Publish AriaSOC synthetic laboratory cases
Browse files- README.md +56 -0
- data/alerts.csv +0 -0
- data/cases.csv +21 -0
- data/evaluation.json +13 -0
- data/sample_preview.json +26 -0
- data/splits.json +5 -0
README.md
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---
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license: cc-by-4.0
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pretty_name: AriaSOC laboratory cases
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task_categories:
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- text-classification
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- other
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tags:
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- cybersecurity
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- soc
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- alert-triage
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- siem
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- synthetic
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language:
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- en
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- fa
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size_categories:
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- n<1K
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---
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# AriaSOC laboratory cases
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Synthetic SIEM alerts and case labels used by [AriaSOC](https://huggingface.co/spaces/alirezaaminzadeh/aria-soc).
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**This is generated data** (seed `24`). It is for reproducible demos and tests, not a customer extract. Addresses are documentation-range or RFC1918 laboratory values. Tokens and mailboxes are fake and redacted in the demo.
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## Files
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| File | Grain | Notes |
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|---|---|---|
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| `data/alerts.csv` | one alert | Required SOC fields plus source, title, optional ATT&CK |
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| `data/cases.csv` | 20 generator scenarios | Incident id, importance, gold label |
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| `data/splits.json` | time cut | Train = earlier 70% of timestamps |
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| `data/evaluation.json` | one run | Recorded baseline vs correlation metrics |
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| `data/sample_preview.json` | UI snapshot | Precomputed KPI HTML; labeled as a sample |
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## Schema
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`alerts.csv`: `event_id, timestamp, asset_id, rule_id, severity, user_id, source, title, message, src_ip, dest_host, process, technique, case_id, incident_id, importance, gold_label`
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Required for the demo parser: `event_id, timestamp, asset_id, rule_id, severity, user_id`. Empty `asset_id` or `user_id` is valid and means **unknown**, not a pass.
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Sources: `identity`, `edr`, `network`.
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Importance: `important`, `benign`, `noise`, `insufficient`.
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## Split
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Do **not** shuffle rows of the same incident into train and test. Use `timestamp <= train_until` from `splits.json` as history. The optional LightGBM ranker is fit only on that earlier window.
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## Generator
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`projects/aria-soc/src/generator.py` in the Space repo, seed `24`. Twenty scenarios include a finance compromise chain, look-alike benign activity, missing-schema events, and a two-day-old recon burst that sits outside the default correlation window.
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## License
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CC-BY-4.0. Keep the synthetic-data label if you reuse the tables.
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data/alerts.csv
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The diff for this file is too large to render.
See raw diff
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data/cases.csv
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case_id,incident_id,importance,gold_label,title,sources
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C01-credential-spray,I-FIN-001,important,true_positive,Credential spray then success,identity
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C02-ransom-like,I-FIN-001,important,true_positive,Mass rename and backup deletion,edr
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C03-lateral-smb,I-FIN-001,important,true_positive,SMB lateral from finance host,"network,edr"
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C04-impossible-travel,I-HR-004,important,true_positive,Two countries in 40 minutes,identity
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C05-beacon,I-DEV-005,important,true_positive,Periodic outbound beacon,network
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C06-encoded-ps,I-JUMP-006,important,true_positive,Encoded PowerShell on jump host,edr
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C07-phish-oauth,I-HR-007,important,true_positive,Mail click then OAuth grant,"identity,edr"
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C08-dns-nx,I-DEV-005,important,true_positive,High NXDOMAIN rate,network
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C09-mfa-disable,I-ADM-009,important,true_positive,Privileged MFA disabled,identity
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C10-svc-interactive,I-BAK-010,important,true_positive,Backup service account interactive logon,identity
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C11-vuln-scan,I-BEN-011,benign,benign,Approved vulnerability scan,network
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C12-av-update-storm,I-NOI-012,noise,noise,Antivirus definition storm,edr
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C13-travel-vpn,I-BEN-013,benign,benign,Travel plus corporate VPN,identity
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C14-helpdesk-rdp,I-BEN-014,benign,benign,Scheduled helpdesk RDP,network
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C15-software-deploy,I-BEN-015,benign,benign,Change-window process storm,edr
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C16-broken-schema,I-UNK-016,insufficient,insufficient,Events missing required context,"identity,edr"
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C17-orphan-low,I-UNK-017,insufficient,insufficient,Single low-severity orphan,network
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C18-shared-ip-unrelated,I-MIX-018,benign,benign,"Shared NAT IP, unrelated users",network
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C19-dup-c02,I-FIN-001,important,true_positive,Near-duplicate ransom alerts that must survive,edr
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C20-early-recon,I-FIN-001,important,true_positive,Recon two days earlier; outside default window,network
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data/evaluation.json
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{
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"has_ground_truth": true,
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"input_events": 643,
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"cluster_count": 92,
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"baseline_queue_size": 48,
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"noise_reduction": 0.8569,
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"unwitnessed_claim_rate": 0.0,
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"precision_at_k": 0.875,
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"pairwise_precision": 0.8578,
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"important_pairwise_recall": 0.8034,
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"important_incident_recall": 1.0,
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"top_k": 8
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}
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data/sample_preview.json
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{
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"run_id": "aria-soc-9d0709194d",
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"status": "ok",
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"status_label": "Live analysis finished",
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"metrics": {
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"has_ground_truth": true,
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"input_events": 643,
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"cluster_count": 92,
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"baseline_queue_size": 48,
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"noise_reduction": 0.8569,
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"unwitnessed_claim_rate": 0.0,
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"precision_at_k": 0.875,
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"pairwise_precision": 0.8578,
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"important_pairwise_recall": 0.8034,
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"important_incident_recall": 1.0,
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"top_k": 8
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},
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"baseline_metrics": {
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"queue_size": 48,
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"noise_reduction": 0.9253,
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"precision_at_k": 1.0,
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"important_incident_recall": 0.8571
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},
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"kpi_html": "\n<div class=\"kpi-grid\">\n <article class=\"kpi-card\"><p class=\"kpi-label\">Needs review</p><p class=\"kpi-value\">32</p><p class=\"kpi-sub\">Cases in the analyst queue</p></article>\n <article class=\"kpi-card\"><p class=\"kpi-label\">Events kept</p><p class=\"kpi-value\">643</p><p class=\"kpi-sub\">Dropped 0 unusable rows</p></article>\n <article class=\"kpi-card\"><p class=\"kpi-label\">Incomplete</p><p class=\"kpi-value\">53</p><p class=\"kpi-sub\">Missing user, asset, or second source</p></article>\n <article class=\"kpi-card\"><p class=\"kpi-label\">Queue compression</p><p class=\"kpi-value\">86%</p><p class=\"kpi-sub\">Always read with important-case recall</p></article>\n <article class=\"kpi-card\"><p class=\"kpi-label\">Runtime</p><p class=\"kpi-value\">7.2s</p><p class=\"kpi-sub\">Warm CPU target < 30s</p></article>\n</div>\n",
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"precomputed": true
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}
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data/splits.json
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{
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"seed": 24,
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"train_until": "2026-09-18T08:23:00",
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"note": "Time split by alert timestamp. Do not shuffle rows of the same incident."
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}
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