「traffic flow」の検索結果

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing patterns.

日本語の概要は準備中です。原文の説明を表示しています。

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing patterns.

日本語の概要は準備中です。原文の説明を表示しています。

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing patterns.

日本語の概要は準備中です。原文の説明を表示しています。

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing patterns.

日本語の概要は準備中です。原文の説明を表示しています。

Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic analysis, packet capture investigation, PCAP analysis, network forensics, C2 traffic detection, or exfiltration detection.

日本語の概要は準備中です。原文の説明を表示しています。

Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic analysis, packet capture investigation, PCAP analysis, network forensics, C2 traffic detection, or exfiltration detection.

日本語の概要は準備中です。原文の説明を表示しています。

Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic analysis, packet capture investigation, PCAP analysis, network forensics, C2 traffic detection, or exfiltration detection.

日本語の概要は準備中です。原文の説明を表示しています。

Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic analysis, packet capture investigation, PCAP analysis, network forensics, C2 traffic detection, or exfiltration detection.

日本語の概要は準備中です。原文の説明を表示しています。

Decompile Android APK, XAPK, JAR, and AAR files using jadx or Fernflower/Vineflower. Reverse engineer Android apps, extract HTTP API endpoints, trace call flows from UI to network layer, and analyze runtime behavior with Frida, network capture, JNI/SO inspection, and signature generation. Use when the user wants to decompile, analyze, hook, inspect network traffic, bypass SSL pinning for analysis, locate crypto or signing logic, or follow call flows in Android packages.

日本語の概要は準備中です。原文の説明を表示しています。

Databricks Model Serving endpoint lifecycle and ops. Use when asked to: CRUD serving endpoints (CLI or MLflow Deployments client); configure traffic routing for A/B / canary deploys and zero-downtime version swaps; retrieve OpenAPI schemas; inspect logs, metrics, or permissions; manage legacy AI Gateway rate limits (not Unity Gateway); discover Foundation Model API endpoints at runtime; integrate endpoints into Databricks Apps; or stream from off-platform clients (Vercel AI SDK v6, standalone Node.js). NOT for: Unity Gateway CRUD and management (databricks-unity-gateway), training, MLflow autologging, UC registration, custom PyFunc/ResponsesAgent authoring (databricks-ml-training); Knowledge Assistants/Supervisor Agents (databricks-agent-bricks); MLflow evaluation (databricks-mlflow-evaluation).

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level transportation engineering covering highway design, traffic flow, intersection design, pavement design, traffic impact studies, and public transit.

日本語の概要は準備中です。原文の説明を表示しています。

Runs SQL queries on CloudWatch Logs data exported as Apache Iceberg tables in S3 Tables. Covers VPC Flow Logs, WAF logs, CloudFront access logs, Route 53 resolver logs, Network Firewall logs, EKS audit logs, Verified Access logs, SES logs, VPC Lattice logs, Step Functions logs, NLB access logs, and 20+ other AWS vended data sources. Applies when analyzing network traffic, investigating security incidents, querying exported logs with SQL, enabling S3 Tables integration, configuring log export, correlating logs with other data, or running Athena queries on the aws-cloudwatch table bucket. Trigger phrases: query logs with SQL, analyze logs in Athena, SQL on VPC flow logs, investigate network traffic, run SQL on exported logs, enable S3 Tables for CloudWatch, correlate logs, historical log analysis, set up log querying.

日本語の概要は準備中です。原文の説明を表示しています。

Guided journey from a leaking conversion flow - landing page, signup, checkout, or in-app onboarding - to a measured, tested funnel. Orchestrates six skills phase by phase - lean-analytics, cro-methodology, storybrand-messaging, hundred-million-offers, influence-psychology, design-everyday-things - each phase carries its full method inline so it runs standalone, asking the user questions at every decision point and recording results in the project docs/ folder (FUNNEL.md, METRICS.md, EXPERIMENTS.md, CONVERSION-OPTIMIZATION-PLAN.md) so the journey resumes across sessions. Use when the user wants to raise conversion on a specific flow, fix checkout or signup abandonment, diagnose onboarding drop-off, or says 'people start but never finish'. With no site yet, use create-website; for a whole-site look, message, and speed audit, improve-website; if the flow converts but needs traffic, grow-website; for in-product engagement and retention, improve-app. For one framework in isolation, invoke that skill directly.

日本語の概要は準備中です。原文の説明を表示しています。

Your competitor just launched. You have no idea how they grew so fast. Should you reverse-engineer their website? Track their social media? Map their growth flywheel? This gives you the complete SOP — from Wayback Machine snapshots to X/Twitter propagation analysis to growth flywheel scoring. Built from 150+ AI startup competitive analyses including the Lovable case study (4.3M views, 229K impressions launch day). By @WeiYipei. Inside: 4-step research framework (website → social → traffic → ad spend) · 3-version Wayback evolution analysis · X/Twitter propagation-chain mapping · growth-flywheel 6-stage scoring · KOL identification · content-effectiveness ranking · ICP + freemium pricing teardown · self-check checklist. New in 1.2: time-machine competitor archaeology — Google date-range search back to pre-fame years, star-history launch-day reconstruction (AppFlowy ~40-channel zero-budget launch teardown), competitor funding news as a launch-timing signal, and the "open source alternative" positioning play. Sourced from first-hand founder interviews (AFFiNE co-founder, 2026-04, self-reported figures marked). 🇨🇳 你的竞品刚刚爆了。你完全不知道他们怎么做到的。该拆官网？盯社媒？画增长飞轮？这份 SOP 给你从 Wayback Machine 快照到 X/Twitter 传播链路还原到飞轮六阶段评分的完整方法论。基于 150+ AI 创业公司竞品分析实战，含 Lovable 完整案例。 🇯🇵 競合が突然バズった。どうやって成長したか全く分からない。このSOPは、Waybackスナップショットからツイッター伝播チェーン分析、フライホイール6段階スコアリングまでの完全な競合調査フレームワークを提供します。150以上のAIスタートアップ分析から構築。 🇰🇷 경쟁사가 갑자기 폭발적으로 성장했습니다. 어떻게 그렇게 빨리 성장했는지 모릅니다. 이 SOP는 Wayback 스냅샷부터 X/Twitter 전파 체인 분석, 플라이휠 6단계 스코어링까지 완전한 경쟁사 조사 프레임워크를 제공합니다. 150개 이상의 AI 스타트업 분석에서 구축. Triggers: "competitor research" | "competitive analysis" | "competitor analysis" | "growth flywheel" | "market research" | "竞品调研" | "竞品分析" | "增长飞轮" | "传播链路" | "競合分析" | "경쟁사 분석" | "social media teardown" | "Twitter propagation" | "content strategy analysis"

OpenStack networking debug operations skill for SDN troubleshooting, packet tracing, and flow analysis. Covers OVS/OVN debugging (ovs-vsctl, ovs-ofctl, ovs-appctl, ovn-nbctl, ovn-sbctl, ovn-trace), security group analysis via OVS flow rules and conntrack, DHCP troubleshooting through namespace inspection and dnsmasq diagnostics, floating IP diagnosis with NAT rule and ARP verification, network namespace inspection (ip netns), MTU chain analysis for overlay networks, DNS resolution debugging, and east-west traffic diagnosis. Use when diagnosing network connectivity failures, tracing packets through the SDN stack, or analyzing flow tables in a running OpenStack cloud.

日本語の概要は準備中です。原文の説明を表示しています。

Detect unauthorized SaaS and cloud service usage (shadow IT) by parsing proxy access logs, DNS query logs, and firewall/netflow data with Python pandas to aggregate traffic by domain, classify domains against known SaaS categories, and score risk by data volume and user count. Use when auditing an organization for unsanctioned cloud/SaaS usage or generating a shadow IT discovery report with remediation recommendations.

日本語の概要は準備中です。原文の説明を表示しています。

Real Chrome/Brave + macOS Computer Use from inside the browser — zero CDP fingerprint, real sessions; mandatory for visual deploy verification. Drive clickwork yourself. USE WHEN verify deploy, confirm UI, screenshot verification, computer use, macos automation, debug web, troubleshoot, visual check, motion/animation bug, jank, transition stutter, scrub a flow, console logs/errors, runtime/JS/react errors, mismatch warning, network traffic/log, HAR/pcapng export, hydration/blank-page debug, flash then blank/page broken, why is this not working/what's happening on the page, authenticated page, bot detection bypass, reproduce bug, drive native app, about to ask the operator to click/navigate/fill a form/log in/approve OAuth, OAuth consent flow, complete a web login, do this in your browser. NOT FOR residential-proxy crawling (BrightData) or social actor scraping (Apify).

日本語の概要は準備中です。原文の説明を表示しています。

Mobile app pentest for bug bounty (Android APK + iOS IPA) — runtime-first workflow: install app, proxy through Burp/mitmproxy, drive the UI, capture packets, then test the API exactly like a web target; escalate to decompile (apktool/jadx) and Frida/objection only when traffic is SSL-pinned, encrypted, or absent. Covers APK/IPA decompile for hardcoded secrets + hidden API endpoints + base URLs the web app never exposes, exported-activity and deeplink intent injection, WebView addJavascriptInterface bridge abuse, SSL pinning bypass (objection patchapk / Frida CertificatePinner + checkServerTrusted hooks), OkHttp interceptor chain to recover request signing, JNI native-lib triage, and the quick apktool/grep secret + endpoint sweep. Use when the program scope includes a mobile app, when web recon dries up and you need a fresh attack surface, or when traffic is pinned and you must MitM it.

日本語の概要は準備中です。原文の説明を表示しています。

Guided journey from a website with traffic it under-converts to a research-driven growth engine that captures more leads, persuades more buyers, sells a sharper offer, and earns referrals. Orchestrates eight skills phase by phase - cro-methodology, scorecard-marketing, storybrand-messaging, made-to-stick, influence-psychology, hundred-million-offers, contagious, one-page-marketing - asking the user questions at every decision point and recording results in the project docs/ folder (WEBSITE.md, OFFER.md, MARKETING.md, GROW-WEBSITE-PLAN.md) so the journey resumes across sessions. Use when the user wants to raise conversion on a site that already has traffic, capture more leads, sharpen a weak offer, add referral loops, or says 'my site gets visitors but nobody buys'. If a broken funnel or usability friction is the real blocker, run improve-website first; if there is no site yet, use create-website; for one leaking flow, conversion-optimization. For one framework in isolation, invoke that skill directly.

日本語の概要は準備中です。原文の説明を表示しています。

Monitor existing content for ranking drops and trigger refresh workflows. Triggers on: "check for content decay", "which content needs updating", "content refresh", "ranking drops", "traffic decline", "stale content", "content audit", "what to refresh", "outdated content", "content performance check", "update old articles", "declining rankings", "content maintenance", "refresh priority list", "which articles are losing traffic", "SEO content audit".

日本語の概要は準備中です。原文の説明を表示しています。

AI SEO Skill workflow skill. Use this skill when the user needs When the user wants to build programmatic SEO with AI, create competitor alternative pages, optimize for AI Overviews, or scale content production. Also use when the user mentions 'SEO,' 'programmatic SEO,' 'AI content,' 'competitor alternative pages,' 'AI Overviews,' 'search optimization,' 'DataForSEO,' 'content at scale,' 'keyword strategy,' or 'organic traffic.' This skill covers AI-powered SEO strategy from keyword research through programmatic page generation. Do NOT use for technical implementation, code review, or software architecture and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

日本語の概要は準備中です。原文の説明を表示しています。

Generates a 3-month SEO performance HTML report for any domain using DataForSEO data. Fetches baseline vs current traffic, keyword rankings, top content pages, and competitive landscape, then outputs a report styled with the Infrasity brand design system: #0D0A1A background, #8157F2 purple accent, Instrument Sans + DM Sans + DM Mono typography. Use this skill whenever a user provides a target domain and a list of competitor URLs and asks for an SEO report, performance report, SEO analysis, competitive SEO comparison, traffic report, ranking report, or 3-month SEO summary. Also trigger when the user says "generate SEO report for X vs Y and Z", "create a performance report", "compare my SEO against competitors", or pastes a domain and asks how it's performing versus the market. Always use this skill for SEO report generation — do not attempt to build the report without following this structured data-fetch and HTML generation workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Conversion rate optimization audit — analyze a landing page, signup flow, or checkout funnel using the 5-layer CRO stack (technical performance, traffic quality, offer/pricing, design/layout, copy/messaging). Produces prioritized fix list with expected impact. Use when "CRO audit", "conversion audit", "why isn't this converting", "improve conversion rate", "landing page not converting", "optimize funnel", "signup flow audit", or any request to diagnose and fix conversion problems.

日本語の概要は準備中です。原文の説明を表示しています。

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.

日本語の概要は準備中です。原文の説明を表示しています。