Datasets:

Attestable
/

scam-detection-corpus

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
id: string
username: string
bio: string
account_age_days: int64
ground_truth_verdict: string
ground_truth_scam_type: string
source: string
notes: string
category: string
text: string
to
{'id': Value('string'), 'category': Value('string'), 'text': Value('string'), 'ground_truth_verdict': Value('string'), 'ground_truth_scam_type': Value('string'), 'source': Value('string'), 'notes': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              id: string
              username: string
              bio: string
              account_age_days: int64
              ground_truth_verdict: string
              ground_truth_scam_type: string
              source: string
              notes: string
              category: string
              text: string
              to
              {'id': Value('string'), 'category': Value('string'), 'text': Value('string'), 'ground_truth_verdict': Value('string'), 'ground_truth_scam_type': Value('string'), 'source': Value('string'), 'notes': Value('string')}
              because column names don't match

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Attestable Scam Detection Corpus v0.1

Matched-pair adversarial training data for AI safety classifiers. 153 human-crafted examples across 7 scam categories with published detection rates and full provenance.

Published Detection Rates

Pipeline	F1	Precision	Recall	False Negatives
Heuristic-only	0.703	0.889	0.582	23/55
Full AI (DeepSeek V4 Pro)	0.981	1.000	0.964	2/55

Dataset Structure

Split	Scam	Safe	Total
Green-team messages	60	30	90
Red-team adversarial	25	2	27
Green-team profiles	15	13	28
Red-team profiles	8	0	8
Total	108	45	153

Adversarial Coverage

Red-team corpus tests evasion techniques: Unicode homoglyphs, zero-width injection, leetspeak, prompt injection, boundary probing, category blindspots.

Data Format

JSONL. Each line:

{
  "id": "unique identifier",
  "category": "phishing|crypto_drainer|impersonation|...",
  "text": "The message or profile text",
  "ground_truth_verdict": "safe|suspicious|dangerous",
  "ground_truth_scam_type": "...",
  "source": "public-pattern-reconstruction|synthetic-benign",
  "notes": "Human context about detection challenge"
}

Licensing

Commercial license. Research use permitted with attribution. Contact for commercial terms.

Built by House Attestable. Methodology: green-team evaluation → red-team adversarial testing → public disclosure.

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