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transilienceai/communitytools104 installs

ti-ingest

Threat-intel signal ingest — converts a CVE + affected-asset + claim payload into a queued engagement-scope row for the validation pipeline.

How do I install this agent skill?

npx skills add https://github.com/transilienceai/communitytools --skill ti-ingest
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    The skill facilitates threat intelligence ingestion, converting CVE signals into a queue for validation. While the core functionality is safe and uses trusted data sources like the NIST National Vulnerability Database, it possesses an indirect prompt injection surface. Specifically, it ingests unvalidated free-text claims from external signal files which are then passed to downstream tasks, potentially allowing malicious instructions to persist in the processing pipeline.

  • Socketpass

    No alerts

  • Snykwarn

    Risk: MEDIUM · 1 issue

What does this agent skill do?

Threat-Intel Signal Ingest

Convert a threat-intel signal into a queued engagement-scope row that the Exploitability Validation Run (cloud-agent task #3) consumes.

Trigger

Two modes:

  • Prompt-invoked: an analyst runs the skill against a signal.json they have on hand.
  • Scheduled poll: the cloud-agent runtime polls {OUTPUT_DIR}/inbox/ on a cron (default every 15 minutes) and processes any new signal files it finds.

Workflow

  1. Read the payload — tools/ti-ingest.py --in <path-or-stdin>.
  2. Validate schema — required keys: signal_id, cve (one or more), assets (one or more), claim. Optional: confidence, source, references.
  3. Enrich with NVD — for every CVE in the payload, run tools/nvd-lookup.py <CVE> and attach {score, severity, cwe} to the row.
  4. De-dup — skip rows whose (asset, cve) pair already exists in queue/scope-*.json. Re-queue only if the prior row's status is REJECTED AND the TI signal carries a higher confidence than the last attempt.
  5. Write queue row — one JSON file per (asset, cve) pair at queue/scope-{ts}-{asset_id}-{cve}.json. The Validation Run task picks these up.

Output

{OUTPUT_DIR}/
  inbox/
    signal-{ts}.json        # raw payload, kept for audit
  queue/
    scope-{ts}-{asset}-{cve}.json

Per scope row:

{
  "scope_id": "scope-20260513-asset42-CVE-2024-12345",
  "signal_id": "ti-2026-0042",
  "asset": {"id": "asset42", "url": "https://app.example.com", "tier": "revenue"},
  "cve": "CVE-2024-12345",
  "nvd": {"score": 9.8, "severity": "CRITICAL", "cwe": "CWE-79"},
  "claim": "Reflected XSS via search parameter",
  "confidence": "high",
  "source": "vendor-advisory",
  "references": ["https://..."],
  "queued_at": "2026-05-13T10:00:00Z",
  "status": "queued"
}

Rules

  1. Idempotent. Re-running on the same payload must not produce duplicate queue rows.
  2. No execution. Ingest never runs PoCs. It only queues scope for downstream tasks.
  3. Audit trail. Raw payload is always copied to inbox/ before any transformation.
  4. NVD failures are non-blocking. If nvd-lookup errors, write the row with nvd: null and nvd_error: "..."; do not drop the signal.
  5. Asset must be in inventory. Cross-check asset.id against artifacts/org-surface.json (from Org Recon Refresh task). Unknown assets get a row but flagged unknown_asset: true so the validator skips them.

References

  • reference/ingest-schema.md — full input/output JSON schemas.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/transilienceai/communitytools/ti-ingest">View ti-ingest on skillZs</a>