Analyze proxy, DNS, and firewall traffic logs to uncover unapproved SaaS and cloud services. Group usage by domain, compare it with approved applications, and produce a report with traffic volumes, user counts, risk scores, and remediation recommendations.
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- Finding unapproved SaaS and cloud services
- Measuring traffic volumes and users by service
- Prioritizing services by potential data leakage risk
mukul975/Anthropic-Cybersecurity-Skills☆ 3.5万2026年8月31日 更新
Detect unauthorized SaaS and cloud service usage (shadow IT) by analyzing proxy logs, DNS query logs, and netflow data using Python pandas for traffic pattern analysis and domain classification.
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andycungkrinx91/konoha☆ 92026年10月19日 更新
tespit etmeunauthorized SaaS and cloud service usage (shadow IT) by analyzing proxy logs, DNS query logs, and netflow data using Python pandas for traffic pattern analysis and domain classification.
中文简介正在准备中。当前显示原文说明。
MustafaKemal0146/fetih☆ 52026年10月11日 更新
Detect unauthorized SaaS and cloud service usage (shadow IT) by analyzing proxy logs, DNS query logs, and netflow data using Python pandas for traffic pattern analysis and domain classification.
中文简介正在准备中。当前显示原文说明。
micsapp/micstec-skills☆ 42026年3月20日 更新
Detect unauthorized SaaS and cloud service usage (shadow IT) by analyzing proxy logs, DNS query logs, and netflow data using Python pandas for traffic pattern analysis and domain classification.
中文简介正在准备中。当前显示原文说明。
aniket2348823/Vul-Agent☆ 22026年6月9日 更新
Org-grade attack-surface mapping: given a company's legal identity, discover its ENTIRE owned internet footprint — corporate family -> owned domains -> owned netblocks/ASN -> live assets — with attribution discipline, not just DNS breadth. The org-first attribution pyramid (legal entity -> LEI/registration -> corporate family -> owned domains -> owned netblocks/ASN -> live assets). Corporate-identity resolution via the GLEIF LEI API (legal name -> LEI, exact-LEI direct-children expansion, downward-only depth-capped BFS, NEVER a name re-resolution), SEC-EDGAR full-text search + Exhibit-21 subsidiary entity names, OpenCorporates entity corroboration, Wikidata SPARQL corporate graph (P856/P355/P749/P1830). Domain attribution via reverse-WHOIS (WhoisXML preview-then-purchase quota guard, SecurityTrails associated-domains — both paid), crt.sh O= certificate-transparency organization pivot (keyless), infrastructure correlation (shared NS/MX/SaaS-TXT, netblock membership, reverse-DNS PTR), and the independent-evidence combiner (1-prod(1-w_i), rule of three, OwnerTier NONE/WEAK/MODERATE/STRONG/CONFIRMED) — discover-only `related:` candidates are NEVER auto-scanned. Netblock/ASN attribution via org-first RIR queries (ARIN Whois-RWS org-handle search, RIPE DB organisation + inverse-org search) that recover 'dark netblocks' with no DNS link to the seed, ASN discovery (RIPEstat + BGPView union), the HYPERSCALER-SCOPE GUARD (never attribute a whole AWS/GCP/Azure/Cloudflare announced range to a tenant — keep only the seed-containing block, tag shared_hosting_cdn), and org-identity-seeded internet-scan-index queries (Shodan/Censys/ZoomEye/FOFA/BinaryEdge org: filters + an always-on keyless crt.sh fallback). Promote-to-scan triage ranks forgotten discover-only netblocks by remote-access exposure (gateway-vendor/KEV/control-plane/datastore port scoring) into an operator queue. Attribution confidence rubric + anti-patterns (namesake grafting via GLEIF name re-resolution, single-signal ownership, hyperscaler over-attribution, privacy-WHOIS pivot poisoning, RIR org-name collisions). Passive/keyless-first OSINT only — every paid-key dependency is enrichment on top of a keyless core, never a hard requirement. Use when mapping an organization's full corporate-family internet footprint, resolving a legal entity to its LEI/subsidiaries, discovering domains/netblocks/ASNs an org owns beyond its one seed domain, auditing M&A/shadow-IT sprawl, or scoping an engagement that starts from a company NAME rather than a domain.
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elementalsouls/Claude-OSINT☆ 28312026年10月10日 更新
SaaS vendor data processing inventory management. Covers shadow IT discovery, API-based data flow detection, processing purpose mapping, contract status tracking, and continuous inventory reconciliation for cloud service providers.
中文简介正在准备中。当前显示原文说明。
mukul975/Privacy-Data-Protection-Skills☆ 3132026年3月17日 更新