---
license: mit
task_categories:
  - tabular-classification
tags:
  - pdf
  - pdf-repair
  - test-corpus
  - synthetic
pretty_name: PDF Corruption Lab
size_categories:
  - 1K<n<10K
configs:
  - config_name: features
    data_files: features/train.csv
    default: true
---

# pdf-corruption-lab

A **fully synthetic** corpus of damaged PDF files with a known kind and severity
of damage, the scripts that generate it, and a ready-to-use feature table.
It is meant for testing and benchmarking PDF repair / recovery tools and for
training small damage-type classifiers.

Everything here is original: documents are built from scratch with
[`pdf-lib`](https://github.com/Hopding/pdf-lib) (MIT). No third-party
documents or models are included.

## What is in this repository

| Path | Description |
|---|---|
| `output/` | 7 hand-checkable reference files: one valid PDF and 6 damaged variants, plus `manifest.json` |
| `training/` | 1,200 randomized PDFs (200 per class: pages, fonts, text and images vary) and `labels.csv` |
| `features/train.csv` | 12 byte-level structural features + label for each training file (powers the dataset viewer) |
| `generate.js` | regenerates the reference files in `output/` |
| `gen_training.js` | regenerates the randomized training set (seeded, reproducible) |

## Damage classes

| Class | Damage | Severity (1-5) |
|---|---|---|
| `valid` | none | 0 |
| `missing_eof` | trailing `%%EOF` removed | 1 |
| `invalid_startxref` | `startxref` value is non-numeric | 2 |
| `scrambled_xref` | xref offsets replaced with bogus values | 3 |
| `bad_root_reference` | trailer `/Root` points to a missing object | 3 |
| `truncated` | file cut at a random point (30-90 % of its length) | 4-5 |

## Features (`features/train.csv`)

`has_pdf_header`, `eof_in_last_1k`, `ends_with_eof`, `startxref_present`,
`startxref_numeric`, `startxref_points_to_xref`, `xref_valid_fraction`,
`has_trailer`, `root_object_exists`, `obj_endobj_gap`, `stream_endstream_gap`,
`log10_size`, and `label`. The extraction code is in the model repo:
[`utilvo-com/pdf-damage-classifier`](https://huggingface.co/utilvo-com/pdf-damage-classifier).

## Regenerate

```bash
npm install
node generate.js ./output
node gen_training.js ./training 200
```

## Suggested evaluation for repair tools

For each damaged file, run your tool and record:

1. Does the output open in a strict parser?
2. How many pages were recovered?
3. Was the embedded image preserved (where present)?

## Limitations

All files are generated by `pdf-lib` with classic xref tables (no object streams
or xref streams) and each file has a single kind of damage. Real-world
corruption (bit flips, mixed damage, files from other producers, encryption) is
not represented. Treat results here as a controlled benchmark, not as a
guarantee for real files.

## Disclosure

Maintained by the Utilvo team. The organization profile links to our website.

## License

MIT. See `LICENSE`.