README.md

---
license: cc-by-sa-4.0
task_categories:
  - text-generation
language:
  - en
tags:
  - base64
  - encoding
  - decoding
  - benchmark
  - evaluation
pretty_name: B64Bench
size_categories:
  - 1K<n<10K
---

# B64Bench

A benchmark dataset for evaluating base64 decoding capabilities of language models.

## Task

Given a base64-encoded string, decode it to recover the original plaintext.

Examples span multiple recursion depths (1-5), meaning the plaintext may itself be a base64-encoded string that requires further decoding.

## Dataset Summary

| Split | Examples | Description |
|---|---|---|
| `test` | 2,999 | Primary evaluation split |
| `val` | 816 | Development / prompt tuning |
| `stress` | 996 | Corruption stress testing |
| `few_shot` | 20 | Curated few-shot prompting pool (separate config) |

**Total**: 4,831 examples across 4 splits. **Evaluation-only** — no training split.

## Loading

```python
from datasets import load_dataset

# Main splits (test, val, stress)
ds = load_dataset("thepushkarp/b64bench")

# Few-shot pool (separate schema)
fs = load_dataset("thepushkarp/b64bench", "few_shot", split="train")
```

## Data Types

Examples are drawn from 11 source text types across three tiers:

### Tier 1 — Primary (~53% of test split)
Anti-memorization data types using random strings.

| Type | Description |
|---|---|
| `random_ascii` | Random printable ASCII characters (chr 32-126) |
| `jwt_length_random` | Random printable ASCII at JWT-typical lengths (120-140 chars) |
| `random_alnum` | Alphanumeric characters only (a-z, A-Z, 0-9) |

### Tier 2 — Secondary (~25% of test split)
Real-world-like data types for ecological validity.

| Type | Description |
|---|---|
| `english_sentence` | Synthetic English sentences from compositional grammar |
| `json_object` | Small JSON objects (`{"key":"value","count":42}`) |
| `shell_command` | Sanitized CLI commands (`git commit -m 'fix bug'`) |
| `uuid` | UUID v4 format strings (always 36 chars) |

### Tier 3 — Edge Cases (~22% of test split)
Structural probes testing specific encoding properties.

| Type | Description |
|---|---|
| `probe_special_chars` | Mixed punctuation and special characters |
| `probe_minimal` | Minimal-length strings (1-3 chars) |
| `probe_boundary` | Strings at specific lengths for padding pattern coverage |
| `probe_high_entropy` | Strings producing high-frequency `+`/`/` in base64 output |

## Recursion Depth

Each example is base64-encoded at a specified recursion depth:

| Depth | Description | % of test |
|---|---|---|
| 1 | Single encode: `text -> base64` | ~27% |
| 2 | Double encode: `base64(base64(text))` | ~24% |
| 3 | Triple encode | ~20% |
| 4 | Quadruple encode | ~16% |
| 5 | Quintuple encode | ~13% |

Higher depths produce longer base64 strings and require multi-step decoding. The depth-length feasibility constraint caps b64 output at ~1024 characters.

## Corruptions

The `surface_b64` field may contain a corrupted version of the `canonical_b64`. Corrupted examples link to their clean parent via `parent_example_id`.

| Corruption | What It Does | Recoverable? |
|---|---|---|
| `none` | Clean, valid base64 | Yes |
| `missing_padding` | Trailing `=` chars stripped | Yes (re-pad) |
| `whitespace` | Random space/newline/tab inserted | Yes (strip) |
| `base64url` | `+` -> `-`, `/` -> `_`, optional padding strip | Yes (translate) |
| `substitution` | One non-padding char replaced with different b64 char | No |
| `illegal_char` | One char replaced with illegal character (`@#$%^&*?`) | No |
| `truncation` | 1-3 chars removed from end | No |

## Schema

Each example has 27 fields:

| Field | Type | Description |
|---|---|---|
| `example_id` | string | Unique identifier (`test-00000042`) |
| `parent_example_id` | string or null | Links corrupted example to clean parent |
| `split` | string | `test`, `val`, or `stress` |
| `schema_version` | string | `1.0.0` |
| `root_seed` | int | Global seed for reproducibility |
| `example_seed` | int | Per-example seed (blake2b-derived) |
| `data_type` | string | Source text type (see Data Types) |
| `data_tier` | string | `primary`, `secondary`, or `edge_case` |
| `source_url` | string or null | Provenance URL (null for synthetic) |
| `source_license` | string | `CC0` |
| `source_text` | string | Original plaintext |
| `source_length_chars` | int | Character count of source |
| `source_length_bytes` | int | UTF-8 byte count of source |
| `recursion_depth` | int | Number of base64 encoding layers (1-5) |
| `intermediate_b64_levels` | list[string] | All encoding layers |
| `canonical_b64` | string | Final (outermost) base64 string |
| `surface_b64` | string | What the model sees (may be corrupted) |
| `b64_length` | int | Length of `canonical_b64` |
| `b64_num_blocks` | int | Number of 4-char base64 blocks |
| `b64_padding_chars` | int | Count of `=` in `canonical_b64` (0, 1, or 2) |
| `b64_has_plus` | bool | Whether `canonical_b64` contains `+` |
| `b64_has_slash` | bool | Whether `canonical_b64` contains `/` |
| `corruption_name` | string | Corruption type applied (see Corruptions) |
| `corruption_params` | dict | Corruption-specific parameters |
| `normalization_recoverable` | bool | Can standard normalization recover the original? |
| `original_recoverable` | bool | Is the original text recoverable at all? |
| `target_text` | string | Ground truth decoded output |

## Generation

The dataset is generated deterministically from a root seed (default: 42) using blake2b-derived per-example seeds. This makes generation order-independent and reproducible.

To regenerate:

```bash
uv run python scripts/generate_dataset.py --seed 42 --validate --summary
```

## Canary

This dataset contains the canary string `CANARY_b64bench_2026_DO_NOT_TRAIN` in its metadata. It is intended for evaluation only and should not be included in language model training data.

## Citation

```bibtex
@dataset{b64bench2026,
  title={B64Bench: A Base64 Decoding Benchmark},
  author={Pushkar Patel},
  year={2026},
  url={https://huggingface.co/datasets/thepushkarp/b64bench}
}
```

## License

CC-BY-SA-4.0