Jeevesus — DugganUSA Threat Intelligence MCP
check-package: block malicious npm/PyPI deps before your AI agent installs them. Free, no key.
我该使用它吗
质量与安全性
发现(7)
- HIGH
- MEDIUM在 stix-feed-summary 中
- LOW在 enrich-ioc 中
- LOW在 stix-feed-summary 中
- LOW在 kev-vendor-risk 中
- LOW在 kev-exploitation-stickiness 中
- LOW在 check-package 中
基于对工具定义和协议合规性的自动分析。
上下文开销
这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。
安装
一键安装
将以下内容添加到你的 `claude_desktop_config.json` 文件中:
{
"mcpServers": {
"dugganusa-threat-intel": {
"url": "https://analytics.dugganusa.com/api/v1/mcp"
}
}
}远程端点
https://analytics.dugganusa.com/api/v1/mcpstreamable-http它能做什么
工具清单
工具(6)
🟢search(query, indexes, limit)
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.
输入模式
{
"type": "object",
"properties": {
"query": {
"type": "string",
"minLength": 1,
"maxLength": 500,
"description": "Search query."
},
"indexes": {
"type": "string",
"maxLength": 200,
"pattern": "^[a-z0-9_,]+$",
"description": "Optional comma-separated allow-listed indexes. Defaults to all public indexes."
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 25,
"description": "Max results (default 10, hard max 25)."
}
},
"required": [
"query"
],
"additionalProperties": false
}🟢enrich-ioc(indicator, value, type)
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.
输入模式
{
"type": "object",
"properties": {
"indicator": {
"type": "string",
"minLength": 1,
"maxLength": 500,
"description": "The indicator to enrich (IP, domain, URL, or hash)."
},
"value": {
"type": "string",
"minLength": 1,
"maxLength": 500,
"description": "Alias of `indicator`. Either field works."
},
"type": {
"type": "string",
"enum": [
"ip",
"domain",
"url",
"hash",
"email",
"auto"
],
"description": "Optional type hint. Default auto-detect."
}
},
"additionalProperties": false
}🔴stix-feed-summary(days)
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.
输入模式
{
"type": "object",
"properties": {
"days": {
"type": "integer",
"minimum": 1,
"maximum": 7,
"description": "Lookback window in days (1–7). Default 1."
}
},
"additionalProperties": false
}🟡kev-vendor-risk(vendor)
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.
输入模式
{
"type": "object",
"properties": {
"vendor": {
"type": "string",
"description": "Optional vendor or product name (e.g. \"Adobe\", \"Citrix\", \"SharePoint\", \"ColdFusion\"). Omit for the top-vendor risk ranking.",
"maxLength": 80
}
},
"additionalProperties": false
}🟢kev-exploitation-stickiness(days)
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).
输入模式
{
"type": "object",
"properties": {
"days": {
"type": "integer",
"minimum": 30,
"maximum": 720,
"description": "Recent-window size in days (30-720). Default 180."
}
},
"additionalProperties": false
}🟢check-package(ecosystem, name, version)
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.
输入模式
{
"type": "object",
"properties": {
"ecosystem": {
"type": "string",
"enum": [
"npm",
"pypi",
"PyPI",
"NPM"
],
"description": "Package ecosystem: npm or pypi."
},
"name": {
"type": "string",
"minLength": 1,
"maxLength": 214,
"description": "The package name to check."
},
"version": {
"type": "string",
"maxLength": 64,
"description": "Optional exact version for version-aware checking."
}
},
"required": [
"ecosystem",
"name"
],
"additionalProperties": false
}社区
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