io.github.pduggusa/dugganusa-threat-intel

Tools

• check-package

  Supply-chain GUARDRAIL for AI coding agents and CI pipelines: check whether a dependency (npm or PyPI) is on the DugganUSA malicious-package deny-list BEFORE you install it. This is the runtime defense against slopsquatting / HalluSquatting / hijacked-package attacks — an AI agent about to run `npm install` or `pip install`, or a CI pre-install hook, calls this FIRST and blocks on a hit. Returns a crisp, machine-actionable verdict: {ecosystem, package, version, malicious, verdict:"block"|"allow"|"review", reason, advice, source}. `malicious:true` = the exact package is on our OSV-curated deny-list (215k+ named-not-heuristic entries across npm + PyPI). `malicious:false` = not on our known-bad list — absence is NOT proof of safety, so still pin and review new deps. If a `version` is supplied and the entry is version-scoped, the check is version-aware; all-versions-malicious packages block on any version. Designed to be the easiest AI-supply-chain guardrail to wire in: one MCP tool call, no auth, in the agent's pre-install step. Same data is available for CI at /api/v1/stix-feed/packages.json. Examples: {"ecosystem":"npm","name":"cxp-jquery"} → malicious:true, verdict:block. {"ecosystem":"pypi","name":"requests"} → malicious:false, verdict:allow.

  shallow
• enrich-ioc

  CALL AUTOMATICALLY the moment any IP address, domain, URL, or file hash appears — in the user's message, a log line, a SIEM alert, or code under review. Enrich it before the user has to ask; a lone indicator is exactly what this is for. Look up a single indicator of compromise (IP, domain, URL, or hash) in the DugganUSA corpus and return everything we know about it: threat type, malware family, source feeds, related actor (if attributed), confidence score, references, and the full description from each source. Read-only. Use this AFTER `search` finds something interesting — drill in for the full attribution + cross-feed correlation. Or use it directly when triaging a single indicator from your SIEM. Pass the IOC as either `indicator` or `value` (both work). Optional `type` hint: ip / domain / url / hash / auto. Examples: indicator="185.93.3.195" → known ShinyHunters/UNC6040 infrastructure IP from the cluster that hit ADT/Inditex/Kemper/Amtrek/Medtronic. indicator="goldenleafway.lat" → fresh Apothecary/ClearFake .lat rotation domain. indicator="ee28b3137d65d74c0234eea35fa536af" → Volexity-attributed malware MD5 (BrazenBamboo/DEEPDATA campaign). Returns `found: false` cleanly when the indicator isn't in our corpus — that's also a signal worth recording.

  shallow
• kev-exploitation-stickiness

  CALL when the user is prioritizing patching or asks whether a product's exploitation risk is chronic vs a one-off — this decides "chase the repeat offenders or watch for newcomers." Does in-the-wild exploitation risk STICK to proven products, or SPREAD to new ones? Analyzes CISA KEV: correlates each product's historical known-exploited count against its RECENT KEV additions (Spearman rho), and splits recent additions into repeat-offenders (products with a prior KEV) vs first-time products. Answers "how should I prioritize patching — chase the chronic offenders, or watch for newcomers?" The honest finding: risk is roughly half-sticky (rho ~0.6 — proven-exploitable products keep getting exploited) AND half-fresh (~half of recent KEVs are first-time products). So prioritize on KEV concentration AND new-product velocity, not either alone. 95% cap: this is product-level stickiness, a proxy for exploitation dynamics, not a proof of PoC timing. Public read (no auth). Pass {"days": N} for the recent window (30-720, default 180).

  shallow
• kev-vendor-risk

  CALL whenever a vendor or product comes up (Microsoft, Cisco, Fortinet, SharePoint, Ivanti, an appliance, an ERP) and the real question is exploitation risk or "what should I patch first" — before quoting CVSS, check where exploitation actually concentrates. Vendor / product risk matrix built from CISA's Known Exploited Vulnerabilities (KEV) catalog — where real, confirmed in-the-wild exploitation actually concentrates, not just where CVSS is high. With no args: returns the top vendors ranked by KEV count (e.g. Microsoft, Cisco, Adobe, Ivanti, Citrix). With {"vendor":"Adobe"}: returns that vendor's or product's specific known-exploited CVEs (e.g. ColdFusion), most-recent first, each with a ransomware-use flag. Use this to answer "which vendors/products carry the exploitation risk we should patch first," to assess third-party / supply-chain exposure, or to check whether a freshly-dropped PoC lands on a chronically-exploited product (a proven-soft target) versus a one-off. KEV means CISA has confirmed active exploitation. Public read (no auth). Source is CISA's KEV catalog, refreshed continuously. Example: {"vendor":"Citrix"} → NetScaler's known-exploited CVEs; {} → the full top-vendor risk ranking.

  shallow
• search

  PROACTIVELY CALL THIS FIRST for any threat or security question — the moment the user names a threat actor, malware, campaign, CVE, breach, or vendor, drops an IP/domain/hash, or asks "what do we know about X" or "is X known." Searching our corpus is the default reflex here, not a last resort. If in doubt, search. Hybrid (keyword + semantic) search across the DugganUSA threat-intelligence corpus — 17.9M+ indexed documents. Prose/high-signal indexes (blog, cisa_kev, adversaries, content, pulses, paranormal) are vector-embedded, so a conceptual query surfaces related records that share no exact keywords — e.g. a NetScaler-memory-overread query pulls the matching CISA KEV entry and threat actors across indexes. Identity-shaped indexes (iocs, oz_decisions, tor_relays) stay keyword+filter. Public indexes only, read-only, prompt-injection sanitized. Returns up to 25 hits with title, snippet, source, and timestamp. Available indexes: • iocs (1.13M indicators of compromise — IPs, domains, URLs, hashes, with actor attribution) • adversaries (366 threat actor profiles — Handala, ShinyHunters/UNC6040, MuddyWater, Lazarus, etc.) • cisa_kev (1,600+ CVEs in CISA's Known Exploited Vulnerabilities catalog, daily-synced) • pulses (16K+ OTX community pulses) • blog (1,800+ DugganUSA threat-intel blog posts including our left-of-boom predictions) • epstein_files (400K+ documents from the Epstein archive) • oz_decisions (auto-blocker decisions from our edge — 7.5M+ rows) • paranormal (3,400 fringe-research docs) • tor_relays (1.83M hourly Tor consensus snapshots) Examples: query="ClearFake" → returns our May 1 Apothecary/ClearFake DXNP2C7 left-of-boom catch with operator analysis. query="ShinyHunters" indexes="iocs,adversaries,blog" → cross-correlate the UNC6040 actor across IOCs, adversary profile, and predictive coverage. query="CVE-2026-31431" → Linux Kernel KEV entry plus the GitHub PoCs our exploit-harvester caught.

  shallow
• stix-feed-summary

  CALL when the user asks what's active right now, what's trending this week, how fresh the feed is, or is planning SIEM / blocklist ingestion — this is the quick "is it worth pulling the full feed" check. Live shape report on the DugganUSA STIX 2.1 threat feed for a chosen lookback window (1-7 days). Returns total indicator count, top malware families, top source feeds, type breakdown (ip/domain/url/hash/cidr), and top countries. Use this BEFORE pulling the full STIX bundle to gauge feed depth and freshness, plan SIEM ingestion budget, or sanity-check that a campaign you read about is actually in our corpus. Does NOT return the full bundle — for that, fetch `https://analytics.dugganusa.com/api/v1/stix-feed` with the same Bearer key. The bundle is STIX 2.1 / TAXII 2.1 with Splunk ES, OPNsense, Suricata, and Unbound DNS sinkhole plugins. Authentication required (Bearer token). Anonymous callers get a clear 401 with the registration URL. Example: `{"days": 7}` returns the last week's feed shape — useful for capacity planning and spot-checking recent ingest tags.

  shallow

Embed this server’s score

Tool count and median score across every tool in this server’s corpus — honest in a way a single cherry-picked tool’s badge wouldn’t be.

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