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Datasets:
omkar6699
/
openworlds-ad-trajectories

Tasks:
Text Generation
Tags:
cybersecurity
pentesting
active-directory
synthetic-data
openworlds
License:
Dataset card Files
xet
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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
id: string
messages: list<item: struct<role: string, content: string>>
  child 0, item: struct<role: string, content: string>
      child 0, role: string
      child 1, content: string
metadata: struct<domain: string, starting_user: string, strategies: list<item: string>, total_steps: int64, su (... 12 chars omitted)
  child 0, domain: string
  child 1, starting_user: string
  child 2, strategies: list<item: string>
      child 0, item: string
  child 3, total_steps: int64
  child 4, success: bool
to
{'messages': List({'role': Value('string'), 'content': Value('string')}), 'id': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                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 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2543, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2060, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2092, in _iter_arrow
                  pa_table = cast_table_to_features(pa_table, self.features)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2192, in cast_table_to_features
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              id: string
              messages: list<item: struct<role: string, content: string>>
                child 0, item: struct<role: string, content: string>
                    child 0, role: string
                    child 1, content: string
              metadata: struct<domain: string, starting_user: string, strategies: list<item: string>, total_steps: int64, su (... 12 chars omitted)
                child 0, domain: string
                child 1, starting_user: string
                child 2, strategies: list<item: string>
                    child 0, item: string
                child 3, total_steps: int64
                child 4, success: bool
              to
              {'messages': List({'role': Value('string'), 'content': Value('string')}), 'id': Value('string')}
              because column names don't match

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OpenWorlds AD Penetration Testing Trajectories

Synthetic training trajectories for fine-tuning AI agents on Active Directory penetration testing.

Dataset Description

Each trajectory is a complete attack path from initial access to Domain Admin, formatted as multi-turn chat conversations with:

  • System prompt with target domain context
  • reasoning traces (expert thought process)
  • Tool calls (nmap, ldapsearch, GetUserSPNs, hashcat, secretsdump, etc.)
  • Tool outputs (realistic simulated responses)
  • Failure recovery (typos, wrong creds, with correction steps)

Attack Strategies Covered

Strategy Description
Kerberoasting Service accounts with SPNs -> crack TGS tickets
AS-REP Roasting Users without pre-auth -> crack AS-REP hashes
ACL Abuse Chains GenericAll -> WriteDACL -> ForceChangePassword -> DCSync
AD CS Abuse (ESC1) Vulnerable cert templates -> impersonate Domain Admin
Credential Pivoting Passwords in shares, GPPs, config files

Usage 

from datasets import load_dataset
ds = load_dataset("omkar6699/openworlds-ad-trajectories")

Generation

Generated using OpenWorlds:

openworlds manifest generate --hosts 10 --users 25 --seed 42
openworlds trajectory generate --failure-rate 0.15

License

Apache 2.0

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Models trained or fine-tuned on omkar6699/openworlds-ad-trajectories