ShareSafe Local only
How it worksVerify “local only”

Anonymize CSV files and keep the IDs linked

Replace customer IDs, names, emails and phone numbers column by column. The same ID gets the same placeholder in every file, so joins between customers.csv and orders.csv still work.

Drop files here

Files are read in this tab and never uploaded.

  • .json
  • .csv
  • .tsv
  • .log
  • .txt

Up to 10 files, 10.0 MB each, 30.0 MB in total. UTF-8 only.

Two exports, one customer

− before+ after
customers.csv
Before: C-1001,Gina Example,gina@example.com
After: customer_001,name_001,person_001@example.invalid
orders.csv
Before: ORD-5001,C-1001,49.00,refunded
After: order_001,customer_001,49.00,refunded
orders.csv
Before: "Card declined, retry on C-1001"
After: "Card declined, retry on customer_001"

C-1001 is customer_001 in both files, including inside the free-text notes column.

How it works

  1. Add files

    Drop JSON, CSV or log files, or paste text. They are read in this tab; nothing is uploaded.

  2. Choose what to hide

    Suggestions find IDs, emails, names, order numbers and keys. Fields that hold the same values share one numbering.

  3. Review & download

    Compare before and after, check what may remain, then download the files with a short report.

How CSV files are handled

Linked columns

Columns are suggested by header name. When two columns hold mostly the same values — at least 30% of the smaller set, within the same category — they share one numbering automatically. Weaker overlaps are shown as a Merge / Keep separate prompt, so a customer_id column is never silently merged with an unrelated ID.

Supported files

  • .csv and .tsv with comma, semicolon, tab or pipe delimiters, detected automatically or set by hand.
  • Quoted cells, escaped quotes, multi-line cells, empty cells and a UTF-8 byte-order mark.
  • A header row, or none: switch it off and columns are addressed by position.

What is preserved

Output is produced by editing the selected cells only. Unchanged cells keep their exact quoting; a changed cell keeps its quotes, and an unquoted cell is quoted only if the new value needs it. Each such change is listed per file. Amounts, dates and other columns you did not select are untouched.

Pseudonymized is not anonymous

Consistent placeholders keep records linkable — that is the point — but the remaining columns (country, dates, amounts) can still identify a person in combination. Under the GDPR, pseudonymised data is still personal data (Regulation (EU) 2016/679, Article 4(5) and Recital 26).

What it does not do

  • Header names are not replaced, only cell values.
  • Indirect identifiers such as birth dates or postcodes are not suggested unless the column name says so; add them by hand.
  • Files with mixed line endings outside quoted cells are rejected as ambiguous.
  • Excel files must be exported to CSV first. Spreadsheet formula escaping is not applied.
  • UTF-8 only; up to 10 files, 10 MB each and 30 MB in total.

Questions

Will the same customer ID match across files?

Yes, when both columns are in the same numbering. Overlapping columns are grouped automatically; you can also merge or split numberings by hand, and the checks warn if one value ended up with two placeholders.

How is this different from hashing the column?

An unsalted hash of a short ID can be reversed by hashing every possible ID. ShareSafe assigns counters (customer_001, customer_002…) that are not derived from the original value, and the mapping never leaves the tab.

Can I use JSON or log files in the same task?

Yes — up to 10 files of any supported format. See redacting JSON and redacting log files.

Replacing selected values does not guarantee anonymity. Suggestions are hints, not a complete scan; review the output before sharing it.

Last reviewed .