Local-only hashing toolkit

OzHashKit

Hash local files or pasted text, compare expected checksums, measure similarity, and export manifests without uploading your data.

Local browser processing No upload Similarity comparison included
Setup

Choose what you want to verify

Use file mode for release artifacts and downloads, or text mode for quick payload checks and copied values.

Switch between local file hashing and pasted text hashing.

Use SHA-256 for most checksum sharing unless you need a different format.

Drop files here

SHA-1, SHA-256, SHA-384, and SHA-512 all run locally in your browser.

OzHashKit can auto-detect the likely algorithm from the checksum length when it matches a known SHA/MD5 pattern.

Checksum comparison works best with a single current result.

Checksum detection

Paste an expected checksum to show the likely algorithm and compare it with the current result.

Use CSV for spreadsheets, checksum sums for release packages, or Markdown for team notes.

The selected manifest style controls the final file extension when you download.

Hash results

Name Size Hash Status

Manifest preview

You can copy or download the current manifest without uploading your files or text.

Common use cases
  • Verify downloaded files before opening or sharing them.
  • Compare release artifacts between environments or team handoff points.
  • Generate checksum manifests for deployment or release notes.
Compare locally

Compare text, files, and duplicate candidates

Comparison happens locally in your browser. OzHashKit does not upload your files or text.

Comparison note

Exact matches come from hashes. Similarity for non-identical files is heuristic unless the files are treated as text and compared directly.

Text Compare

Compare two text blocks

Normalized Levenshtein similarity and token overlap both run locally.

File Compare

Compare two files

SHA-256 runs first. If files differ, OzHashKit uses a safe local heuristic based on file type.

Batch Duplicate Finder

Group exact duplicates and likely candidates

Exact duplicate groups scale well. Heuristic similarity checks stay limited and optional.

No batch analysis is running.