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Datasets:
hookprobe
/
edge-ids-threats

Tasks:
Tabular Classification
Time Series Forecasting
Modalities:
Tabular
Text
Formats:
parquet
Languages:
English
Size:
100K - 1M
Tags:
cybersecurity
intrusion-detection
network-security
edge-computing
threat-intelligence
Libraries:
Datasets
Dask
Polars
License:
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edge-ids-threats / README.md
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hookprobe
Release 2026-05-01
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metadata 
license: cc-by-4.0
task_categories:
  - tabular-classification
  - time-series-forecasting
language:
  - en
tags:
  - cybersecurity
  - intrusion-detection
  - network-security
  - edge-computing
  - threat-intelligence
pretty_name: HookProbe Edge IDS Threat Telemetry
size_categories:
  - 100K<n<1M
configs:
  - config_name: verdicts
    data_files:
      - split: all
        path: data/*.parquet
  - config_name: aggregated
    data_files:
      - split: daily
        path: aggregated/daily_country_asn.parquet

HookProbe Edge IDS Threat Telemetry

Real-world, anonymised threat verdicts from the HookProbe production edge intrusion-detection system. Unlike synthetic lab datasets (CICIDS2017, UNSW-NB15, Kitsune) this is what an actual edge sensor mesh observes on the open internet, labelled by the SENTINEL ensemble (isolation forest + calibrated naive-Bayes) that ships with HookProbe.

  • Sensor: Raspberry Pi edge node + NAPSE AI-native flow classifier
  • Enrichment: RDAP country + ASN lookups
  • Labels: malicious / suspicious / benign with anomaly score 0–1
  • Actions: block / throttle / cognitive_block / cognitive_throttle / escalate / alert / monitor / cognitive_none / none — emitted by the CNO cognitive-defense layer. cognitive_* variants indicate the decision came from the CNO synaptic controller rather than the static HYDRA rule path.
  • License: CC-BY-4.0 — free for commercial or academic use with attribution
  • Canonical URL: https://hookprobe.com/threats/

Schema

verdicts (primary)

column type description
timestamp_hour timestamp[s] UTC, truncated to the hour
src_ip_hash string(16) SHA-256(salt ∥ src_ip)[:16]. Pseudonymous.
country string ISO-3166-1 alpha-2
asn uint32 Autonomous-system number (0 if unknown)
asn_name string ASN organisation name
anomaly_score float32 Ensemble output, 0.0 benign – 1.0 malicious
verdict enum malicious | suspicious | benign
action_taken enum see Actions above — 9 possible values

aggregated (derived)

column type description
date date32 UTC day
country, asn, asn_name ... same semantics as primary
threat_count uint32 total verdicts for that country/asn/day
malicious, suspicious, benign uint32 per-class counts
avg_anomaly_score float32 mean ensemble score

Privacy model

  • IPs are hashed with a project salt that is not published. The hash is deterministic across releases so longitudinal analysis of attacker behaviour is preserved, but the mapping is one-way.
  • Timestamps are truncated to the hour to prevent correlation against third-party logs with second-precision timestamps.
  • No payload data is exposed — only verdicts and enrichment.

Data caveats

  • The SENTINEL calibration window (2026-02-22 → 2026-03-09) is excluded by default. During that period the ensemble produced a ~98% false-positive rate, which was fixed in the 9-point SENTINEL release on 2026-03-09. Training on that window would mis-lead downstream models.
  • Because the sensor is a single edge node, geographic and ASN distributions reflect what targets that specific deployment — not a global baseline. Treat skew accordingly.

Citation 

@dataset{hookprobe_edge_ids_threats_2026,
  author  = { {HookProbe Security Research} },
  title   = { {HookProbe Edge IDS Threat Telemetry} },
  year    = { 2026 },
  url     = { https://huggingface.co/datasets/hookprobe/edge-ids-threats },
  note    = { 548,428 verdicts; temporal coverage 2026-04 → 2026-04 },
}

Example usage 

from datasets import load_dataset

# Full verdict stream — ML-grade labelled data
ds = load_dataset("hookprobe/edge-ids-threats", name="verdicts", split="all")
print(ds[0])

# Pre-aggregated daily country/ASN counts — analyst-grade
agg = load_dataset("hookprobe/edge-ids-threats", name="aggregated", split="daily")

Updates

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