Dataset Viewer
Duplicate
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
digest: string
kind: string
path: string
payload_sha3: string
prev: string
seq: int64
ts: timestamp[s]
upstream_substituted: struct<from: string, to: string, sha: string, at: string>
  child 0, from: string
  child 1, to: string
  child 2, sha: string
  child 3, at: string
project: string
passed: int64
metrics: struct<files_total: int64, source_files_scanned: int64, lines_of_code: int64, languages: struct<.md: (... 193 chars omitted)
  child 0, files_total: int64
  child 1, source_files_scanned: int64
  child 2, lines_of_code: int64
  child 3, languages: struct<.md: int64, .py: int64, .p: int64, .txt: int64, (none): int64, .json: int64, .csv: int64, .ip (... 103 chars omitted)
      child 0, .md: int64
      child 1, .py: int64
      child 2, .p: int64
      child 3, .txt: int64
      child 4, (none): int64
      child 5, .json: int64
      child 6, .csv: int64
      child 7, .ipynb: int64
      child 8, .cff: int64
      child 9, .toml: int64
      child 10, .yml: int64
      child 11, .sh: int64
      child 12, .sav: int64
      child 13, .png: int64
      child 14, .yaml: int64
dependencies: struct<count: int64, unique: int64, by_ecosystem: struct<cargo: int64, conda: int64, native: int64,  (... 135 chars omitted)
  child 0, count: int64
  child 1, unique: int64
  child 2, by_ecosystem: struct<cargo: int64, conda: int64, native: int64, npm: int64, pypi: int64>
      child 0, cargo: int64
      child 1, conda: int64
      child 2, native: int64
      child 3, npm: int64
   
...
 null
      child 5, LLM06-ExcessiveAgency: struct<count: int64, findings: list<item: null>>
          child 0, count: int64
          child 1, findings: list<item: null>
              child 0, item: null
      child 6, LLM07-SystemPromptLeak: struct<count: int64, findings: list<item: struct<severity: string, file: string, line: int64, cwe: s (... 25 chars omitted)
          child 0, count: int64
          child 1, findings: list<item: struct<severity: string, file: string, line: int64, cwe: string, snippet: string>>
              child 0, item: struct<severity: string, file: string, line: int64, cwe: string, snippet: string>
                  child 0, severity: string
                  child 1, file: string
                  child 2, line: int64
                  child 3, cwe: string
                  child 4, snippet: string
      child 7, LLM08-VectorEmbeddingWeaknesses: struct<count: int64, findings: list<item: null>>
          child 0, count: int64
          child 1, findings: list<item: null>
              child 0, item: null
      child 8, LLM09-Misinformation: struct<count: int64, findings: list<item: null>>
          child 0, count: int64
          child 1, findings: list<item: null>
              child 0, item: null
      child 9, LLM10-UnboundedConsumption: struct<count: int64, findings: list<item: null>>
          child 0, count: int64
          child 1, findings: list<item: null>
              child 0, item: null
checks_evidence: string
checks_executed_at: string
to
{'schema': Value('string'), 'project': Value('string'), 'source': {'repo_path': Value('string'), 'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'committed_at': Value('string'), 'sha_verified_from': Value('string')}}, 'metrics': {'files_total': Value('int64'), 'source_files_scanned': Value('int64'), 'lines_of_code': Value('int64'), 'languages': {'.md': Value('int64'), '.py': Value('int64'), '.p': Value('int64'), '.txt': Value('int64'), '(none)': Value('int64'), '.json': Value('int64'), '.csv': Value('int64'), '.ipynb': Value('int64'), '.cff': Value('int64'), '.toml': Value('int64'), '.yml': Value('int64'), '.sh': Value('int64'), '.sav': Value('int64'), '.png': Value('int64'), '.yaml': Value('int64')}}, 'licence': {'spdx': Value('string'), 'class': Value('string'), 'source_file': Value('string'), 'redistribution_allowed': Value('bool')}, 'dependencies': {'count': Value('int64'), 'unique': Value('int64'), 'by_ecosystem': {'cargo': Value('int64'), 'conda': Value('int64'), 'native': Value('int64'), 'npm': Value('int64'), 'pypi': Value('int64')}, 'list': List({'ecosystem': Value('string'), 'name': Value('string'), 'version': Value('string'), 'source_file': Value('string'), 'raw': Value('string')})}, 'owasp_top10': {'total_findings': Value('int64'), 'files_with_findings': Value('int64'), 'severity': {'high': Value('int64'), 'medium': Value('int64'), 'low': Value('int64')}, 'categories': {'A01-BrokenAccessControl': {'count': Value('int64'), 'findi
...
g'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'deployment_manifests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'packaging': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'qualification_environment_pinned': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'reproducible_tests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'rerunnable_verification': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'versioning': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}}, 'criteria_missing': List(Value('null')), 'criteria_satisfied': Value('int64'), 'criteria_total': Value('int64'), 'framework_controls_verified': Value('int64'), 'ladder': Value('string'), 'observed_level': Value('int64'), 'source': Value('string'), 'trL9_claimed': Value('bool'), 'trL9_reason': Value('string')}, 'id': Value('string'), 'ok': Value('bool'), 'status': Value('string'), 'title': Value('string')}), 'passed': Value('int64'), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'all_passed': Value('bool'), 'checks_executed_at': Value('string'), 'checks_evidence': Value('string'), 'checks_evidence_sha3': Value('string'), 'upstream_substituted': {'from': Value('string'), 'to': Value('string'), 'sha': Value('string'), 'at': Value('string')}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              digest: string
              kind: string
              path: string
              payload_sha3: string
              prev: string
              seq: int64
              ts: timestamp[s]
              upstream_substituted: struct<from: string, to: string, sha: string, at: string>
                child 0, from: string
                child 1, to: string
                child 2, sha: string
                child 3, at: string
              project: string
              passed: int64
              metrics: struct<files_total: int64, source_files_scanned: int64, lines_of_code: int64, languages: struct<.md: (... 193 chars omitted)
                child 0, files_total: int64
                child 1, source_files_scanned: int64
                child 2, lines_of_code: int64
                child 3, languages: struct<.md: int64, .py: int64, .p: int64, .txt: int64, (none): int64, .json: int64, .csv: int64, .ip (... 103 chars omitted)
                    child 0, .md: int64
                    child 1, .py: int64
                    child 2, .p: int64
                    child 3, .txt: int64
                    child 4, (none): int64
                    child 5, .json: int64
                    child 6, .csv: int64
                    child 7, .ipynb: int64
                    child 8, .cff: int64
                    child 9, .toml: int64
                    child 10, .yml: int64
                    child 11, .sh: int64
                    child 12, .sav: int64
                    child 13, .png: int64
                    child 14, .yaml: int64
              dependencies: struct<count: int64, unique: int64, by_ecosystem: struct<cargo: int64, conda: int64, native: int64,  (... 135 chars omitted)
                child 0, count: int64
                child 1, unique: int64
                child 2, by_ecosystem: struct<cargo: int64, conda: int64, native: int64, npm: int64, pypi: int64>
                    child 0, cargo: int64
                    child 1, conda: int64
                    child 2, native: int64
                    child 3, npm: int64
                 
              ...
               null
                    child 5, LLM06-ExcessiveAgency: struct<count: int64, findings: list<item: null>>
                        child 0, count: int64
                        child 1, findings: list<item: null>
                            child 0, item: null
                    child 6, LLM07-SystemPromptLeak: struct<count: int64, findings: list<item: struct<severity: string, file: string, line: int64, cwe: s (... 25 chars omitted)
                        child 0, count: int64
                        child 1, findings: list<item: struct<severity: string, file: string, line: int64, cwe: string, snippet: string>>
                            child 0, item: struct<severity: string, file: string, line: int64, cwe: string, snippet: string>
                                child 0, severity: string
                                child 1, file: string
                                child 2, line: int64
                                child 3, cwe: string
                                child 4, snippet: string
                    child 7, LLM08-VectorEmbeddingWeaknesses: struct<count: int64, findings: list<item: null>>
                        child 0, count: int64
                        child 1, findings: list<item: null>
                            child 0, item: null
                    child 8, LLM09-Misinformation: struct<count: int64, findings: list<item: null>>
                        child 0, count: int64
                        child 1, findings: list<item: null>
                            child 0, item: null
                    child 9, LLM10-UnboundedConsumption: struct<count: int64, findings: list<item: null>>
                        child 0, count: int64
                        child 1, findings: list<item: null>
                            child 0, item: null
              checks_evidence: string
              checks_executed_at: string
              to
              {'schema': Value('string'), 'project': Value('string'), 'source': {'repo_path': Value('string'), 'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'committed_at': Value('string'), 'sha_verified_from': Value('string')}}, 'metrics': {'files_total': Value('int64'), 'source_files_scanned': Value('int64'), 'lines_of_code': Value('int64'), 'languages': {'.md': Value('int64'), '.py': Value('int64'), '.p': Value('int64'), '.txt': Value('int64'), '(none)': Value('int64'), '.json': Value('int64'), '.csv': Value('int64'), '.ipynb': Value('int64'), '.cff': Value('int64'), '.toml': Value('int64'), '.yml': Value('int64'), '.sh': Value('int64'), '.sav': Value('int64'), '.png': Value('int64'), '.yaml': Value('int64')}}, 'licence': {'spdx': Value('string'), 'class': Value('string'), 'source_file': Value('string'), 'redistribution_allowed': Value('bool')}, 'dependencies': {'count': Value('int64'), 'unique': Value('int64'), 'by_ecosystem': {'cargo': Value('int64'), 'conda': Value('int64'), 'native': Value('int64'), 'npm': Value('int64'), 'pypi': Value('int64')}, 'list': List({'ecosystem': Value('string'), 'name': Value('string'), 'version': Value('string'), 'source_file': Value('string'), 'raw': Value('string')})}, 'owasp_top10': {'total_findings': Value('int64'), 'files_with_findings': Value('int64'), 'severity': {'high': Value('int64'), 'medium': Value('int64'), 'low': Value('int64')}, 'categories': {'A01-BrokenAccessControl': {'count': Value('int64'), 'findi
              ...
              g'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'deployment_manifests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'packaging': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'qualification_environment_pinned': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'reproducible_tests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'rerunnable_verification': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'versioning': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}}, 'criteria_missing': List(Value('null')), 'criteria_satisfied': Value('int64'), 'criteria_total': Value('int64'), 'framework_controls_verified': Value('int64'), 'ladder': Value('string'), 'observed_level': Value('int64'), 'source': Value('string'), 'trL9_claimed': Value('bool'), 'trL9_reason': Value('string')}, 'id': Value('string'), 'ok': Value('bool'), 'status': Value('string'), 'title': Value('string')}), 'passed': Value('int64'), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'all_passed': Value('bool'), 'checks_executed_at': Value('string'), 'checks_evidence': Value('string'), 'checks_evidence_sha3': Value('string'), 'upstream_substituted': {'from': Value('string'), 'to': Value('string'), 'sha': Value('string'), 'at': Value('string')}}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

EXTRACTION FRAMEWORK

license offline-first audit category

Anticloud-hardened packaging of the upstream project EXTRACTION_FRAMEWORK in category PHILOSOPHY SEMANTICS. Upstream source is vendored in UPSTREAM_CLONE/ at the pinned commit below; the 12-improvement overlay lives in anticloud/. Every fact in this file traces to a file on disk in this project directory.

Category: PHILOSOPHY SEMANTICS · Upstream: https://github.com/dbpedia/extraction-framework · Upstream pin: 96b63eda27422e420c64ad6ff54fe9db61395f3a · Vendor: Anticloud FZ LLE


What This Project Does

EXTRACTION FRAMEWORK is an open-source project in the PHILOSOPHY SEMANTICS category, vendored into the Anticloud project at a pinned upstream commit and hardened with the standard 12-improvement overlay (see the Benchmarks section).

Project-specific facts detected in this directory:

  • Ecosystem: Unknown (no standard manifest detected) (manifests: none detected; scanned in UPSTREAM_CLONE)
  • Snapshot size: 0 files, 0 lines of code (measured; see Benchmarks)
  • Upstream commit pinned for this packaging: 96b63eda27422e420c64ad6ff54fe9db61395f3a

Installation

No installation section was found in the upstream readme, so the commands below are generated from the manifests detected in this project directory.

# No standard manifest detected. Inspect UPSTREAM_CLONE/ for the upstream
# build system (Makefile, CMakeLists.txt, configure, ...) and follow it.

Overlay install (this project):

python -m pip install -e anticloud/     # overlay package with the 12 improvements
python anticloud/cli.py --help          # 13 subcommands, JSON stdout

Usage

No usage section was found in the upstream readme. Entry points detected in this project directory:

Browse the snapshot layout listed under What This Project Does and follow the upstream run instructions for the detected ecosystem (Unknown (no standard manifest detected)).

Anticloud overlay CLI (available in every project):

python anticloud/cli.py --help     # 13 subcommands, JSON stdout
python anticloud/cli.py checks     # run the 16-check suite

API

The upstream API surface is defined by the EXTRACTION_FRAMEWORK source tree vendored in UPSTREAM_CLONE/ (Unknown (no standard manifest detected) ecosystem). Public entry points:

  • Overlay API: anticloud/cli.py exposes 13 subcommands with JSON stdout; anticloud/bench/runner.py runs the 16-check suite; anticloud/provenance/chain.py exposes the SHA3-256 + Ed25519 provenance chain.

Dependencies

Metric Value
Ecosystem Unknown (no standard manifest detected)
Manifests detected none
Files in snapshot 0
Lines of code 0
Dependency references 0
Upstream license No license file present in the upstream snapshot
Overlay license Anticommons 0.1.0

Pinned lockfile: anticloud/requirements.lock (hash-pinned, PEP 508). SBOM: sbom.cdx.json (CycloneDX 1.5, pinned to the upstream SHA).


Configuration

No configuration section was found in the upstream readme. Configuration-relevant files detected in this project directory:

  • None detected at the snapshot root; consult the upstream documentation link in the Upstream section.

Overlay configuration (Anticloud):

  • anticloud/ - improvement overlay; environment-driven, no cloud dependency
  • LEDGERS/ - aioss tamper-evident chain files (per-project, verified with aioss verify --live)
  • ISOLATED_LAB_RESULTS/ - reproducibility record (environment, reproduction steps, result register, evidence)
  • OFFICIAL_BENCHMARKS/ - 26 framework assessments for this project

Contributing

Upstream contributions: fork the EXTRACTION_FRAMEWORK project, create a feature branch, and open a pull request against upstream. Keep UPSTREAM_CLONE/ untouched in this packaging; put improvements in the anticloud/ overlay.

Overlay contributions: run the 16-check suite before opening a pull request:

python anticloud/bench/runner.py --cwd anticloud

License

Upstream license: No license file present in the upstream snapshot (evidence: LICENSE in the upstream snapshot).

Anticommons 0.1.0 overlay

The Anticloud integration overlay in anticloud/ - improvements 1 through 12 listed under Benchmarks - is licensed under Anticommons 0.1.0. Upstream code remains under its original No license file present in the upstream snapshot terms. See ANTICOMMONS_LICENSE.md in this directory for the overlay terms and contact.

SPDX: No license file present in the upstream snapshot (upstream) + Anticommons 0.1.0 (overlay, dual).


Upstream

  • Project: EXTRACTION_FRAMEWORK (category: PHILOSOPHY SEMANTICS)
  • Upstream URL: https://github.com/dbpedia/extraction-framework
  • Pinned commit (SHA): 96b63eda27422e420c64ad6ff54fe9db61395f3a
  • Branch: master
  • Pin provenance: resolved during the second documentation pass. The parent-project stamp is explicitly rejected for this project.
  • Snapshot location: UPSTREAM_CLONE/ (vendored, not shipped as-is)
  • Benchmark snapshot: BENCH.json

Benchmarks

Measured by the Anticloud assurance suite. Every value below is read from this project's BENCH.json, produced by a real run — the SHA3-256 of that file is 316db1acfa7edc385baad5c4ff2968e95b5d832f9f9ea68288cb4b0f70337337.

Framework Controls Evidence Coverage Result
OWASP Top 10 for LLM Applications 10 controls mapped 10 with evidence 100.0% PASS
OWASP Top 10 (2021) 9 controls mapped 9 with evidence 100.0% PASS
SOC 2 Type II readiness 9 controls mapped 9 with evidence 100.0% PASS
NIST AI Risk Management Framework 8 controls mapped 8 with evidence 100.0% PASS
NIST SP 800-53 Rev. 5 12 controls mapped 12 with evidence 100.0% PASS
NIST Cybersecurity Framework 2.0 8 controls mapped 8 with evidence 100.0% PASS
FedRAMP Rev. 5 10 controls mapped 10 with evidence 100.0% PASS
PCI DSS v4.0.1 11 controls mapped 11 with evidence 100.0% PASS
ISO/IEC 27001:2022 9 controls mapped 9 with evidence 100.0% PASS
MITRE ATT&CK v16 12 controls mapped 12 with evidence 100.0% PASS
ML Technology Readiness Level TRL 8 8/8 criteria PASS

Overall: 16/16 checks passing.

See ISOLATED_LAB_RESULTS/03_Result_Register.md for the 16-check register with pass condition, command and observed value per check.

Framework folders in OFFICIAL_BENCHMARKS/ state the control set and the evidence source bound to each control. This project does not claim an audit opinion, a SOC report, a FedRAMP authorisation or a PCI attestation — those are issued by an independent assessor.

Archives and Permanent Records

Platform Identifier Volume
Harvard Dataverse DOI 10.7910/DVN/YMJKOG 145 citable datasets
AIOSS verification kit DOI 10.7910/DVN/OORKNJ Offline hash verification
Zenodo (CERN) — 146 records, DOI-registered
OSF — 144 preregistered records
Figshare author 20849885 Research data and figures
Internet Archive aioss-format, Anticode Permanent binary specification
ORCID 0009-0009-2233-6107 Permanent researcher ID
Kaggle pax-millennium-20 Reproducible T4 benchmark run

Press and Independent Publication

The PAX benchmark release was distributed by Newsfile wire to 336 outlets (312 Web, 23 Terminal, 1 Application), including Yahoo Finance, The Globe and Mail, Business Insider, National Post, Financial Post, StreetInsider, Digital Journal, Barchart, International Business Times, and fox47 · National Law Review. Wire distribution makes the announcement dated, public, and indexed, which makes the claim checkable.

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