AbuseIPDB API reference. IP reputation and abuse report lookups.
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Censys API v2 reference. Host reconnaissance and certificate data.
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
https://search.censys.io/api/v2
Basic Auth: $CENSYS_API_ID:$CENSYS_API_SECRET
curl -s "https://search.censys.io/api/v2/hosts/{ip}" \
-u "$CENSYS_API_ID:$CENSYS_API_SECRET"
Important: Free tier is very limited. Use selectively — prioritise high-value lookups.
curl -s "https://search.censys.io/api/v2/hosts/{ip}" \
-u "$CENSYS_API_ID:$CENSYS_API_SECRET"
Useful fields:
result.services[] — port, service_name, transport_protocol, bannerresult.services[].tls.certificates — TLS certificate chainresult.autonomous_system — ASN inforesult.location — geographic locationresult.operating_system — OS detectionresult.last_updated_at — scan freshnesscurl -s "https://search.censys.io/api/v2/hosts/search?q={query}" \
-u "$CENSYS_API_ID:$CENSYS_API_SECRET"
Search syntax: services.port: 443 AND services.tls.certificates.leaf_data.subject.common_name: example.com
curl -s "https://search.censys.io/api/v2/certificates/{fingerprint}" \
-u "$CENSYS_API_ID:$CENSYS_API_SECRET"
ip: {ip} — specific hostservices.tls.certificates.leaf_data.subject.common_name: {domain} — hosts with cert for domainservices.http.response.body_hash: {hash} — hosts serving same contentservices.jarm.fingerprint: {jarm} — hosts with same JARM fingerprint (C2 detection)labels: {label} — Censys-labeled hostsCensys excels at:
ip: <IP>
services:
- port: <port>
service: <name>
banner: <truncated>
certificates:
- subject_cn: <common name>
issuer: <issuer>
valid_from: <date>
valid_to: <date>
autonomous_system:
asn: <number>
name: <name>
location:
country: <country>
city: <city>
last_updated: <date>
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AbuseIPDB API reference. IP reputation and abuse report lookups.
中文简介正在准备中。当前显示原文说明。
Analysis of Competing Hypotheses — structured technique for evaluating multiple explanations against evidence. Use when facing ambiguous attribution or multiple plausible scenarios. Prefers graded evidence items from /quality-of-information-check and runs that skill first when handed raw URLs or text. Runs on ungraded evidence when asked, labelled as such, unweighted, and capped at Moderate confidence.
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Use when documenting a named campaign across time and victims, the user asks to start or update a campaign record, or another skill identified a multi-incident cluster that warrants formal tracking. Provides the template (timeline, attribution, victimology, attack chain, Diamond Model mapping, IOC clusters) and the lifecycle from active to historical.
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Use when the user asks about carding, BIN attacks, payment-card breach markets, fullz/CVV2 trade, autoshops (BidenCash, Brian's Club, Russianmarket, B1ack's Stash), or financial-fraud TTPs. Self-updating knowledge cell.
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Use when the user asks about Chinese state-sponsored cyber operations or specific PRC-aligned actors (APT41, Volt Typhoon, Mustang Panda, APT10, APT31, Salt Typhoon, etc.), MSS/PLA-attributed campaigns, or PRC sector targeting. Self-updating knowledge cell.
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Use when a report or article needs to be split into individual claims before it is graded, cited or used as evidence — the user asks "what does this report actually claim?", "split this into claims", "separate the facts from the judgements", or another skill needs a claim list. Turns one document into five to twelve atomic claims, each typed (observation, attribution, assessment, actor claim, victim disclosure) and anchored to the verbatim sentence it rests on, so every extraction can be checked against the source. Preserves the source's own hedging. Does not grade. Invoked by /quality-of-information-check; its output feeds /ach, /key-assumptions-check, /intelligence-writing, /writing-assessments and /threat-actor-profiling.
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