Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add 26zl/cybersec-toolkit --skill building-threat-intelligence-feed-integrationgit clone --depth 1 https://github.com/26zl/cybersec-toolkitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/26zl/cybersec-toolkit/building-threat-intelligence-feed-integration)<a href="https://agentmods.dev/skills/26zl/cybersec-toolkit/building-threat-intelligence-feed-integration"><img src="https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/building-threat-intelligence-feed-integration/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/26zl/cybersec-toolkit/building-threat-intelligence-feed-integration"><img src="https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/building-threat-intelligence-feed-integration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00074 | $0.02973 |
| Opus 5 | $0.00037 | $0.01486 |
| Sonnet 5 | $0.00015 | $0.00595 |
| Haiku 4.5 | $0.00007 | $0.00297 |
Grade A, and why
building-threat-intelligence-feed-integration scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get("https://urlhaus.abuse.ch/downloads/csv_recent/") Copies of this mod
2 near-identical copies found in the catalogue:
- building-threat-intelligence-feed-integration — 100% identical, 0 lines differ
- building-threat-intelligence-feed-integration — 97% identical, 36 lines differ
How it starts
The opening of the file, as written. The whole thing — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Building Threat Intelligence Feed Integration
When to Use
Use this skill when:
- SOC teams need automated ingestion of threat intelligence feeds into SIEM platforms
- Multiple TI sources require normalization into a common format (STIX 2.1)
- Detection systems need real-time IOC matching against network and endpoint telemetry
- TI feed quality assessment and deduplication processes need to be established
Do not use for manual IOC lookup — use dedicated enrichment tools (VirusTotal, AbuseIPDB) for ad-hoc queries.
Prerequisites
- MISP instance or Threat Intelligence Platform (TIP) for feed aggregation
- STIX/TAXII client library (
taxii2-client,stix2Python packages) - SIEM platform (Splunk ES, Elastic Security, or Sentinel) with TI framework configured
- API keys for commercial and open-source feeds (AlienVault OTX, Abuse.ch, CISA AIS)
- Python 3.8+ for feed processing automation
Workflow
Step 1: Identify and Catalog Intelligence Sources
Map available feeds by type, format, and update frequency:
| Feed Source | Format | IOC Types | Update Freq | Cost |
|---|---|---|---|---|
| AlienVault OTX | STIX/JSON | IP, Domain, Hash, URL | Real-time | Free |
| Abuse.ch URLhaus | CSV/JSON | URL, Domain | Every 5 min | Free |
| Abuse.ch MalwareBazaar | JSON API | File Hash | Real-time | Free |
| CISA AIS | STIX/TAXII 2.1 | All types | Daily | Free (US Gov) |
| CrowdStrike Intel | STIX/JSON | All types + Actor TTP | Real-time | Commercial |
| Mandiant Advantage | STIX 2.1 | All types + Reports | Real-time | Commercial |
Step 2: Ingest STIX/TAXII Feeds
Connect to a TAXII 2.1 server and download indicators:
from taxii2client.v21 import Server, Collection
from stix2 import parse
# Connect to TAXII server (example: CISA AIS)
server = Server(
"https://taxii.cisa.gov/taxii2/",
user="your_username",
password="your_password"
)
# List available collections
for api_root in server.api_roots:
print(f"API Root: {api_root.title}")
for collection in api_root.collections:
print(f" Collection: {collection.title} (ID: {collection.id})")
# Fetch indicators from a collection
collection = Collection(
"https://taxii.cisa.gov/taxii2/collections/COLLECTION_ID/",
user="your_username",
password="your_password"
)
# Get indicators added in last 24 hours
from datetime import datetime, timedelta
added_after = (datetime.utcnow() - timedelta(days=1)).strftime("%Y-%m-%dT%H:%M:%S.000Z")
response = collection.get_objects(added_after=added_after, type=["indicator"])
for obj in response.get("objects", []):
indicator = parse(obj)
print(f"Type: {indicator.type}")
print(f"Pattern: {indicator.pattern}")
print(f"Valid Until: {indicator.valid_until}")
print(f"Confidence: {indicator.confidence}")
print("---")
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 343 lines · 74 tokens per session scan A af58c8d74fa9
building-threat-intelligence-feed-integration is a skill published in the GitHub repository 26zl/cybersec-toolkit (52 stars, last pushed yesterday), licensed MIT. It adds 74 tokens to every session and 2,973 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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