

In order to comply with the various restrictions in place covering the security of PII at least three levels of security classifications are recommended: Public, Private and Restricted.

1. Public Data is PII data that is in the “public domain”, which includes data found in public records, public telephone directories, business directories, business cards, newspapers, social media platforms and websites. While anyone can access this data, access controls to prevent it’s unauthorized use is recommended. If an individual does not want the data disclosed it should be classified as Private Data. If it’s linkable to disassociated data such as name, address, social insurance, bank account, credit card and medical record data, it should be classified as Restricted Data.

2. Private Data is PII data an individual may not wish to disclose, such as date-of-birth, home address and phone number. Private data should be covered by a moderate level of protection. If it is linkable to disassociated data such as name, address, social insurance, bank account, credit card and medical record data. It should be classified as Restricted Data.

3. Restricted Data is sensitive PII (SPII), and is data which cannot obtain through legitimate means. Restricted data includes social insurance numbers, bank account, credit card details, medical information, etc. Restricted data should be covered by the highest level of security controls.

How to use RegEx Expressions to Locate Compliance Data

The following are Regex expressions that will help to identify data as defined by PII, CPI, PHI and GDPR standards. All of these expressions have been tested using a mock database containing data for Germany, France, Italy, Spain, UK, Canada and US. The mock data Included:

1. Document Security Classification

2. Name

3. Address  (Street, City, State or Province)

4. Postal Code

5. Telephone

6. Email

7. Date of Birth

8. Social Insurance Number

9. Bank Account (Account Number, Routing Number, IBAN Number)

10. Credit Card (number, CVV, Exp Date)

11. Medical Record Number

12. Blood Type, Height

Regex Expression Testing Tools

A regex is a string of text that allows you to create patterns that help match, locate, and manage text.

The https://regex101.com/ test site was used to test and validate all the following expressions:

Basic Regex Syntax for Most Scenarios

1. The following regex examples can be used for most matching scenarios. Use these examples to build your own rules.
   1. Case insensitive matching
      1. (?i)xxxxx - Using (?i) and then a string will match the string regardless of case
   2. Combining key words with OR logic
      1. xxxx | yyyy - Using the pipe command will match string xxxx OR yyyy
   3. Combining key words with AND logic
      1. xxxx AND yyyy - using upper case AND command will match string xxxx AND yyyy
   4. Numeric range matching
      1. Example 1 - matching a single number between 0 to 9
         1. [0-9]
      2. Example 2 - Matching a 2 digit 10 to 99
         1. [1-9][0-9]
      3. Example 1 - matching - 0 to 255
         1. [0-9]|[1-9][0-9]|1[0-9][0-9]|2[0-4][0-9]|25[0-5].
      4. Examples of numerous number matching options
         1. 000..255: ^([01][0-9][0-9]|2[0-4][0-9]|25[0-5])$
         2. 0 or 000..255: ^([01]?[0-9]?[0-9]|2[0-4][0-9]|25[0-5])$
         3. 0 or 000..127: ^(0?[0-9]?[0-9]|1[01][0-9]|12[0-7])$
         4. 0..999: ^([0-9]|[1-9][0-9]|[1-9][0-9][0-9])$
         5. 000..999: ^[0-9]{3}$
         6. 0 or 000..999: ^[0-9]{1,3}$
         7. 1..999: ^([1-9]|[1-9][0-9]|[1-9][0-9][0-9])$
         8. 001..999: ^(00[1-9]|0[1-9][0-9]|[1-9][0-9][0-9])$
         9. 1 or 001..999: ^(0{0,2}[1-9]|0?[1-9][0-9]|[1-9][0-9][0-9])$
         10. 0 or 00..59: ^[0-5]?[0-9]$
         11. 0 or 000..366: ^([012]?[0-9]?[0-9]|3[0-5][0-9]|36[0-6])$

Tested RegEx Expressions

The following Classification Tags and RegEx expressions have been tested using ssh prompt. They contain the necessary escape characters to work with bash prompt over ssh and can be copied and pasted to the ssh session to set up a classification rule. The data base used to test these expressions contained words in German, French, Italian, Spanish and English. German, French and Spanish languages contain accented (i.e é, ë, ê, è, ñ) and or special characters (i.e. German language ß). The following tested RegEx's do not include accommodation for accented or special characters. In a database search using these expressions data up to a accented character will be shown, the accented character and any letters following will not be displayed.  

Identify Executable Files

Format: This Regular Expression will identify executable files in the format of <file name>.<File Extension>. The expression will identify the following executable file extensions:

BAT, BIN, CMD, COM, CPL, EXE, GADGET, INF1, INS, INX, ISU, JOB, JSE, LNK, MSC, MSI, MSP, MST, PAF, PIF, PS1, REG, RGS, SCR, SCT, SCT, SHB, SHS, U3P, VB, VBE, VBS, VBSCRIPT, WS, WSF, WSH, ACTION, APP, COMMAND, CSH, IPA, KSH, OSX, OUT, PRG, RUN, WORKFLOW

Identify Executable Files RegEx Expression: searchctl classification add --name 'executablefiles' --regex '(.*\.(BAT|BIN|CMD|COM|CPL|EXE|GADGET|INF1|INS|INX|ISU|JOB|JSE|LNK|MSC|MSI|MSP|MST|PAF|PIF|PS1|REG|RGS|SCR|SCT|SCT|SHB|SHS|U3P|VB|VBE|VBS|VBSCRIPT|WS|WSF|WSH|ACTION|APP|COMMAND|CSH|IPA|KSH|OSX|OUT|PRG|RUN|WORKFLOW))'  

Tag: executablefiles

Key Words: Executable File

Keyword RegEx Expression: searchctl classifications add --name 'executablefilekeyword' --regex '((?i)(Executable|File|Files|Identify|Extension|Extensions))' 

Phrase Example: Identify Executable File Extensions 

Security: File extensions are not considered PII, PCI, PHI, or GDPR data

Files with URL's

Format: This Regular Expression can be used to find URL's in a document.

Search URL's RegEx Expression: searchctl classification add --name 'searchurl' --regex '(http|ftp|https):\/\/([\w_-]+(?:(?:\.[\w_-]+)+))([\w.,@?^=%&:\/~+#-]*[\w@?^=%&\/~+#-])'  

Tag: searchurl

Key Words: Find, Search, URL, URL's

Keyword RegEx Expression: searchctl classifications add --name 'searchurlkeyword' --regex '((?i)(URL|URL's|Search|Identify|Find))' 

Phrase Example: Find URL's, Identify URL 

Security: URL's are not considered PII, PCI, PHI, or GDPR data

Document Security Classification

Format: string match case insensitive

Document Security Classification RegEx Expression:  searchctl classifications add --name 'docclass' --regex '((?i)(Public|Private|Restricted|Confidential|Secret|Top|Unrestricted|Propritary|Sensitive|Unclassified|Tres secret defense|Secret defense|Confidentiel defense|Diffusion restreinte|STRENG GEHEIM|GEHEIM|VS-VERTRAULICH|VS-NUR FUR DEN DIENSTGEBRAUCH|Segretissimo|Segreto|Riservatissimo|Riservato|Secreto|Reservado|Confidencial|Difusion Limitada|OFFICIAL-SENSITIVE|OFFICIAL|Confidentiel|Protected|Protoge))' 

Name

Format: First Last Name

Name RegEx Expression:  searchctl classification add --name 'names' --regex '[a-zA-Z]+[\-'"'"'\s]?[a-zA-Z ]{1,40}' 

Key Words: Name, Nombre,  Nome, First Name, Last Name, Apellido, Cognome, Nom de famille,  Familienname,  Nachname 

Name Keyword RegEx Expression: searchctl classification add --name 'nameskeyword' --regex '(Name|Nombre|Nome|First|Last|Middle|Zuerst|Letzte|Mitte|Milieu|D'"'"'abord|Durer|Primo|Prima|Medio|Media|Scorso|Scorsa|Ultimo|Ultima)'

Phrase Example: Customers Name, Patients Name, Kundenname, Nom du client, 

Nome del cliente,  Nombre de las clientas

Security: 

Address

Street Address

Security: 

North American Street Address

Format: Number followed by street name and designation i.e. 125 June Street

Street RegEx Expression:  searchctl classification add --name 'nastreet' --regex '(?i)\d+(\s+\w+){1,}\s+(?:st(?:\.|reet)?|dr(?:\.|ive)?|pl(?:\.|ace)?|ave(?:\.|nue)?|rd|road|lane|ln.|drive|way|court|ct.|plaza|square|run|parkway|point|pike|square|driveway|trace|park|terrace|blvd)' 

Key Words: Drive, drive, Street, street, St. Place, Lane, Ln., ln., Road, Rd., rd., Avenue, avenue, Ave., ave., Circle, Court, court, Ct., ct., Way, Plaza, Square, square, Run, run, Parway, parkway, Pkw., pkw., Point, point, Pike, pike, driveway, trace, Park, park, terrace, Terrace, blvd  

North American Street Address Keyword Regex Expression:  searchctl classification add --name 'nastreetkeyword' --regex '((?i)(Drive|drive|Street|street|Place|Lane|Ln.|ln.|Road|Rd.|rd.|Avenue|avenue|Ave.|ave.|Circle|Court|court|Ct.|ct.|Way|Ave|Plaza|Square|square|Run|run|Parway|parkway|Pkw.|pkw.|Point|point|Pike|pike|driveway|trace|Park|park|terrace|Terrace|blvd))' 

German Street Address

Format: Street Name followed by Number i.e. Kieler Strasse 89 

French Street Name RegEx Expression: searchctl classification add --name 'gstreet' --regex '([a-zA-Z]+\s*-?[a-zA-Z]+\s*-?[a-zA-Z]+\s*\d{1,3})' 

Key Words: Weg, Straße, Allee, Mitte 

German Street Address Keyword Regex Expression: searchctl classification add --name 'gstreetkeyword' --regex '(Weg|Strasze|Allee|Mitte)'

French Street Address

Format: Number followed by street designation (i.e. rue, quai) followed be name. i.e. 48 rue des Lacs 

French Street Name RegEx Expression: searchctl classification add --name 'frstreet' --regex '((\d{1,3}),?\s\b(cours|rue|Rue|boulevard|Avenue|avenue|Quai|route)\s([a-zA-Z]{1,15})\s?([a-zA-Z]{1,15})\s?([a-zA-Z]{1,15})\s?([a-zA-Z]{1,15}))' 

Key Words: cours, rue, Rue, boulevard, Avenue, avenue, Quai, route

French Street Address Keyword Regex Expression: searchctl classification add --name 'frstreetkeyword' --regex '((?i)(cours|rue|Rue|boulevard|Avenue|avenue|Quai|route))'

Italian Street Address

Format: Street designation (i.e. Via, corso) followed be name, followed by number i.e. Piazza Trieste e Trento 136 

Italian Street Name RegEx Expression: searchctl classification add --name 'itstreet' --regex '(Via|Corso|Viale|Piazza|Largo) ([a-zA-Z ]+?),? (\d+)'  

Key Words: Via, Corso, Viale, Piazza, Largo

Italian Street Address Keyword Regex Expression: searchctl classification add --name 'itstreetkeyword' --regex '((?i)(Via|Corso|Viale|Piazza|Largo))' 

Spanish Street Address

Format: Street name, followed by number i.e. Rio Segura 47 

Spanish Street Name RegEx Expression: searchctl classification add --name 'spstreet' --regex '([a-zA-Z./]+\s*[a-zA-Z]+\s*[a-zA-Z]+\s*[a-zA-Z]+\s*\d{1,3})' 

Key Words: Calle 

 

Spanish Street Address Keyword Regex Expression: searchctl classification add --name 'spstreetkeyword' --regex '(Calle|calle)' 
 

United Kingdom Street Address

Note: UK Street Expression is the same as the North American Expression

Format: Number followed by street name and designation i.e. 92 Great Western Road 

UK Street RegEx Expression:  searchctl classification add --name 'ukstreet' --regex '(\d{1,5}\s(\w+)?([a-zA-Z]+)(\.)?\s?([a-zA-Z]+)\s?\-?([a-zA-Z]+)\s?(Drive|drive|Street|street|Place|Lane|Ln.|ln.|Road|Rd.|rd.|Avenue|avenue|Ave.|ave.|Circle|Court|court|Ct.|ct.|Way|Ave|Plaza|Square|square|Run|run|Parway|parkway|Pkw.|pkw.|Point|point|Pike|pike|driveway|trace|Park|park|terrace|Terrace|blvd)?)' 

Key Words: Drive, drive, Street, street, St. Place, Lane, Ln., ln., Road, Rd., rd., Avenue, avenue, Ave., ave., Circle, Court, court, Ct., ct., Way, Plaza, Square, square, Run, run, Parway, parkway, Pkw., pkw., Point, point, Pike, pike, driveway, trace, Park, park, terrace, Terrace, blvd  

UK Street Address Keyword Regex Expression: searchctl classification add --name 'ukstreetkeyword' --regex '((?i)(Drive|drive|Street|street|Place|Lane|Ln.|ln.|Road|Rd.|rd.|Avenue|avenue|Ave.|ave.|Circle|Court|court|Ct.|ct.|Way|Ave|Plaza|Square|square|Run|run|Parway|parkway|Pkw.|pkw.|Point|point|Pike|pike|driveway|trace|Park|park|terrace|Terrace|blvd))' 

Street Address Key Words (North America, Germany, France, Italy, Spain, UK)

Key Words: Drive, drive, Street, street, St. Place, Lane, Ln., ln., Road, Rd., rd., Avenue, avenue, Ave., ave., Circle, Court, court, Ct., ct., Way, Plaza, Square, square, Run, run, Parway, parkway, Pkw., pkw., Point, point, Pike, pike, driveway, trace, Park, park, terrace, Terrace, blvd, Weg, Straße, Allee, Mitte, cours, rue, Rue, boulevard, Avenue, avenue, Quai, route, Via, Corso, Viale, Piazza, Largo,  Calle, Address, Addresse, Indirizzo, Habla a, Dirección 

 

Street Address Keyword RegEx Expression: searchctl classification add --name 'streetkeyword' --regex '((?i)(Drive|drive|Street|street|Place|Lane|Ln.|ln.|Road|Rd.|rd.|Avenue|avenue|Ave.|ave.|Circle|Court|court|Ct.|ct.|Way|Ave|Plaza|Square|square|Run|run|Parway|parkway|Pkw.|pkw.|Point|point|Pike|pike|driveway|trace|Park|park|terrace|Terrace|blvd|Weg|Strasze|Allee|Mitte|rue|Rue|cours|rue|boulevard|Quai|route|strada|Via|Corso|Viale|Piazza|Largo|Strada|Calle|calle|Address|Addresse|Indirizzo|Habla a|Direccion))'

Phrase Example: Street address, Adresse de rue, Dirección

City Name

Format: City Name

City RegEx Expression: searchctl classifications add --name 'city' --regex '(?:[A-Z][a-z.-]+[ ]?)+' 

Key Words: City, Stadt, Ville, Città, Ciudad

City Name Keyword RegEx Expression: searchctl classifications add --name 'citykey' --regex '(City|Citta|Ciudad|Ville|Stadt).*$ 

Phrase Example: City address, Stadtadresse, Adresse de la ville, Indirizzo della città, 

Dirección de la ciudad

Security: If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

State, Region or Province

State, Region or Province Key Words

Key Words: State, Zustand,Province, Provincia,Region 

Keyword RegEx Expression: searchctl classifications add --name 'srpkeyword' --regex '(State|Zustand|Province|Provincia|Region)' 

German States

Format: 2 Letter abbreviation or name of German State

German State RegEx Expression: searchctl classifications add --name 'gstate' --regex '\b(?:BW|Baden-Wurttemberg|BY|Bavaria|Bayern|BE|Berlin|BB|Brandenburg|HB|Bremen|HH|Hamburg|HE|Hesse|Hessen|NI|Lower Saxony|MV|Mecklenburg-Vorpommern|NW|North Rhine-Westphalia|Nordrhein-Westfalen|RP|Rhineland-Palatinate|SL|Saarland|SN|Saxony|Sachsen|ST|Saxony-Anhalt|Sachsen-Anhalt|SH|Schleswig-Holstein|TH|Thuringia|Thuringen|Freistaat Bayern|Rheinland-Pfalz|Nordrhein-Westfalen|Niedersachsen|Zustand)\b'

Key Words: Zustand

State Region or Province Keyword RegEx Expression: searchctl classifications add --name 'srpkeyword' --regex '(State|Zustand|Province|Provincia|Region)' 

Phrase Example: Zustand

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

French Province

Format: 3 letter abbreviation or Province name.

French Province RegEx Expression: searchctl classifications add --name 'fstate' --regex '(Aquitaine|IDF|Ile-de-France|CBL|Centre|Basse-Normandie|Lorraine|Bretagne|Picardie|Languedoc-Roussillon|Rhone-Alpes|BRE|Brittany|NOR|Normandy|HDF|Hauts-de-France|Grand Est|Pays de la Loire|Centre-Val de Loire|BFC|Bourgogne-Franche-Comte|NAQ|Nouvelle-Aquitaine|ARA|Auvergne-Rhone-Alpes|OCC|Occitanie|Provence-Alpes-Cote d'"'"'Azur|COR|Corsica)\b' 

Key Words: Province

Sate Region or Province Keyword RegEx Expression: searchctl classifications add --name 'srpkeyword' --regex '(State|Zustand|Province|Provincia|Region)' 

Phrase Example: Province

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

Italian Region or Province

Format: 2 Letter abbreviation or Region or Province Name (Note, Region is like a US State, and Province is like a US county)

Italian Region RegEx Expression: searchctl classifications add --name 'istate' --regex '\b(Provincia|ABR|Abruzzo|BAS|Basilicata|CAM|Campania|CAL|Calabria|CAM|Campania|EMI|Emilia-Romagna|FRI|Friuli-Venezia Giulia|LAZ|Lazio|LIG|Liguria|LOM|Lombardia|MAR|Marche|MOL |Molise|PIE |Piemonte|PUG |Puglia|SAR |Sardegna|SIC|Sicilia|Südtirol|TOS|Toscana|TRE|Trentino-Alto Adige|UMB|Umbria|VAL|Valle d'"'"'Aosta|VEN|Veneto|PD|Padova|VA|Varese|BS|Brescia|MI|Milano|PA|Palermo|AN|Ancona|CS|Cosenza|CN|Cuneo|VV|Vibo Valentia|FI|Firenze|OR|Oristano|TN|Trento|CH|Chieti|AP|Ascoli Piceno|VR|Verona|AT|Asti|MS|Massa|VC|Vercelli)\b' 

Key Words: Provincia, Regione

State Region or Province Keyword RegEx Expression: searchctl classifications add --name 'srpkeyword' --regex '(State|Zustand|Province|Provincia|Region)' 

Phrase Example: Provincia, Regione

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

Spain

Format: Province Name or 1 or 2 letter abbreviation

Spanish Province RegEx Expression:searchctl classifications add --name 'spstate' --regex '\b(A Coruna|Araba|VI|Alava|Albacete|A|Alicante|Alacant|Almeria|O|Asturias|Avila|Badajoz|Balears|B|Barcelona|Bizkaia|Biscay|Burgos|Cacer|Cadiz|Cantabria|CS|Castellon|Castello|Ciudad Real|Cordoba|Cuenca|Gipuzkoa|Girona|Granada|Guadalajara|Huelva|HU|Huesca|Huca|J|Jaen|LO|La Rioja|Las Palmas|Leon|Lleida|Lugo|M|Madrid|MA|Malaga|Murcia|NA|Navarre|Nafarro|OR|Ourense|Palencia|Pontevedra|SA|Salamanca|Santa Cruz de Tenerife|Segovia|Sevilla|SE|Seville|Soria|Tarragona|Teruel|Toledo|V|Valencia|VA|Valladolid|Zamora|Zaragoza|Provincia)\b'

Key Words: Provincia

State Region or Province Keyword RegEx Expression: searchctl classifications add --name 'srpkeyword' --regex '(State|Zustand|Province|Provincia|Region)' 

Phrase Example: Provincia

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

UK

Format: Name

RegEx Expression: searchctl classifications add --name 'ukcountry' --regex '\b(Great Britain|England|Scotland|Wales|Northern Ireland|Western Isles)\b' 

Key Words: Country or Region

State Region or Province Keyword RegEx Expression: searchctl classifications add --name 'srpkeyword' --regex '(State|Zustand|Province|Provincia|Region)' 

Phrase Example: Country or Region

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

Canadian Province 

Format: Province Name or Abbreviation

Canadian Province RegEx Expression: searchctl classifications add --name 'caprov' --regex '\b(AB|ALB|Alta|Alberta|BC|CB|British Columbia|LB|Labrador|MB|Man|Manitoba|N[BLTSU]|Nfld|NF|Newfoundland|NWT|Northwest Territories|Nova Scotia|New Brunswick|Nunavut|ON|ONT|Ontario|PE|PEI|IPE|Prince Edward Island|QC|PC|QUE|QU|Quebec|SK|Sask|Saskatchewan|YT|Yukon|Yukon Territories)\b' 

Key Words: Province

State Region or Province Keyword RegEx Expression: searchctl classifications add --name 'srpkeyword' --regex '(State|Zustand|Province|Provincia|Region)' 

Phrase Example: Province

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

US State

Format:  State Name or Abbreviation

US State RegEx Expression: searchctl classifications add --name 'usstate' --regex '(?:Ala(?:(?:bam|sk)a)|Arizona|Arkansas|California|Colorado|Connecticut|Delaware|District of Columbia|Florida|Georgia|Hawaii|Idaho|Illinois|Indiana|Iowa|Kansas|Kentucky|Louisiana|Maine|Maryland|Massachusetts|Michigan|Minnesota|Miss(?:(?:issipp|our)i)|Montana|Nebraska|Nevada|New (?:Hampshire|Jersey|Mexico|York)|North (?:(?:Carolin|Dakot)a)|Ohio|Oklahoma|Oregon|Pennsylvania|Rhode Island|South (?:(?:Carolin|Dakot)a)|Tennessee|Texas|Utah|Vermont|Virginia|Washington|West Virginia|Wisconsin|Wyoming|A[KLRZ]|C[AOT]|D[CE]|FL|GA|HI|I[ADLN]|K[SY]|LA|M[ADEINOST]|N[CDEHJMVY]|O[HKR]|PA|RI|S[CD]|T[NX]|UT|V[AT]|W[AIVY])' 

Key Words: State

State Region or Province Keyword RegEx Expression: searchctl classifications add --name 'srpkeyword' --regex '(State|Zustand|Province|Provincia|Region)' 

Phrase Example: State name

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

US Zip Code

Format: 5 digit code (xxxxx), or 5 plus 4 digit code (xxxxx-xxxx)

US Zip Code RegEx Expressions:

searchctl classification add --name 'zip' --regex '([0-9]{5})'

searchctl classification add --name 'zip9' --regex '([0-9]{5}-[0-9]{4})'

Key Words: Zip Code, Postal Code

US Zip Code Keyword RegEx Expression: searchctl classifications add --name 'zipkeyword' --regex '((?i)(Zip|Postal|Code))' 

Phrase Example: Zip Code, Postal Code 

Security: If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

Telephone Number

Telephone Number Key Words

Key Words: Phone,Telephone,Number,Numero,Número,Mobile,Telefonnummer,Numéro,Telefono,Telefon,Téléphone,Teléfono,Handynummer,Poratble,Cell,Cellular,Cellulare|móvil 

Telephone Number Keyword RegEx Expression:   searchctl classification add --name 'phonekeyword' --regex '((?i)(Phone|Telephone|Number|Mobile|Telefonnummer|Telefono|Telefon|Telephone|Telefono|Handynummer|Poratble|Cell|Cellular|Cellulare|movil|Numero|de|telephone|portable))'  

German Telephone Numbers

Formats:

6 2 2 (XXXXXX XX XX)

5 2 2 2 (XXXXX XX XX XX)

4 2 2 2 (XXXX XX XX XX)

RegEx Expression: searchctl classification add --name 'germanphone' --regex '([+][0-9]{1,3}[ .-])?([(]{1}[0-9]{1,6}[)])?([0-9 .-\/]{3,20})' 

Key Words: Telefonnummer, Telephon, Handynummer

German Telephone Number Keyword RegEx Expression:  searchctl classification add --name 'dephonekeyword' --regex '((?i)(Telefonnummer|Telefon|Handynummer))'  

Phrase Example: Telefonnummer

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

French Telephone Number

Format: XX XX XX XX 

RegEx Expression: searchctl classification add --name 'frenchphone' --regex '\d{10}|\+33\d{9}|\+33\s\d{1}\s\d{2}\s\d{2}\s\d{2}\s\d{2}|\d{2}\s\d{2}\s\d{2}\s\d{2}\s\d{2}' 

Key Words: Numéro de téléphone, Numéro de portable 

 

French Telephone Number Keyword RegEx Expression:  searchctl classification add --name 'frphonekeyword' --regex '((?i)(Numero|de|telephone|portable))' 
 

 

Phrase Example: Numéro de téléphone, Numéro de portable 

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

Italian Telephone Number

Land Line

Format: XXXX XXXXXXX

RegEx Expression: searchctl classification add --name 'itphone' --regex '([0][1-9][0-9]{1,2}\s?[0-9]{6,11})'  

Mobile Phone

Format:3xx xxxxxxxx or 3xxxxxxxxx 

RegEx Expression: searchctl classification add --name 'itmoblephone' --regex '([3][0-9]{2}\s?[0-9]{6,7})' 

Key Words: Numero di telefono, Numero di cellulare 

ItalianTelephone Number Keyword RegEx Expression:  searchctl classification add --name 'itphonekeyword' --regex '((?i)(Numero|telefono|de|cellulare))'

Phrase Example: Numero di telefono, Numero di cellulare  

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

Spanish Telephone Number

Format: XXX XXX XXX

RegEx Expression:   searchctl classification add --name 'spanishphone' --regex '[6,7]\d{2}\s\d{3}\s\d{3}' 

Key Words: Número de teléfono, Número de teléfono móvil 

Spanish Telephone Number Keyword RegEx Expression:  searchctl classification add --name 'spphonekeyword' --regex '((?i)(Numero|de|telefono|movil))' 

Phrase Example: Número de teléfono

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

UK Telephone Number

Format: XXX XXXX XXXX

RegEx Expression: searchctl classification add --name 'ukphone' --regex '\s*\(?(0|\+44)(\s*|-)\d{4}\)?(\s*|-)\d{3}(\s*|-)\d{3}\s*|(\s*\(?(0|\+44)(\s*|-)\d{3}\)?(\s*|-)\d{3}(\s*|-)\d{4}\s*)|(\s*\(?(0|\+44)(\s*|-)\d{2}\)?(\s*|-)\d{4}(\s*|-)\d{4}\s*)|(\s*(7|8)(\d{7}|\d{3}(\-|\s{1})\d{4})\s*)|(\s*\(?(0|\+44)(\s*|-)\d{3}\s\d{2}\)?(\s*|-)\d{4,5}\s*)' 

Key Words: Telephone Number, Mobile Number, Cellular Number, Cell Number

UK Telephone Number Keyword RegEx Expression:  searchctl classification add --name 'ukphonekeyword' --regex '((?i)(Telephone|Number|Mobile|Cellular|Cell))'

Phrase Example:Telephone Number, Mobile Number, Cellular Number, Cell Number 

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

North American Telephone Number

Format: XXX-XXX-XXXX

RegEx Expressions:  

searchctl classifications add --name 'naphone' --regex '(\+\d{1,2}\s)?\(?\d{3}\)?[\s.-]\d{3}[\s.-]\d{4}' 

searchctl classification add --name 'usaphone' --regex '(?:\+?1[-.]?)?\(?([0-9]{3})\)?[-.]?([0-9]{3})[-.]?([0-9]{4})'

Key Words: Telephone Number, Mobile Number, Cellular Number, Cell Number 

North America Telephone Number Keyword RegEx Expression:  searchctl classification add --name 'naphonekeyword' --regex '((?i)(Telephone|Number|Mobile|Cellular|Cell))'

Phrase Example:Telephone Number, Mobile Number, Cellular Number, Cell Number 

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

North American Fax Number

Format: XXX-XXX-XXXX

RegEx Expressions:  

searchctl classification add --name 'fax' --regex '\+?\d{0,3}[- (]{0,2}?\d{3}[- )]{0,2}?\d{3}[- )]{0,2}?\d{4}?' 

Key Words: Fax, Fax Number

North America Telephone Number Keyword RegEx Expression:  searchctl classification add --name 'faxkeyword' --regex '((?i)(Fax|Number))'

Phrase Example:Fax, Fax Number 

Security:  If a stand alone element no security restrictions required, only if in conjunction with name and street address the following security restrictions apply:

Social Insurance Number

Social Insurance or Social Security Key Word

Key Words: Social Security, Pension Insurance, Rentenversicherung, SIN, Social Code, Sozialgesetzbuch (SGB), INSEE,  Codice fiscale,  NIE, Número de Identificación de Extranjero,  DNI, Documento Nacional de Identidad, NINO, NI, No, Social Insurance, SIN,  Social Security, SSN 

Keyword RegEx Expression: searchctl classification add --name 'ssnkeyword' --regex '.*((?i)(Social|Insurance|Number|Security|SIN|SSN|Pension|INSEE|Numero|Securite|Sociale|Codice fiscale|DNI|Documento|Nacional|Identidad|NIE|Identificacion|Extranjero|NI|National|Rentenversicherung|Sozialgesetzbuch|Deutsche|Code|German|System|Identification|Italino|Italian)).*' 

German Social Insurance Number

Format: 12 123456 A 123

RegEx Expression: searchctl classification add --name 'germansin' --regex '([0-9]{2}\s[0-9]{6}\s[a-zA-Z]\s[0-9]{3})' 

Format: 12 123456 A 12 1

RegEx Expression: searchctl classification add --name 'germansin2' --regex '([0-9]{2}\s[0-9]{6}\s[a-zA-Z]\s[0-9]{2}\s[0-9])'

Format:  12 12345678 A 121

RegEx Expression: searchctl classification add --name 'germansin3' --regex '([0-9]{2}\s[0-9]{8}\s[a-zA-Z]\s[0-9]{3})'

Format:  12 12345678 A 12 1

RegEx Expression: searchctl classification add --name 'germansin4' --regex '([0-9]{2}\s[0-9]{8}\s[a-zA-Z]\s[0-9]{2}\s[0-9])'  

Key Words: Social Security, Pension Insurance, Rentenversicherung, SIN, Social Code, Sozialgesetzbuch (SGB)

Social Insurance/Security Keyword RegEx Expression: searchctl classification add --name 'desinkeyword' --regex '((?i)(Social|Security|Pension|Insurance|Rentenversicherung|SIN|Social|Code|Sozialgesetzbuch|SGB))'

Phrase Examples: “German Social Security Number”,  “German Social Security System (Sozialversicherung)”, Deutsche Sozialversicherungsnummer

Security: 

French Social Insurance Number

Format: 1234567891234 12

RegEx Expression:  searchctl classification add --name 'frenchsin' --regex '([0-9]{13}\s[0-9]{2})' 

Format: 1 12 12 12345 123 12

INSEE RegEx Expression:  searchctl classification add --name 'frenchsin2' --regex '([1-9]\s[0-9]{2}\s[0-9]{2}\s[0-9]{5}\s[0-9]{3}\s[0-9]{2})' 

Key Words: INSEE 

French INSEE Keyword RegEx Expression:  searchctl classification add --name 'frsinkeyword' --regex '((?i)(NIRPP|INSEE|National|Identification|Number|numero|d'"'"'inscription|au|repertoire|de|securite|sociale))' 

Phrase Examples: “National Identification Number” , “"numéro d'inscription au répertoire", "numéro de sécurité sociale"

Security: 

Italian Codice Fiscale 

Format: 16 characters alphanumeric code (i.e. MRT MTT86S28 F205Z)

RegEx Expression:   searchctl classification add --name 'italiansin' --regex '([A-Za-z]{3}\s[A-Za-z]{3}\s[0-9|A-Z]{5}\s[0-9|A-Z]{5})' 

Format: MRTMTT86S28F205Z (No spaces in number)

Codice Fiscale RegEx Expression: searchctl classifications add --name 'italiansin2' --regex '([A-Za-z]{6}[0-9lmnpqrstuvLMNPQRSTUV]{2}[abcdehlmprstABCDEHLMPRST]{1}[0-9lmnpqrstuvLMNPQRSTUV]{2}[A-Za-z]{1}[0-9lmnpqrstuvLMNPQRSTUV]{3}[A-Za-z]{1})|([0-9]{11})' 

Key Words: Codice fiscale

Italian Codice Fiscale Keyword RegEx Expression: searchctl classification add --name 'itsinkeyword' --regex '((?i)(Codice|fiscale|italiano|Italian|fiscal|code))'

Phrase Examples: Italian fiscal code, Codice fiscale italiano

Security: 

Spanish Social Insurance

NIE (Número de Identificación de Extranjero) for non Spanish Citizens

Format: K,L,X,Y,or Z, followed by 7 digits followed by a letter (i.e K1234567A)

NIE RegEx Expression:  searchctl classification add --name 'spanishsin' --regex '((?i)([K-L]|[X-Z])\d{7}([A-Z]))' 

Key Words: NIE, Número de Identificación de Extranjero

Spanish NIE Keyword RegEx Expression: searchctl classification add --name 'spsinkeyword' --regex '((?i)(NIE|Numero|de|Identificacion|Extranjero|DNI|Documento|Nacional|Identidad))'

Phrase Example: Número de Identificación de Extranjero

Security: 

DNI (Documento Nacional de Identidad) for Spanish citizens

Format: The DNI format is 8 digits followed by a letter (example: 12345678A). The same number is used for one's driver's license.

There are two other classes of DNI for citizens of Spain:

• 'K' (example: K12345678A) for children under 14 who are Spanish residents.

• 'L' (example: L12345678A) for Spanish citizens who live outside Spain.

DNI RegEx Expression: searchctl classification add --name 'spanishsin2' --regex '((?i)([K-L]?)(\d{8}[A-Z]))' 

Key Words: DNI, Documento Nacional de Identidad

Spanish DNI Keyword RegEx Expression: searchctl classification add --name 'spsinkeyword' --regex '((?i)(NIE|Numero|de|Identificación|Extranjero|DNI|Documento|Nacional|Identidad))'

Phrase Example: Documento Nacional de Identidad

Security: 

UK NINO

Format: Two prefix letters, six digits and one suffix letter. ( i.e. QQ123456C)

NINO RegEx Expression: searchctl classification add --name 'uknino' --regex '(?!BG|GB|NK|KN|TN|NT|ZZ)[A-CEGHJ-PR-TW-Z][A-CEGHJ-NPR-TW-Z](?:\s*\d{2}){3}\s*[A-D]'  

Key Words: NINO, NI, No.

UK NINO Keyword RegEx Expression: searchctl classification add --name 'ukninokeyword' --regex '((?i)(National|Insurance|number|NINO|NI|No.))'

Phrase Example: National Insurance number

Security:

Canadian Social Insurance Number 

Format: 123-123-123 or 123 123 123

Social Insurance Number RegEx Expression: searchctl classification add --name 'canadiansin' --regex '(\d{3}-?\s?\d{3}-?\s?\d{3})'

Key Words: Social Insurance, SIN

Canadian Social Insurance Keyword RegEx Expression: searchctl classification add --name 'casinkeyword' --regex '((?i)(Social|Insurance|Number|SIN))' 

Phrase Example: Social Insurance Number

Security:

US Social Security Number

Format: 123-12-123 or 123 12 1234

Social Security Number RegEx Expressions:

searchctl classification add --name 'usssn' --regex '(\d{3}-?\s?\d{2}-?\s?\d{4})' 

searchctl classification add --name 'usassn' --regex '(?!(000|666|9))\d{3}-(?!00)\d{2}-(?!0000)\d{4}$|^(?!(000|666|9))\d{3}(?!00)\d{2}(?!0000)\d{4}'

Key Words: Social Security, SSN

US Social Security Keyword RegEx Expression: searchctl classification add --name 'usssnkeyword' --regex '((?i)(Social|Security|Number|SSN))' 

Phrase Example: Social Security Number

Security:

Date of Birth

Format: m-d-yy or mm-dd-yy, or m-d-yyyy, or mm-dd-yyyy, or m/d/yy, or mm/dd/yy, or m/d/yyyy, or mm/dd/yyyy. 

Date of Birth RegEx Expression: searchctl classification add --name 'dob' --regex '([0-1]?)([0-9])-?\/?[0-3]?[0-9]-?\/?\d{2,4}' 

 

Format: m/d/yy, or mm/dd/yy, or m/d/yyyy, or mm/dd/yyyy. 

Date of Birth RegEx Expression:  searchctl classification add --name 'dob2' --regex '([0-1]?)([0-9])\/[0-3]?[0-9]\/\d{2,4}' 

Format: m-d-yy or mm-dd-yy, or m-d-yyyy, or mm-dd-yyyy, . 

Date of Birth RegEx Expression:  searchctl classification add --name 'dob3' --regex '([0-1]?)([0-9])-[0-3]?[0-9]-\d{2,4}' 

Format: mm/dd/yyyy, or mm-dd-yyyy, or mm.dd.yyyy, or m/d/yyyy, or m-d-yyyy or m.d.yyyy 

Date of Birth Expression: searchctl classification add --name 'usadob' --regex '(?:(?:(?:0?[13578]|1[02])(\/|-|\.)31)\1|(?:(?:0?[1,3-9]|1[0-2])(\/|-|\.)(?:29|30)\2))(?:(?:1[6-9]|[2-9]\d)?\d{2})$|^(?:0?2(\/|-|\.)29\3(?:(?:(?:1[6-9]|[2-9]\d)?(?:0[48]|[2468][048]|[13579][26])|(?:(?:16|[2468][048]|[3579][26])00))))$|^(?:(?:0?[1-9])|(?:1[0-2]))(\/|-|\.)(?:0?[1-9]|1\d|2[0-8])\4(?:(?:1[6-9]|[2-9]\d)?\d{2})'

 

Key Words: DOB, Date, Data, Fecha, Birth, Geburt, naissance, nascita, nacimiento 

DOB Keyword RegEx Expression: searchctl classification add --name 'dobkeyword' --regex '((?i)(Date|Birth|DOB|Geburtsdatum|Naissance|Nascita|Fecha|Nacimiento|Geburt|Data))' 

Phrase Example: Date of Birth,  Geburtsdatum,  Date de naissance,  Data di nascita,  Fecha de nacimiento

Security:  As a stand alone data element it is Public Data and not restricted, but with Social Security Number and Name it is restricted data.

Email

Email RegEx Expressions:  

searchctl classifications add --name 'email' --regex '[\w-\.]+@([\w-]+\.)+[\w-]{2,4}' 

searchctl classification add --name 'usaemail' --regex '([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})'

Key Words: Email

Email Key Word RegEx Expression:  searchctl classifications add --name 'emailkeyword' --regex '((?i)(Email|E-mail|Address|Adresse|Correo|electronico|Indirizzo\\e-mail|correo|Direccion|email))'  

Key Phrase: Email, E-mail, Email Address, Correo electrónico, E-Mail-Addresse, Adresse e-mail, Indirizzo email, Dirección de correo electrónico

Security:

IBAN: Europe Only

Note IBAN is used in Europe, not Canada or US. The first two digits are for the country code (i.e "DE" for Germany) followed by a check digit comprising two characters and the national account number BBAN (basic bank account number), which is made up of the eight-digit bank sort code and the ten-digit account number

Germany, Italy, France, Spain, UK (all formats)

RegEx Expression:  searchctl classifications add --name 'iban' --regex '(?:DE)\d{20}|(?:FR)\d{19}[A-Z]\d{5}|(IT)\d{2}[A-Z]\d{22}|(?:ES)\d{22}|(?:GB)\d{2}[A-Z]{4}\d{14}|(?:DE)\d{2}\s\d{4}\s\d{4}\s\d{4}\s\d{4}\s\d{2}|(?:FR)\d{2}\s\d{4}\s\d{4}\s\d{4}\s\d{4}\s\d{1}[A-Z]\d{2}\s\d{3}|(IT)\d{2}\s[A-Z]\d{3}\s\d{4}\s\d{4}\s\d{4}\s\d{4}\s\d{3}|(?:GB)\d{2}\s[A-Z]{4}\s\d{4}\s\d{4}\s\d{4}\s\d{2}|(?:ES)\d{2}\s\d{4}\s\d{4}\s\d{4}\s\d{4}\s\d{4}' 

Note the following Key Words and Keyword Regex Expression apply to the Bank Acounts for Germany, France, Italy Spain and the UK:

Key Words: IBAN, BBAN, Bank Konto,  Kontonummer,  Bank, Numéro, compte, bancaire, Numero, conto, bancario, Número, cuenta, bancaria, Bank, Account, Number, Intrenational, IBAN 

IBAN Keyword RegEx Expression:  searchctl classifications add --name 'ibankeyword' --regex '((?i)(Bank|Account|Number|Numero|Nummer|Routing|Transit|Bankario|Financial|Institution|German|French|Italian|Spanish|Kontonummer|Compte|Bancaire|Conto|International|Basic|Cuenta|Banco|Konto|Bankaire|Internacional|Internazionale|Internationale|BANK|ACCOUNT|NUMBER|NUMERO|CUENTA|BANCARIA|IBAN|BBAN))' 

Phrase Examples: International Bank Account Number, Basic Bank Account Number, Numero de cuenta de Banco Internacional,  Numero di conto bancario internazionale, Numéro de compte bancaire international, Internationale Kontonummer

Security:

Bank Account Numbers

Germany

Format: DE29 1349 3022 4806 3708 88 

German Bank Account RegEx Expression:  searchctl classifications add --name 'ibande' --regex '(?:DE)\d{2}\s\d{4}\s\d{4}\s\d{4}\s\d{4}\s\d{2}' 

Format:  DE12345678901234567890 

German Bank Account RegEx Expression:  searchctl classifications add --name 'ibande2' --regex '(?:DE)\d{20}' 

Key Words: Bank Konto

German IBAN Keyword RegEx Expression:  searchctl classifications add --name 'debakeyword' --regex '((?i)(Kontonummer|Bank|Konto|konto|IBAN))'  

Phrase Examples: Kontonummer,  Bank Konto

Security: 

France

Format: FR29 9169 9073 6047 1767 2P38 290 

French Bank Account RegEx Expression: searchctl classifications add --name 'ibanfr' --regex '(?:FR)\d{2}\s\d{4}\s\d{4}\s\d{4}\s\d{4}\s\d{1}[A-Z]\d{2}\s\d{3}' 

Format: FR1234567895487613478A12345 

French Bank Account RegEx Expression: searchctl classifications add --name 'ibanfr2' --regex '(?:FR)\d{19}[A-Z]\d{5}' 

Key Words: Numéro de compte bancaire

French IBAN Keyword RegEx Expression: searchctl classifications add --name 'frbakeyword' --regex '((?i)(Numero|compte|bancaire|INUMERO|DE|COMPTE|BANCAIRE|IBAN))'

Phrase Examples: Numéro de compte bancaire, Compte bancaire

Security: 

Italy

Format: IT89 R374 3328 2256 2103 0440 500 

Italian Bank Account RegEx Expression:  searchctl classifications add --name 'ibandit' --regex '(?:IT)\d{2}\s[A-Z]\d{3}\s\d{4}\s\d{4}\s\d{4}\s\d{4}\s\d{3}' 

Format: IT12A1234567891234567891234 

Italian Bank Account RegEx Expression: searchctl classifications add --name 'ibandit2' --regex '(IT)\d{2}[A-Z]\d{22}' 

Key Words: Numero di conto bancario

Italian IBAN Keyword RegEx Expression: searchctl classifications add --name 'itbakeyword' --regex '((?i)(Numero|conto|bancario|di|DI|NUMERO|DI|CONTO|BANCARIO|IBAN))'

Phrase Examples: Numero di conto bancario, Conto bancario

Security: 

Spain

Format: ES00 4514 6356 8256 8068 7871 

RegEx Expression: searchctl classifications add --name 'ibanesp' --regex '(?:ES)\d{2}\s\d{4}\s\d{4}\s\d{4}\s\d{4}\s\d{4}' 

Format: ES1234567901234567890123 

RegEx Expression:  searchctl classifications add --name 'ibanes2' --regex '(?:ES)\d{22}' 

Key Words: Número de cuenta bancaria

Spanish IBAN Keyword RegEx Expression: searchctl classifications add --name 'spbakeyword' --regex '((?i)(Numero|cuenta|bancaria|de|DE|NUMERO|CUENTA|BANCARIA|IBAN))'

Phrase Examples:  Número de cuenta bancaria, Cuenta bancaria

Security: 

United Kingdom

Format: GB96 CZTD 5452 0531 6999 91 

RegEx Expression: searchctl classifications add --name 'ibanduk' --regex '(?:GB)\d{2}\s[A-Z]{4}\s\d{4}\s\d{4}\s\d{4}\s\d{2}' 

Format: GB12ABCD12345678912345 

RegEx Expression:  searchctl classifications add --name 'ibanduk2' --regex '(?:GB)\d{2}[A-Z]{4}\d{14}' 

Key Words: Bank, Account, Number, Intrenational, IBAN

UK IBAN Keyword RegEx Expression: searchctl classifications add --name 'ukbakeyword' --regex '((?i)(Bank|Account|Number|Intrenational|BANK|ACCOUNT|NUMBER|IBAN))'

Phrase Examples:  International Bank Account Number, IBAN Number

Security: 

Bank Account Numbers: Canada and US only

Account Numbers Canada and US

Canadian Account Numbers breakdown:

Financial Institution 3 digits

Bank Transit Number 5 digits

Account Number 7 - 12 digits

Total 15 -20 digits

US Account Numbers Breakdown:

US Routing Number 9 digits

Account Number 10 - 12 digits

Total 19 - 21 Digits

Bank Account Number US (10 - 12 digits) and Canada (7- 12 digits)

US

Format: 10 to 12 digits

US Bank Account RegEx Expression:  searchctl classifications add --name 'usba' --regex '(\d{10,12})' 

Key Words: Bank Account Number

Keyword RegEx Expression: searchctl classifications add --name 'nabakeyword' --regex '((?i)(Bank|Account|Number|BANK|ACCOUNT|NUMBER|Routing|ROUTING|Transit|Financial|Institution|Canadian|Canada|US))' 

Phrase Examples: Bank Account, Bank Account Number

Security: 

Canada

Format: 7 to 12 digits

Canadian Bank Account RegEx Expression:  searchctl classifications add --name 'caba' --regex '(\d{7,12})' 

Key Words: Canadian Bank Account Number

Keyword RegEx Expression: searchctl classifications add --name 'cabakeyword' --regex '((?i)(Bank|Account|Number|BANK|ACCOUNT|NUMBER|Routing|Transit|Financial|Institution|Canadian|Canada))' 

Phrase Examples: Bank Account, Bank Account Number

Security: 

Bank Routing Numbers

US Routing Number

Format: Nine Digit Bank Routing Transit Number complying with ABA Rules:

US Routing Number RegEx Expression: searchctl classifications add --name 'usbr' --regex '((0[0-9])|(1[0-2])|(2[1-9])|(3[0-2])|(6[1-9])|(7[0-2])|80)([0-9]{7})' 

Key Words: Bank Routing Number

Keyword RegEx Expression: searchctl classifications add --name 'usbrkeyword' --regex '((?i)(Bank|Account|Number||BANK|ACCOUNT|NUMBER|ROUTING|Routing|Transit|Financial|Institution|US))' 

Phrase Examples: US Bank Routing Number

Security: Public information

Canadian Routing Numbers

Canadian Routing numbers are composed of a 5 digit Bank Transit Number and a 3 digit Financial Institution number. 

Canadian Routing Number RegEx Expression:  searchctl classifications add --name 'cabr' --regex '(\d{5}-?\s?\d{3})' 

Key Words: Routing Number, Financial Institution, Transit Number

Keyword RegEx Expression: searchctl classifications add --name 'cabrkeyword' --regex '((?i)(Bank|Account|Number||BANK|ACCOUNT|NUMBER|ROUTING|Routing|Transit|Financial|Institution|Canadian|Canada))' 

Phrase Examples: Canadian Bank Routing Number, Financial Institution, Bank Transit Number

Security: Public information

Routing and Bank Account Numbers

US

Format: Nine Digit Bank Routing Transit Number plus 10 to 12 digit Bank Account Number 

US Routing plus Bank Account RegEx Expression:  searchctl classifications add --name 'usbrba' --regex '(((0[0-9])|(1[0-2])|(2[1-9])|(3[0-2])|(6[1-9])|(7[0-2])|80)([0-9]{7}))-?\s?(\d{10,12})' 

Key Words: Bank Account Number

Keyword RegEx Expression: searchctl classifications add --name 'usbrbakeyword' --regex '((?i)(Bank|Account|Number||BANK|ACCOUNT|NUMBER|ROUTING|Routing|Transit|Financial|Institution|US))' 

Phrase Examples: Bank Account Data

Security: 

Canada

Format: 5 digit Bank Transit Number, a 3 digit Financial Institution number and 7 to 12 digit Account Number  

Canadian Routing plus Bank Account RegEx Expression: searchctl classifications add --name 'carba' --regex '(\d{5}-?\s?\d{3}-?\s?\d{7,12})' 

Key Words: Bank Account Number

Keyword RegEx Expression: searchctl classifications add --name 'carbakeyword' --regex '((?i)(Bank|Account|Number||BANK|ACCOUNT|NUMBER|ROUTING|Routing|Transit|Financial|Institution|Canadian|Canada))' 

Phrase Examples: Bank Account Data

Security: 

Credit Card Number

Regex Expression for Visa (Vpay), Visa Electron, AMX, MasterCard, Maestro, Diners Club Cart Blanche, Diners Club International, Diners Club US & Canada, Discover to match Length, IIN Ranges and Spacing Patterns shown in Credit Card IIN Ranges & Spacing Patterns:

searchctl classifications add --name 'creditcard' --regex '((2[2-7]\d{2}-?\s?\d{4}-?\s?\d{4}-?\s?\d{4})|(4\d{3}-?\s?\d{4}-?\s?\d{4}-?\s?\d{4})|(3[0-9]\d{2}-?\s?\d{6}-?\s?\d{4,5})|(5[0-8]\d{2}-?\s?\d{4,6}-?\s?\d{4,5}-?\s?\d{0,4}-?\s?\d{0,3})|(6[0-9]\d{2}-?\s?\d{4,6}-?\s?\d{4,5}-?\s?\d{0,4})-?\s?\d{0,3})'

Key Words: Credit Card, CCN

Keyword RegEx Expression: searchctl classifications add --name 'creditcardkeyword' --regex '((?i)(Credit|Card|Number|Master|Discover|American Express|Maestro|Visa|CC|Diners Club|International|Cart Blanche|Electron|AMX|Kreditkartennummer|Numero|Carte|credito|de|carta|tarjeta))' 

Phrase Example: Credit Card Number, Kreditkartennummer,  Numéro de Carte de Crédit, Numero di carta di credito, Número de tarjeta de crédito, Mastercard, VISA, Discover Card, American Express, AMX, Maestro, Cart Blanche, Diners Club, Diners Club International

Security: 

ACH Format Compliance Check

Automated Clearing House (ACH) is an electronic network for financial transactions. These transactions include credit and debit transactions. ACH credit transfers include direct deposit payroll and vendor payments.Can use the following  RegEx to pattern match numbers to check ACH format compliance, check for 1 to 17 alpha-numerics:  

ACH Format Compliance Check Regex Expression: searchctl classifications add --name 'achcompliance' --regex '\w{1,17}'

Key Words: ACH, ACH Check

Keyword RegEx Expression: searchctl classifications add --name 'achkeyword' --regex '(ACH|Compliance|Check)' 

Phrase Examples: ACH Compliance

Security: 

Credit Card CVV

Format: xx, or xxx, or xxxx

Credit Card CVV RegEx Expression (2 to 4 Digit): searchctl classifications add --name 'cvv' --regex '\d{2,4}' 

Format: xxx

Credit Card CVV RegEx Expression (3 Digit):  searchctl classifications add --name 'cvv3' --regex '\d{3}' 

Key Words: CVV, CVC

Keyword RegEx Expression: searchctl classifications add --name 'cvvkeyword' --regex '((?i)(CVV|CVC|Card|Karten|Verification|Number|Code|Verificacion|Verifiziernummer|Uberprufung|Verifica|Wert|Valeur|Valore|Valor|Le code de|Codigo|Codice|Numero|Nombre|Nummer))' 

Phrase Example: Card Verification Value, Card Verification Code, Credit Card Verification, CVV Number, CVC Number, Credit Verification Value Number, Credit Card Verification Number, Karten Verifiziernummer,  Valeur de vérification de la carte,  Valore di verifica della carta,  valor de verificación de la tarjeta,  Kartenbestätigungscode,  Le code de vérification de carte,  Codice di verifica della carta,  Código de verificación de la tarjeta 

Security: As a stand alone data element there are no restrictions but, In conjunction with Credit Card Number and Expiration Date the following restrictions apply

Expiration Date

Format: mm/yy

Expiration Data RegEx: searchctl classifications add --name 'exp2' --regex '(?:0[1-9]|1[0-2])\/[0-9]{2}' 

Format: mm/yy or mm/yyyy 

Expiration Data RegEx: searchctl classifications add --name 'exp2or4' --regex '(?:0[1-9]|1[0-2])\/[0-9]{2,4}' 

Key Words: Expiration Date, Haltbarkeitsdatum, Ablaufdatum der Kreditkarte, Date d'expiration, Data di scadenza, Fecha de caducidad

Keyword RegEx Expression: searchctl classifications add --name 'ccexpkeyword' --regex '((?i)(Credit|Card|Expiration|Date|Data|Fecha|Haltbarkeitsdatum|Ablaufdatum|Kreditkarte|scadenza|caducidad|Credito|Anerkennung|Credito|Tarjeta|Carta|Carte|Karte))' 

Phrase Examples: Credit Card Expiration, Credit Card Expiration Date, Ablaufdatum der Kreditkarte, Date d'expiration de la carte de crédit, Data di scadenza della carta di credito, Fecha de vencimiento de la tarjeta de crédito

Security: As a stand alone data element there are no restrictions but, In conjunction with Credit Card Number and CVV the following restrictions apply.

Medical Data

Medical Record Number (MRN)

Format: xxx-x-xxxxx, or xxx x xxxxx, or xxxxxxxxx 

Medical Record RegEx Expression:  searchctl classifications add --name 'mrn' --regex '[0-9]{3}-?\s?[0-9]{1}-?\s?[0-9]{5}' 

Format: 05xxxxxxx

Medical Record RegEx Expression: searchctl classification add --name 'usamrn' --regex '(05)\d{7}'

Key Words: MRN, Medical Record Number, Nummer der Krankenakte, Numéro de dossier médical, Numero di cartella clinica, Numero de historia clinica

Keyword RegEx Expression:  searchctl classifications add --name 'mrnkeyword' --regex '((?i)(Medical|Record|Number|MRN|Nummer|Krankenakte|Numero|dossier|medical|cartella|clinica|historia|clinica|Geduldig|Patiente|Patient|Paziente|Paciente|Med Rec))' 

Phrase Example: Patients Medical Record Number, Nummer der Patientenakte, Numéro de dossier médical du patient, Numero di cartella clinica del paziente, Número de historia clínica del paciente

Security: 

National Provider Identifier (NPI)

Format: 10 digits XXXXXXXXXX

RegEx Expression: searchctl classification add --name 'npi' --regex '\d{10}'

 

Key Words: NPI,"National Provider Identifier" 

Keyword RegEx Expression:  searchctl classifications add --name 'npikeyword' --regex '((?i)(NPI|National|Provider|Identifier|ID))' 

Phrase Example: NPI,"National Provider Identifier"  

Security:

Financial Identification Number (FIN)

Format: 1200xxxxxx

RegEx Expression: searchctl classification add --name 'fin' --regex '(1200)\d{6}' 

 

Key Words: FIN,"Financial Identification Number","Financial ID","Patient ID","Encounter ID","Encounter #" 

Keyword RegEx Expression:  searchctl classifications add --name 'finkeyword' --regex '((?i)(FIN|Financial|Identification|Number|ID|Patient|Encounter))' 

Phrase Example: FIN,"Financial Identification Number","Financial ID","Patient ID","Encounter ID","Encounter #"  

Security:

Medical License Number

Format: 2 letter prefix followed by 5 digits (i.e. ME.10003)

RegEx Expression: searchctl classification add --name 'mln' --regex '[A-Z]{2}\.\d{5}' 

 

Key Words: License,"License #","Medical License Number" 

Keyword RegEx Expression:  searchctl classifications add --name 'mlnkeyword' --regex '((?i)(License|Medical|Number|MLN))' 

Phrase Example: FIN,"Financial Identification Number","Financial ID","Patient ID","Encounter ID","Encounter #"  

Security:

J Number

Format: J ollowed by 8 digits (Jxxxxxxxx)

RegEx Expression: searchctl classification add --name 'jnumber' --regex '[Jj][0-9]{8}'' 

 

Key Words: "J #","J Number" 

Keyword RegEx Expression:  searchctl classifications add --name 'Jkeyword' --regex '((?i)(J|Number))' 

Phrase Example: "J #","J Number"   

Security:

DEA Registration Number

Format: 2 letter prefix followed by 7 digits (i.e. MR0622476)

RegEx Expression: searchctl classification add --name 'dea' --regex '[A-HJ-NPR-UX]{1}[A-Z]{1}\d{7}' 

 

Key Words: DEA,"DEA Registration","Drug Enforcement Administration" 

Keyword RegEx Expression:  searchctl classifications add --name 'deakeyword' --regex '((?i)(DEA|Registration|Drug|Enforcement|Administration|Number))' 

Phrase Example: DEA,"DEA Registration","Drug Enforcement Administration"  

Security:

Blood Type

Format: X(+/-)

Blood Type RegEx Expression: searchctl classifications add --name 'bloodtype' --regex '(A|B|AB|O)[+-]' 

Key Words: Blood Type

Keyword RegEx Expression:  searchctl classifications add --name 'btkeyword' --regex '((?i)(Blood Type|Blutgruppe|Groupe sanguin|Gruppo sanguigno|Tipo de sangre))' 

Phrase Example: Blood Type, Blutgruppe, Groupe sanguin, Gruppo sanguigno, Tipo de sangre

Security:

Weight

Metric or English:

Weight RegEx Expression: searchctl classification add --name 'weight' --regex '(\d*\.?\d+)\s*(pounds?|lbs?|lb?|kgs?|kg)'  

Key Words: Weight

Keyword RegEx Expression: searchctl classifications add --name 'weightkeyword' --regex '((?i)(Weight|Gewicht|Poids|Peso))' 

Phrase Example: Weight, Gewicht, Poids, Peso, 

Security:

Height

Format:  cm or ft, in or ‘ “.

RegEx Expression:  searchctl classification add --name 'height' --regex '(\d{1,3}\s?(ft)\s?\d{1,2}\s?(in)?)|(\d*\.?\d*\scm)' 

Format:  cm

RegEx Expression: searchctl classification add --name 'heightm' --regex '(\d*\.?\d*\scm)' 

Format:  ft, in or ', "

RegEx Expression:  searchctl classification add --name 'heighti' --regex '(\d{1,3}'"'"'?\s?(ft)?\s?\d{1,2}\"?\s?(in)?)' 

Note: For English height data, the characters ‘ and “ are format sensitive. For example

5'9" worked

while 

5’6” did not work

Key Words: Height

Keyword RegEx Expression: searchctl classifications add --name 'heightkeyword' --regex '((?i)(Height|Hohe|Hohe|la taille|Taille|Altezza|Altura))' 

Phrase Example: Height, Höhe, la taille, Altezza, Altura

Security: 

Delaware

Format: Delaware driver's license numbers are a seven numbers, unformated. For example:1232805. 

RegEx Expression: searchctl classification add --name 'Delawaredl' --regex '\d{7}' 

 

Security:

Florida

Format: Florida driver's license numbers consist of one letter and 12 numbers, using the format L##-###-##-###-#. For example: G544-061-73-925-0. 

RegEx Expression: searchctl classification add --name 'Floridadl' --regex '[a-zA-Z]\d{3}-\d{3}-\d{2}-\d{3}-\d{1}' 

 

Format: Florida driver's license numbers may also consist of one letter and 12 numbers, unformatted. For example: G544061739250. 

RegEx Expression: searchctl classification add --name 'Floridadl2' --regex '[a-zA-Z]\d{12}' 

Security:

Georgia

Format: Georgia driver's license numbers are nine numbers, unformated. For example: 199999999. 

RegEx Expression: searchctl classification add --name 'Georgiadl' --regex '\d{9}' 

 

Security:

Hawaii

Format: Hawaii driver's license numbers consist of one letter and eight numbers, unformated. For example: H00000002. 

RegEx Expression: searchctl classification add --name 'Hawaiidl' --regex '[a-zA-Z]\d{8}' 

 

Security:

Idaho

Format: Idaho driver's license numbers consist of two letters, six numbers, and one letter. For example: AA123456Z. 

RegEx Expression: searchctl classification add --name 'Idahodl' --regex '[a-zA-Z]{2}\d{6}[a-zA-Z]' 

 

Security:

Illinois

Format: Illinois driver's license numbers consist of one letter and 11 numbers formatted as L###-####-####. For example: D400-7836-0001. 

RegEx Expression: searchctl classification add --name 'IIllinoisdl' --regex '[a-zA-Z]\d{3}-\d{4}-\d{4}' 

Format: Illinois driver's license numbers may also consist of one letter and 11 numbers formatted as L###########. For example: D40078360001.. 

RegEx Expression: searchctl classification add --name 'IIllinoisdl2' --regex '[a-zA-Z]\d{11}' 

 

Security:

Indiana

Format: Indiana driver's license numbers consist of 10 numbers formatted as ####-##-####. For example: 0299-11-6078. 

RegEx Expression: searchctl classification add --name 'Indianadl' --regex '\d{4}-\d{2}-\d{4}' 

 

Security:

Iowa

Format: Iowa driver's license numbers consist of three numbers, two letters, and four numbers. For example: 123AB9755. 

RegEx Expression: searchctl classification add --name 'Iowadl' --regex '\d{3}[a-zA-Z]{2}\d{4}' 

Format: Iowa driver's license numbers may also consist of nine numbers, unformated. For example: 123456789. 

RegEx Expression: searchctl classification add --name 'Iowa9dl' --regex '\d{9}' 

 

Security:

Kansas

Format: Kansas driver's license numbers consist of one letter and eight numbers formatted as L##-##-####. For example: K00-09-7443. 

RegEx Expression: searchctl classification add --name 'Kansasdl' --regex '[a-zA-Z]\d{2}-\d{2}-\d{4}' 

 

Security:

Kentucky

Format: Kentucky driver's license numbers consist of one letter and eight numbers formatted as L##-###-###. For example: V12-345-678. 

RegEx Expression: searchctl classification add --name 'Kentuckydl' --regex '[a-zA-Z]\d{2}-\d{3}-\d{3}' 

 

Security:

Louisiana

Format: Louisiana driver's license numbers are a nine numbers, unformated. For example: 123456789. 

RegEx Expression: searchctl classification add --name 'Louisianadl' --regex '\d{9}'  

 

Security:

Maine

Format: Maine driver's license numbers are seven numbers, unformated. For example: 1234567. 

RegEx Expression: searchctl classification add --name 'Mainedl' --regex '\d{7}'  

 

Security:

Maryland

Format: Maryland driver's license numbers consist of one letter and 12 numbers formatted as L-###-###-###-###. For example: S-514-778-616-977. 

RegEx Expression: searchctl classification add --name 'Marylanddl' --regex '[a-zA-Z]-\d{3}-\d{3}-\d{3}-\d{3}'  

Format: Maryland driver's license numbers may also consist of one letter and 12 numbers, unformatted. For example: S514778616977. 

RegEx Expression: searchctl classification add --name 'Marylandd2l' --regex '[a-zA-Z]\d{12}'  

 

Security:

Massachusetts

Format: Massachusetts driver's license numbers consist of one letter and nine numbers. For example: S99988881. 

RegEx Expression: searchctl classification add --name 'Massachusettsdl' --regex '[a-zA-Z]\d{8}'  

 

Security:

Michigan

Format: Michigan driver's license numbers consist of one letter and 12 numbers formatted as L ### ### ### ###. For example: P 800 000 224 312. 

RegEx Expression: searchctl classification add --name 'Michigandl' --regex '[a-zA-Z]\s\d{3}\s\d{3}\s\d{3}\s\d{3}'  

Format: Michigan driver's license numbers may also be one letter and 12 numbers, unformatted. For example: P800000224322.  

RegEx Expression: searchctl classification add --name 'Michigandl2' --regex '[a-zA-Z]\d{12}'  

 

Security:

Minnesota

Format: Minnesota drivers license consist of one letter and 12 numbers formatted as L-###-###-###-###. For example: S514-778-616-977. 

RegEx Expression: searchctl classification add --name 'Minnesotadl' --regex '[a-zA-Z]\d{3}-\d{3}-\d{3}-\d{3}'  

Format: Minnesota driver's license numbers may also consist of one letter and 12 numbers, unformatted. For example: S514778616977.  

RegEx Expression: searchctl classification add --name 'Minnesotadl2' --regex '[a-zA-Z]\d{12}'  

 

Security:

Mississipi

Format: Mississippi driver's license numbers are nine numbers formatted like a Social Security number as ###-##-####. For example: 125-01-2050. 

RegEx Expression: searchctl classification add --name 'Mississippidl' --regex '\d{3}-\d{2}-\d{4}'  

Format: Mississippi driver's license numbers may may also consist of nine numbers, unformated. For example: 125012050.  

RegEx Expression: searchctl classification add --name 'Mississippidl2' --regex '\d{9}'  

 

Security:

Missouri

Format: Missouri driver's license numbers consist of one letter and nine numbers, unformated. For example: F050256006. 

RegEx Expression: searchctl classification add --name 'Missouridl' --regex '[a-zA-Z]\d{9}'  

 

Security:

Montana

Format: Montana driver's license numbers are 13 numbers: first 2 - month of biirth, next 3 random, next 4 - year of birth, next number is 41, last 2 - day of birth. For example: 0898719684104. 

RegEx Expression: searchctl classification add --name 'Montanadl' --regex '(([0][1-9]|[1][0-2])\d{3}([1-9][0-9]{3})41([0][1-9]|[1][0-9]|[3][0-1]))'  

Format: Prior licenses used either the licensee’s Social Security number or the Social Security number followed by four zeros. For example: 2623806260000. 

RegEx Expression: searchctl classification add --name 'Montanadl2' --regex '\d{9,13}'  

 

Security:

Nebraska

Format: Nebraska driver's license numbers consist of one letter and eight numbers, unformated. For example: A20600249. 

RegEx Expression: searchctl classification add --name 'Nebraskadl' --regex '[a-zA-Z]\d{8}'  

 

Security:

Navada

Format: Nevada driver's license numbers consist of 12 numbers, unformated. For example: 0002102201. 

RegEx Expression: searchctl classification add --name 'Nevadadl' --regex '\d{12}'  

Format: Older Nevada driver's license numbers consist of 9 to 10 numbers, unformated. For example: 626926253. 

RegEx Expression: searchctl classification add --name 'Nevadadl2' --regex '\d{9,10}'  

 

Security:

New Hampshire

Format: The upgraded system now issues New Hampshire driver licenses with three letters and eight randomly assigned digits for a total of 11 characters. For example: NHL12506717. 

RegEx Expression: searchctl classification add --name 'NewHampshiredl' --regex '[a-zA-Z]{3}\d{8}'  

Format: Older New Hampshire driver's license numbers are 10 numbers: First 2 digits - month of birth, next 3 - the first and last letters of last name and the first initial of first name, next 4 - year and date of birth, last random digit. For example: 06HYD46018. 

RegEx Expression: searchctl classification add --name 'NewHampshiredl2' --regex '([0][1-9]|[1][0-2])[a-zA-Z]{3}\d{2}(0[1-9]|[1-2][0-9]|3[0-1])\d'  

 

Security:

New Jersey

Format: New Jersey driver's license numbers consist of one letter and 14 numbers formatted as L####-#####-#####. The first character is the first initial of the last name, next 9 digits are assigned, last 5 digits = the month and year of birth and a code for eye color . For example: A5438 07571 07894. 

RegEx Expression: searchctl classification add --name 'NewJerseydl' --regex '[a-zA-Z]\d{4}\s\d{5}\s\d{5}'  

Format: New Jersey driver's lecense numbers may also consist of one letter followed by 14 digits with no spaces. For example: A54380757107894. 

RegEx Expression: searchctl classification add --name 'NewJerseydl2' --regex '[a-zA-Z]\d{14}'  

 

Security:

New Mexico

Format: New Mexico driver's license numbers are nine numbers, unformated. For example: 113696424. 

RegEx Expression: searchctl classification add --name 'NewMexicodl' --regex '\d{9}'  

 

Security:

New York

Format: New York driver's license numbers are nine numbers formatted as ### ### ###. For example: 123 456 789.. 

RegEx Expression: searchctl classification add --name 'NewYorkdl' --regex '\d{3} \d{3} \d{3}'  

Format: New York driver's license numbers may also consist of nine numbers with no spaces. For example: 123456789.

RegEx Expression: searchctl classification add --name 'NewYorkdl2' --regex '\d{9}'  

 

Security:

North Carolina

Format: North Carolina driver's license numbers are 12 numbers, unformated. For example: 300031499905. 

RegEx Expression: searchctl classification add --name 'NorthCarolinadl' --regex '\d{12}'  

 

Security:

North Dakota

Format: North Dakota driver's license numbers are 3 letters and 6 numbers: first 3 letters of last name, next 2 year of birth, finally 4 digits. For example: HAG-46-7689. 

RegEx Expression: searchctl classification add --name 'NorthDakotadl' --regex '[a-zA-Z]{3}-\d{2}-\d{4}'  

 

Security:

Ohio

Format: Ohio driver's license numbers are two letters and six numbers. For example: TL545796. 

RegEx Expression: searchctl classification add --name 'Ohiodl' --regex '[a-zA-Z]{2}[0-9]{6}'  

 

Security:

Oklahoma

Format: Oklahoma driver's license numbers consist of one letter and nine numbers,unformated. For example: B000062835 . 

RegEx Expression: searchctl classification add --name 'Oklahomadl' --regex '[a-zA-Z]\d{9}'  

 

Security:

Oregon

Format: Oregon driver's license numbers are a seven numbers, unformated. For example: 6110033. 

RegEx Expression: searchctl classification add --name 'Oregondl' --regex '\d{7}'  

 

Security:

Pennsylvania 

Format: Pennsylvania driver's license numbers are eight numbers formatted as ## ### ###. For example: 99 900 104.. 

RegEx Expression: searchctl classification add --name 'Pennsylvaniadl' --regex '\d{2}\s\d{3}\s\d{3}'  

 

Security:

Rhode Island 

Format: Rhode Island driver's license numbers are seven numbers. The first two digits are the year the license was issued (i.e. 2008 is indicated by “28”). For example: 2858889. 

RegEx Expression: searchctl classification add --name 'RhodeIslanddl' --regex '[1-9]{2}\d{5}' 

 

Security:

South Carolina 

Format: South Carolina driver's license numbers are a nine numbers, unformated. For example: 100179226. 

RegEx Expression: searchctl classification add --name 'SouthCarolinadl' --regex '\d{9}'  

 

Security:

South Dakota 

Format: South Dakota driver's license numbers are eight numbers, unformated. For example: 10616775. 

RegEx Expression: searchctl classification add --name 'SouthDakotadl' --regex '\d{8}'  

 

Security:

Tennessee 

Format: Tennessee driver's license numbers can consist of eight or nine numbers, unformated. For example: 101915638. 

RegEx Expression: searchctl classification add --name 'Tennesseedl' --regex '\d{8,9}'  

 

Security:

Texas 

Format: Texas driver's license numbers are eight numbers, unformated. For example: 17600550. 

RegEx Expression: searchctl classification add --name 'Texasdl' --regex '\d{8}'  

 

Security:

Utah 

Format: Utah driver's license numbers are a nine numbers, unformated. For example: 400138831. 

RegEx Expression: searchctl classification add --name 'Utahdl' --regex '\d{9}'  

 

Security:

Vermont

Format: Vermont driver's license numbers are eight numbers, unformated. For example: 17600550. 

RegEx Expression: searchctl classification add --name 'Vermontdl' --regex '\d{8}'  

Format: Vermont driver's license numbers can also consist of seven numbers and one letter. For example: 8205059A. 

RegEx Expression: searchctl classification add --name 'Vermontdl2' --regex '\d{7}[a-zA-Z]'  

 

Security:

© Superna Inc