---
license: cc-by-4.0
task_categories:
  - tabular-classification
  - other
tags:
  - host-intrusion-detection
  - tetragon
  - ebpf
  - sequence-modeling
  - att-and-ck
  - anomaly-detection
size_categories:
  - 10M<n<100M
language: []
pretty_name: "v0.2 Tetragon-native HIDS corpus (22 technique IDs)"
---

## Dataset summary

- **Source:** Tetragon 1.6.1 eBPF telemetry on a single LXC container,
  6-day collection window 2026-04-14 → 2026-04-20.
- **Population:** all process / file / network / credential / memory events
  attributable to the target container's PID-namespace inum across the
  collection window (parser filters host-namespace events at parse time).
- **Splits:** chronological — train (2026-04-14T01:41Z → 2026-04-19T22:09Z) /
  test (2026-04-19T21:46Z → 2026-04-20T02:01Z). All ART attack intervals
  fall in the test split; train is benign-only by construction.
- **Format:** Parquet shards under `data/`, suitable for the Hugging Face
  `datasets` library streaming loader. Labels are a separate `labels.csv`.
- **License:** CC BY 4.0.

---

## Supported tasks

- **Host-telemetry anomaly detection.** Per-event or per-window scoring
  against the time-window labels in `labels.csv`.
- **Sequence anomaly modeling.** Autoregressive next-event prediction (NLL)
  or masked-event modeling (MEM, including field-aware MEM-FA) over the
  integer-coded feature columns.
- **Event-stream classification baselines.** N-gram, IsolationForest,
  XGBoost, etc. operate directly on the categorical / hash columns.

The corpus is **not** intended for: attack-payload synthesis, ground-truth
event-level labels (only intervals are labeled), or production deployment
without recalibration to the operator's own host distribution.

---

## Dataset structure

### Splits

| Split | Rows       | Time span (UTC)†                                  | Attack events | Attack rate |
|-------|------------|---------------------------------------------------|---------------|-------------|
| train | 16,951,950 | 2026-04-14 01:41:13 → 2026-04-19 22:09:18         | 0             | 0.0 %       |
| test  |  2,349,965 | 2026-04-19 21:46:27 → 2026-04-20 02:01:27         | 705,852       | 30.0 %      |

**† Pre-window event timestamps.** ≈295 events (267 train + 28 test, 0.0015 %
of the corpus) carry `event_time` values that predate the stated collection
window. All have `f_is_procfs_walk = 1`: parser-synthesized `process_exec`
records for daemons (`systemd`, `bash`, `dbus-daemon`, `polkitd`, `cron`,
`sshd`, etc.) that were already running when Tetragon collection started,
using the daemon's original `process_start_time` as the event timestamp.
They preserve lineage roots for downstream events. Filter
`WHERE f_is_procfs_walk = 0` to exclude them from time-window analysis.

### Schema evolution (v0.2.1)

The release artifact is the **encoded** parquet (63 columns: 39 model-input
columns + 7 hash columns + identifier and side-string columns). Compared to
v0.2.0 the encoded schema gained four 3a′ promoted categoricals
(`f_path_category`, `f_dst_ip_category`, `f_dst_port_category`,
`f_object_category`) and lost two constant-zero booleans (`f_in_init_tree`,
`f_args_truncated`); two hash columns were right-sized
(`f_proc_name_hash` 1024 → 2048, `f_proc_cwd_hash` 256 → 4096 with depth
2 → 4 path components hashed). The full integer-code → label mapping is in
`reproduction/feature_definitions.json` (schema version 1.1).

The release pipeline is three-stage:

| Stage | Source field                                  | Stage column                              | Transformation |
|-------|-----------------------------------------------|-------------------------------------------|----------------|
| Raw Tetragon JSON | `process_exec` / `process_exit` / `process_kprobe` envelope    | `event_type`                              | passthrough → vocab `f_event_type` |
| → Parser (126-col raw, withheld) | `process.binary`                            | `proc_binary` (full path)                 | derive basename → `proc_binary_basename` (released, aliased) + hash `f_proc_name_hash` |
|                                 | `process.cwd`                               | `proc_cwd` (full path)                    | normalize → `proc_cwd_normalized` (path-rewritten at release) + hash `f_proc_cwd_hash` |
|                                 | `process.uid`                               | `proc_uid` (uint32)                       | bucket → `f_proc_uid_bucket` (uint8) — raw uid not released |
|                                 | `process.arguments`                         | `proc_arguments`                          | length-bucket → `f_args_length_bucket` (uint8); raw args not released |
|                                 | `process_kprobe.args[].sock.daddr`          | `kp_sock_daddr`                           | category bucket → `dst_ip_category` (string) — raw IP not released |
| → Behavior builder (encoded, released) | (event_type, kprobe_function_name)          | `f_action_family` (uint8, 15 codes)       | derived; see `feature_definitions.json` |
|                                                | (parent_basename, proc_basename) pair        | `f_parent_child_pair_hash` (uint16, 1024 buckets) | hash |
|                                                | proc_exec_id walk                            | `f_lineage_depth`, `f_root_ancestor_basename_hash`, `f_process_tree_id_hash` | derived |

The **126-column raw parser output is withheld** from the public release.
All raw paths, raw arguments, raw IPs, raw uids, hostnames, and PID-namespace
inums are dropped at this stage; see "Personal and sensitive information"
below for the per-column decisions.

### Feature column inventory (encoded parquet)

Full integer-code → label mapping for every categorical column lives in
`reproduction/feature_definitions.json`. High-level summary:

- **22 integer-coded categorical columns** — 18 from v0.2.0 plus the four
  3a′ promoted categoricals (`f_path_category` 11-way, `f_dst_ip_category`
  6-way, `f_dst_port_category` 7-way, `f_object_category` 8-way).
- **4 string-coded categorical columns** (`path_category`, `object_category`,
  `dst_ip_category`, `dst_port_category`) — provenance side columns,
  identical semantics to their `f_*` integer counterparts.
- **7 hash columns** with declared bucket capacities (2048 / 1024 / 4096 /
  256 / 1024 / 1024 / 4096 — see *Hash-bucket utilization* below).
- **6 boolean flag columns** (e.g. `f_is_procfs_walk`, `f_uid_eq_parent`,
  `f_kp_commit_creds_uid_change`).
- **5 numeric columns** (`delta_t_prev_ns`, `process_age_ns`, mmap/mprotect
  prot bitmasks, fd integer).
- **3 bucketed log-time columns** (`f_delta_t_log_bucket`,
  `f_process_age_log_bucket`, `f_lineage_depth`).
- **3 identifier columns** (`event_time`, `proc_exec_id`, `proc_pid`).
- **7 release-eligible side-string columns** (basenames, normalized cwd,
  parent-child pair, token, process_tree_root_exec_id).

### Class distributions (train split)

**`f_event_type`** (4-way; OOV not observed):

| Code | Label             | Count       | %     |
|------|-------------------|-------------|-------|
| 2    | process_kprobe    | 16,413,759  | 96.83 |
| 1    | process_exit      |    288,716  |  1.70 |
| 0    | process_exec      |    249,475  |  1.47 |

**`f_action_family`** (15-way; top 10 shown; full table in
`feature_definitions.json`):

| Code | Label              | Count       |
|------|--------------------|-------------|
| 6    | FILE_OPEN          | 14,852,286  |
| 12   | MEM_MAP            |  1,168,402  |
| 1    | PROC_EXIT          |    288,716  |
| 9    | PRIV_CHANGE        |    257,709  |
| 0    | PROC_EXEC          |    249,475  |
| 7    | FILE_DELETE        |     44,818  |
| 5    | NET_SEND           |     23,672  |
| 13   | MEM_PROTECT        |     19,059  |
| 3    | NET_CLOSE          |     18,451  |
| 2    | NET_CONNECT        |     16,359  |

### ATT&CK label coverage

61 labeled time intervals span 21 ATT&CK techniques + 1 supply-chain capstone
chain across 8 tactics. **All attack-positive intervals are in the test
split.** Per-technique event counts (test split, top 10 by event volume):

| ID          | Technique                                                  | Test events |
|-------------|------------------------------------------------------------|-------------|
| T1059.004   | Unix Shell                                                 | 175,797     |
| T1083       | File and Directory Discovery                               | 154,581     |
| T1552.001   | Credentials In Files                                       |  97,493     |
| T1543.002   | Systemd Service                                            |  47,901     |
| CHAIN.CAP01 | Capstone Chain v0.1 (Supply-Chain Narrative)               |  34,130     |
| T1548.003   | Sudo and Sudo Caching                                      |  24,229     |
| T1059.006   | Python                                                     |  22,675     |
| T1562.001   | Disable or Modify Tools                                    |  18,610     |
| T1195.002   | Compromise Software Supply Chain                           |  15,703     |
| T1548.001   | Setuid and Setgid                                          |  12,461     |

Full per-technique table is reproducible from `notebooks/v0-2_dataset_audit.ipynb`
(cell 63).

### Hash-bucket utilization (train split, post-3a′ caps)

| Column                          | Capacity | Buckets used | Saturation |
|---------------------------------|----------|--------------|------------|
| f_proc_name_hash                | 2048     | 269          | 13.1 %     |
| f_parent_proc_hash              | 1024     | 121          | 11.8 %     |
| f_proc_cwd_hash                 | 4096     |  65          |  1.6 %     |
| f_lineage_bag_hash              |  256     |  98          | 38.3 %     |
| f_parent_child_pair_hash        | 1024     | 490          | 47.9 %     |
| f_root_ancestor_basename_hash   | 1024     |   5          |  0.5 %     |
| f_process_tree_id_hash          | 4096     |   7          |  0.2 %     |

Low saturation reflects the single-host single-developer baseline (a small
real basename / cwd / lineage population). The 3a′ capacity bumps on
`f_proc_name_hash` and `f_proc_cwd_hash` were sized for plausible multi-host
saturation rather than this corpus's observed counts; the values are
documented here so re-trainers can resize the embedding tables.

---

## Dataset creation

### Curation rationale

This dataset was assembled to support the v0.2 milestone of an academic
project investigating Mamba-based anomaly detection on host telemetry. The
v0.1 predecessor produced an *inverted* AUROC (~0.35) on a similar but
parser-buggy corpus; v0.2 was rebuilt with a Tetragon-native parser,
sentinel-window exclusion at parse time, and a two-stage
parser → behavior-builder design that preserves a raw normalized parquet
internally for iteration. The **v0.2.1 release** further re-parsed the same
collection on 2026-04-29 with five correctness fixes:

- Procfs-walk synthetic execs are now **tagged, not dropped** (1,346 events
  recovered corpus-wide; lineage gaps for daemons running before agent start
  closed).
- `delta_t_prev_ns` is keyed **per-process** rather than globally, removing
  44,947 train + 1,643 test negative residuals.
- Test-split lineage walking now seeds from the train parquet first,
  resolving 39 % of previously-missing parents (test
  `lineage_missing_parent`: 5.25 % → 2.88 %).
- Parser parallelized across files via `multiprocessing.Pool`, with DuckDB
  `ORDER BY event_time` for chronological output.
- Mamba NLL scorer's front-pad alignment fix: `nll_padded[i]` is now event
  *i*'s surprise (was *i+1*'s in v0.2.0).

### Source data

- **Sensor:** Tetragon 1.6.1 (Cilium eBPF) running on a Linux host.
- **Workload:** a single LXC container hosting a developer's daily workspace
  (Node, Python, VSCode, npm). Background services inside the container
  (systemd-resolved, dbus, polkitd, etc.) contribute system noise.
- **Tracing policies:** 7 YAML policies covering file, network, memory,
  privilege, process-injection, and file-attribute kprobes (bundled in
  `reproduction/tetragon-configs/`).
- **Attribution:** the parser pins on PID-namespace inum, which uniquely
  identifies the target container across an inum rotation that occurred
  during the collection window. Host-namespace events are dropped at parse
  time.

### Annotations

Time-window labels are provided in `labels.csv` (61 rows; 22 distinct
technique IDs incl. one capstone chain; 8 tactics). Labels were generated
by an Atomic Red Team campaign run inside the same container during the
test window, with start/end timestamps captured per-trial. The campaign
manifest is bundled at `reproduction/agentic-art-campaign/`.

### Personal and sensitive information

**component-first anonymization** with deep aliasing across all PII-bearing string
columns. Summary:

- **126-column raw parquet withheld.** All raw paths, raw arguments, raw
  IPs, raw uids, hostnames, and PID-namespace inums are dropped at the
  parser stage. The released parquet is the 63-column encoded form.
- **Basename aliasing.** A single alias map covers `proc_binary_basename`,
  `parent_binary_basename`, and `root_ancestor_basename`. Distro-standard
  binaries and dev-tooling that anchor the "standardized agentic-research
  workstation" baseline (`bash`, `node`, `python3.12`, `claude`, `gh`,
  `npm`, `code`, `git`, etc.) pass through verbatim. Custom binaries
  (ART trial scripts, build artifacts) become `custom_tool_NNN` (lex-sorted).
  VSCode commit-hash binaries (`code-<40hex>`) collapse to a single
  `vscode_server_bin` alias. The full original → alias map is shipped at
  `reproduction/alias_map.json`.
- **Composite re-composition.** `parent_child_pair` and `token` are
  regenerated from the aliased atomic columns via the canonical
  `format_token`, so the original (un-aliased) basename never re-enters
  these fields.
- **Path rewriting.** `proc_cwd_normalized` is rewritten by ordered rules:
  `/home/<user>` → `/home/_user_`, `/Users/<user>` → `/Users/_user_`,
  `/mnt/projects/<X>` → `/workspace/_project_`, `/projects/<X>` →
  `/workspace/_project_`, residual `rypow_` → `custom_`.
- **Exec-id pseudonymization.** `proc_exec_id` and
  `process_tree_root_exec_id` are rewritten as
  `exec_<32hex>` via salted HMAC-SHA256 (16-byte digest, hex-encoded).
  Equality joins are preserved (lineage walks still work); the original
  base64-encoded `host:ts:pid` payload is erased.
- **Defensive global string sweep.** A final substring pass over every
  string column substitutes `rypow → research_user`,
  `prox1 → sandbox_host`, `dendroaspis → agent_platform_v02`,
  `ryan_admin → privileged_user` as a safety net.
- **Post-write assertions.** A regex sweep over the released shards
  (notebook §22-24) confirms zero matches on raw or base64-decoded values
  for any of: `prox1`, `rypow`, `ryan_admin`, `/home/rypow/`,
  `/projects/ml_final_project`, `/mnt/projects/`, `dendroaspis`,
  `/datasets/`, MAC-address pattern. `proc_exec_id` and
  `process_tree_root_exec_id` are format-checked against
  `^exec_[0-9a-f]{32}$`. Every basename in the three basename columns is
  asserted to be in the alias-map closure.

---

## Considerations for using the data

### Sources of bias

- **Single host, single developer.** All baseline (benign) telemetry comes
  from one Linux container running one developer's daily workflow over six
  days. Tool habits (VSCode, npm, git, claude-code) appear at high
  frequency; absent activities (CI/CD pipelines, multi-tenant traffic, GPU
  jobs) are simply not represented.
- **Container-internal UIDs.** Tetragon 1.6.1 emits container-internal UIDs;
  the encoder buckets uids into 5 classes (ROOT / RESEARCH_USER /
  SYSTEM_LOW / DAEMON_HIGH / OTHER) rather than treating them as a
  continuous identifier. Researchers reusing these buckets on multi-host
  data should re-bucket.
- **Time skew.** Train spans 5 d 20 h, test spans only 4 h 15 m. The test
  window concentrates 30 % attack-event mass, which is unrealistically dense
  for production traffic; downstream metrics (AUROC, AP) on this corpus
  reflect the campaign's deliberate density.
- **Hash-bucket sparsity.** Hash columns are sized for plausible multi-host
  saturation; on this single-host corpus most are < 50 % utilized (see
  hash-bucket table above).
- **Aliased basename narrative.** The v0.2.1 anonymizer collapses a long
  tail of one-off custom binaries into `custom_tool_NNN` slots and folds
  per-build VSCode commit-hash binaries into `vscode_server_bin`. The
  resulting parquet looks like a "standardized agentic-research workstation"
  baseline more than the specific developer's machine; the true diversity
  of custom-script names was higher than what survives in the released
  string columns.

### Social impact

This is a defensive-research dataset. It enables researchers to develop and
benchmark host-anomaly-detection models without operating live attack
infrastructure. The bundled ATT&CK technique inventory is **not** an
attack tutorial — payload generation requires a separate Atomic Red Team
installation and is out of scope.

### Known limitations

- **No ground-truth event-level labels.** Labels are time-window only; some
  benign system activity (e.g. background daemons running during an ART
  technique window) is *labeled-attack* by association.
- **Train has zero attack events.** All ART intervals fall in test by
  construction. Unsupervised / self-supervised methods are the natural fit;
  fully supervised classifiers would need to engineer their own
  train-time positives.
- **Single Tetragon version.** Format quirks of Tetragon 1.6.1 (e.g.
  KPROBE_ACTION enum coverage, ns-PID inum semantics) are baked in. Older
  / newer Tetragon emits slightly different envelopes; the parser pin in
  `reproduction/PARSER_VERSION` documents the exact reference build.
- **Linux only.** Tetragon is Linux-only; this corpus has no Windows or
  macOS analogue.

### Intended use + dual-use disclaimer

**Intended use.** This dataset supports:

- training and evaluating sequence / anomaly models on host telemetry,
- benchmarking baselines (n-gram, XGBoost, IsolationForest, LSTM, Mamba,
  Transformer) on a fixed split,
- studying ATT&CK-technique-specific detectability,
- research on attack representations, lineage features, and event encoders.

**Not intended use.** The attack telemetry is real ATT&CK technique
execution but generated in an isolated lab LXC container; the corpus is
**not** an attack template, **not** a payload library, and **not** a
substitute for production EDR data. Operators who reuse the bundled
tracing policies + parser to collect their own corpus are responsible for
their own sandboxing.

---

## Additional information

### License

CC BY 4.0 — see `LICENSE` in this repo. Code under
`reproduction/scripts/` (in the project repository) is MIT-licensed.

### Citation

```bibtex
@dataset{dendroaspis_v0_2_2026,
  title   = {v0.2 Tetragon-native HIDS corpus with 21 ATT\&CK techniques},
  author  = {Powers, Ryan William},
  year    = {2026},
  version = {0.2.1},
  doi     = {<TBD-on-publish>},
  url     = {<TBD-on-publish>}
}
```

### Contact

GitHub: [@ryypow](https://github.com/ryypow). Issues / corrections
preferred via the project repository.

repos: https://github.com/ryypow/dendroaspis