Hugging Face's logo

Datasets:
Anticloud
/
anticloud-stardog

Dataset card Files
xet
 Community
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]
method: struct<aggregate_rule: string, excluded: string, reproduce: string, thresholds_note: string>
  child 0, aggregate_rule: string
  child 1, excluded: string
  child 2, reproduce: string
  child 3, thresholds_note: string
sbom_written: bool
platform: string
version: string
failed: int64
passed: int64
source: struct<git: struct<head: string, url: string, branch: string, sha_verified_from: string>>
  child 0, git: struct<head: string, url: string, branch: string, sha_verified_from: string>
      child 0, head: string
      child 1, url: string
      child 2, branch: string
      child 3, sha_verified_from: string
python: string
schema: string
total: int64
benchmarks: list<item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: i (... 3044 chars omitted)
  child 0, item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code (... 3032 chars omitted)
      child 0, evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code_lines: int64, co (... 2961 chars omitted)
          child 0, ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>
              child 0, max_files: int64
              child 1, max_lines: int64
              child 2, min_lines: int64
          child 1, code_lines: int64
          child 2, command: string
          child 
...
ail: string, evidence_path: string, present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
              child 5, reproducible_tests: struct<detail: string, evidence_path: string, present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
              child 6, rerunnable_verification: struct<detail: string, evidence_path: string, present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
              child 7, versioning: struct<detail: string, evidence_path: string, present: bool>
                  child 0, detail: string
                  child 1, evidence_path: string
                  child 2, present: bool
          child 62, criteria_missing: list<item: null>
              child 0, item: null
          child 63, criteria_satisfied: int64
          child 64, criteria_total: int64
          child 65, framework_controls_verified: int64
          child 66, ladder: string
          child 67, observed_level: int64
          child 68, source: string
          child 69, trL9_claimed: bool
          child 70, trL9_reason: string
      child 1, id: string
      child 2, ok: bool
      child 3, status: string
      child 4, title: string
root: string
all_passed: bool
failed_ids: list<item: null>
  child 0, item: null
to
{'all_passed': Value('bool'), 'benchmarks': List({'evidence': {'ceilings': {'max_files': Value('int64'), 'max_lines': Value('int64'), 'min_lines': Value('int64')}, 'code_lines': Value('int64'), 'command': Value('string'), 'counts_command': Value('string'), 'files_source': Value('int64'), 'files_tests': Value('int64'), 'files_total': Value('int64'), 'method': Value('string'), 'test_to_source_line_ratio': Value('float64'), 'total_lines': Value('int64'), 'a_licences': List(Value('string')), 'b_licences': List(Value('string')), 'default_for_unknown_is_C': Value('bool'), 'mismatches': {}, 'observed': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'only_class_A_may_relicense': Value('bool'), 'policy_probes': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'project_licence': {'LICENSE': Value('string'), '
...
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')}), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'method': {'aggregate_rule': Value('string'), 'excluded': Value('string'), 'reproduce': Value('string'), 'thresholds_note': Value('string')}, 'passed': Value('int64'), 'platform': Value('string'), 'python': Value('string'), 'root': Value('string'), 'sbom_written': Value('bool'), 'schema': Value('string'), 'total': Value('int64'), 'version': Value('string'), 'source': {'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'sha_verified_from': 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]
              method: struct<aggregate_rule: string, excluded: string, reproduce: string, thresholds_note: string>
                child 0, aggregate_rule: string
                child 1, excluded: string
                child 2, reproduce: string
                child 3, thresholds_note: string
              sbom_written: bool
              platform: string
              version: string
              failed: int64
              passed: int64
              source: struct<git: struct<head: string, url: string, branch: string, sha_verified_from: string>>
                child 0, git: struct<head: string, url: string, branch: string, sha_verified_from: string>
                    child 0, head: string
                    child 1, url: string
                    child 2, branch: string
                    child 3, sha_verified_from: string
              python: string
              schema: string
              total: int64
              benchmarks: list<item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: i (... 3044 chars omitted)
                child 0, item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code (... 3032 chars omitted)
                    child 0, evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code_lines: int64, co (... 2961 chars omitted)
                        child 0, ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>
                            child 0, max_files: int64
                            child 1, max_lines: int64
                            child 2, min_lines: int64
                        child 1, code_lines: int64
                        child 2, command: string
                        child 
              ...
              ail: string, evidence_path: string, present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                            child 5, reproducible_tests: struct<detail: string, evidence_path: string, present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                            child 6, rerunnable_verification: struct<detail: string, evidence_path: string, present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                            child 7, versioning: struct<detail: string, evidence_path: string, present: bool>
                                child 0, detail: string
                                child 1, evidence_path: string
                                child 2, present: bool
                        child 62, criteria_missing: list<item: null>
                            child 0, item: null
                        child 63, criteria_satisfied: int64
                        child 64, criteria_total: int64
                        child 65, framework_controls_verified: int64
                        child 66, ladder: string
                        child 67, observed_level: int64
                        child 68, source: string
                        child 69, trL9_claimed: bool
                        child 70, trL9_reason: string
                    child 1, id: string
                    child 2, ok: bool
                    child 3, status: string
                    child 4, title: string
              root: string
              all_passed: bool
              failed_ids: list<item: null>
                child 0, item: null
              to
              {'all_passed': Value('bool'), 'benchmarks': List({'evidence': {'ceilings': {'max_files': Value('int64'), 'max_lines': Value('int64'), 'min_lines': Value('int64')}, 'code_lines': Value('int64'), 'command': Value('string'), 'counts_command': Value('string'), 'files_source': Value('int64'), 'files_tests': Value('int64'), 'files_total': Value('int64'), 'method': Value('string'), 'test_to_source_line_ratio': Value('float64'), 'total_lines': Value('int64'), 'a_licences': List(Value('string')), 'b_licences': List(Value('string')), 'default_for_unknown_is_C': Value('bool'), 'mismatches': {}, 'observed': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'only_class_A_may_relicense': Value('bool'), 'policy_probes': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'project_licence': {'LICENSE': Value('string'), '
              ...
              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')}), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'method': {'aggregate_rule': Value('string'), 'excluded': Value('string'), 'reproduce': Value('string'), 'thresholds_note': Value('string')}, 'passed': Value('int64'), 'platform': Value('string'), 'python': Value('string'), 'root': Value('string'), 'sbom_written': Value('bool'), 'schema': Value('string'), 'total': Value('int64'), 'version': Value('string'), 'source': {'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'sha_verified_from': 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.

STARDOG

license offline-first audit category

Anticloud-hardened packaging of the upstream project STARDOG 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/stardog-union/stardog-examples · Upstream pin: f95303fe40a0016c655b2855c58fcdbf2bcc213b · Vendor: Anticloud FZ LLE

What This Project Does

Join the chat at https://gitter.im/Complexible/stardog-examples

Programming Stardog: Examples

This is a small collection of examples of working with Stardog via its APIs, as well as examples of how to use some of the extension points within Stardog.

How to build examples

First, you'll need a valid Stardog download.

You can use the included Gradle Wrapper script to build the examples in examples/api, example/foaf, examples/function.

To compile or run the examples, gradle will automatically download the dependencies from our public maven project:

$ ./gradlew compileJava

To run the examples, they require a valid $STARDOG_HOME; you can provide this via the parameter stardog.home (eg -PstardogHome=/my/stardog/home).

To run any of the examples, you can use the Gradle execute task. By default, this will run the ConnectionAPIExample program, but you can specify the fully-qualified class name of any of the other examples using the mainClass parameter.

$ ./gradlew execute -PmainClass=com.complexible.stardog.examples.api.ICVExample

.NET Examples

To compile the .NET examples, you will need to install .NET Core. Make sure that the dotnet tool is on your PATH

While you can build the sample with the latest version of the .NET Core SDK you will need .NET Core runtime installed to run the example. You can download it from here - you can verify which .NET Core runtimes you have installed by running:

dotnet --list-runtimes

Once you have installed .NET Core SDK and runtime,you can build the sample with the following command:

$ ./gradlew compileDotnet

To run the .NET examples you should have Stardog running locally and listening on port 5820 (you can change this by editing the connection string in ./examples/dotnet/TrinityConsoleSample/Program.cs. In addition, the example expects Stardog to have a database named 'music' loaded with the data from ./examples/dotnet/TrinityConsoleSample/Ontologies/music_schema.ttl and music.ttl.gz in a named graph called http://stardog.com/tutorial

You can run the sample with the following command (NOTE: the following command will automatically rebuild the sample):

$ ./gradlew runDotnet

The sample project will connect to Stardog and execute several queries using SPARQL and LINQ. It will print the results to the console.

For additional information see the DotNet Samples' README file - ./examples/dotnet/README.md

Generating Documentation

The Stardog documentation and its javadocs are a good place to start. But some examples in this project are annotated using Markdown; they can be processed by Docco.

If you don't have Docco installed, it's pretty easy to get started:

$ sudo npm install -g docco

Then, you can run it directly against any example:

$ docco -o docs main/src/com/complexible/stardog/api/ConnectionAPIExample.java

Or you can use the supplied gradle docs task in each build file that will run Docco against all annotated source files.

Service Loading

You'll notice that a number of examples have in their source a directory META-INF/services, these are the service registrations for each example.

Stardog uses the JDK ServiceLoader to load new services at runtime and make them available to the various parts of the system. The files in the services directory should be the fully qualified class name of the class/service, such as com.complexible.stardog.plan.filter.functions.Function, and the contents of the file should be a list of the fully qualified class names of the implementations of that service.

These need to be a part of your classpath, usually embedded in the jar file with the compiled source, in order for the ServiceLoader to make them up.

List of Examples

  1. Custom Analyzers
  2. Stardog API Examples
  3. Integrity Constraint Validation
  4. CSV example
  5. Docs Examples
  6. Database Archetype Extensibility
  7. DotNet Examples
  8. Function Extensibility
  9. Transaction Listener
  10. Cloud Foundry Example Application
  11. Machine Learning
  12. Anti-money laundering (AML) Example
  13. Transaction listener
  14. Http handler
  15. Stardog Free Examples

Quoted from the upstream README.md file in UPSTREAM_CLONE/. Project-specific facts detected in this directory:

  • Ecosystem: Java / Gradle (manifests: build.gradle; scanned in UPSTREAM_CLONE)
  • Top-level source layout: config/, demo-days/, examples/, gradle/, weblog/
  • Snapshot size: 314 files, 32948 lines of code (measured; see Benchmarks)
  • Primary languages: .ttl (35), .java (31), .sms (23), .csv (19), .md (19), .sparql (17)
  • Upstream commit pinned for this packaging: f95303fe40a0016c655b2855c58fcdbf2bcc213b

Installation

First, you'll need a valid Stardog download.

You can use the included Gradle Wrapper script to build the examples in examples/api, example/foaf, examples/function.

To compile or run the examples, gradle will automatically download the dependencies from our public maven project:

$ ./gradlew compileJava

To run the examples, they require a valid $STARDOG_HOME; you can provide this via the parameter stardog.home (eg -PstardogHome=/my/stardog/home).

To run any of the examples, you can use the Gradle execute task. By default, this will run the ConnectionAPIExample program, but you can specify the fully-qualified class name of any of the other examples using the mainClass parameter.

$ ./gradlew execute -PmainClass=com.complexible.stardog.examples.api.ICVExample

Section quoted from the upstream readme. 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 (Java / Gradle).

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

well as examples of how to use some of the extension points within Stardog.

Section quoted from the upstream readme.

Dependencies

Metric Value
Ecosystem Java / Gradle
Manifests detected build.gradle
Files in snapshot 314
Lines of code 32948
Dependency references 0
Upstream license Apache-2.0
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:

  • config

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 STARDOG 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: Apache-2.0 (evidence: LICENSE in the upstream snapshot).

License file excerpt:


                                 Apache License
                           Version 2.0, January 2004
                        http://www.apache.org/licenses/

   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION

   1. Definitions.

      "License" shall mean the terms and conditions for use, reproduction,
      and distribution as defined by Sections 1 through 9 of this document.

      "Licensor" shall mean the copyright owner or entity authorized by
      the copyright owner that is granting the License.

      "Legal Entity" shall mean the union of the acting entity and all
      other entities that control, are controlled by, or are under common
      control with that entity. For the purposes of this definition,
      "control" means (i) the power, direct or indirect, to cause the
      direction or management of such entity, whether by contract or

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 Apache-2.0 terms. See ANTICOMMONS_LICENSE.md in this directory for the overlay terms and contact.

SPDX: Apache-2.0 (upstream) + Anticommons 0.1.0 (overlay, dual).

Upstream

  • Project: STARDOG (category: PHILOSOPHY SEMANTICS)
  • Upstream URL: https://github.com/stardog-union/stardog-examples
  • Pinned commit (SHA): f95303fe40a0016c655b2855c58fcdbf2bcc213b
  • Branch: develop
  • Pin provenance: GitHub API commits/develop. 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 a2ae956bb12ca801ff1dd453421c0a3f1b692b889b78d6ff36398f6de1a2a231.

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.
Downloads last month
49
Total file size:
42.3 kB