「net」の検索結果

AWS guidance — core services, IAM least privilege, networking, cost control, and production architecture patterns.

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Structural and functional brain connectivity — tractography, functional networks, and graph-theoretic analysis.

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Use OpenAI models on Azure — enterprise deployment with private networking, compliance, and managed scaling.

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Product-led growth and customer-base growth for B2B SaaS. Use this skill for self-serve funnel work (activation, time-to-value, free trial vs freemium, PQL definition, in-product upgrade moments, sales-assist triggers), for the self-guided interactive product demo that runs in front of the login wall (demo portfolio and flow design, gated vs ungated policy, demo seed data and privacy, keeping a published demo in sync with the shipping product, step-level demo analytics), and for growing revenue from existing customers (adoption, expansion, churn-save, the self-serve cancel flow and failed-payment recovery, renewal marketing, net revenue retention, and champion tracking: watching the people who bought and used you at each customer, confirming a job change from evidence, and running both plays a move fires, the seat they left and the account they joined). Also triggers on: PLG, product-led growth, activation, aha moment, time to value, free trial, freemium, PQL, product qualified lead, onboarding, self-serve, customer marketing, expansion revenue, upsell, cross-sell, churn, retention, NRR, renewal, cancel flow, cancellation flow, save offer, exit survey, pause subscription, dunning, failed payment recovery, involuntary churn, people keep canceling, champion tracking, job change signals, job change alerts, our champion left, our champion changed jobs, customer alumni, former customers who moved to a new company, interactive demo, self-guided demo, product tour, click-through demo, demo automation, demo library, should our demo be gated, ungated demo, demo without a sales call, our demo is out of date, demo shows the old UI, put a demo on our homepage, demo completion rate, demo drop-off, try before you talk to sales.

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DevOps 工作技能 - CI/CD 流程、容器化构建、Kubernetes 部署、基础设施即代码、监控告警。当用户提到部署、容器化、K8s、Helm、ArgoCD、CI/CD、监控、日志、或需要执行部署、排查线上问题时，必须使用此技能。

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This skill provides guidance for using Chrome DevTools MCP for browser debugging and automation. Use when debugging web pages, analyzing performance, inspecting network requests, viewing console messages, or interacting with Chrome DevTools features programmatically.

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Reverses proprietary command-and-control protocols: locating send/recv routines, recovering the message framing and encryption/encoding, and reconstructing the command set to build a decoder or emulator. Activates for requests to reverse a custom C2 protocol, decode beacon traffic, or document a malware command structure.

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Hunts for Cobalt Strike beacon traffic by detecting default stager URI checksum8 values, default Malleable C2 profile artifacts, and default ports/named pipes in HTTP and process telemetry. Activates for requests to hunt Cobalt Strike, detect beacon stager URIs, or find default Malleable C2 indicators.

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Establishes behavioral baselines from historical telemetry (process, network, or logon events) so hunts can flag rare and first-seen activity instead of relying on static signatures. Activates for requests to build a telemetry baseline, find rare or first-seen activity, or compute frequency baselines for anomaly hunting.

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Hunts for domain fronting and CDN abuse by detecting TLS SNI versus HTTP Host header mismatches and high-reputation CDN domains carrying anomalous traffic in network telemetry. Activates for requests to hunt domain fronting, detect SNI/Host mismatch, or find CDN abuse used to mask C2.

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Summarizes runtime behavior of a sample from Procmon-style operation logs — process and thread creation, file and registry writes, and network-related operations — to build a behavioral profile. Activates for requests to analyze Procmon output, summarize sample behavior, or profile process/file/registry activity from a sandbox run.

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Runs a sample in an instrumented sandbox to observe behavior: process tree, file and registry changes, network activity, and persistence, then summarizes the behavioral report into capabilities and IOCs. Activates for requests to detonate a sample, do dynamic or behavioral analysis, or interpret sandbox output.

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Detects DNS-based tunneling and data exfiltration in DNS logs: scoring high query volume to single domains, long/high-entropy subdomains, unusual record types, and encoded payload labels. Activates for requests to hunt DNS tunneling, detect DNS exfiltration, or analyze suspicious DNS query patterns.

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Analyzes a memory image with Volatility 3 to find malware: rogue processes, injected code, suspicious network connections, loaded modules, and persistence, then extracts artifacts for further analysis. Activates for requests to do memory forensics, analyze a RAM dump, or hunt malware in memory with Volatility.

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Analyzes API call traces from a sandbox or API monitor (JSON) to group calls by category, reconstruct high-level behaviors (process injection, file drops, network, crypto), and flag suspicious call sequences. Activates for requests to analyze an API trace, interpret sandbox API logs, or identify behavior from Win32/Native API calls.

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Collects volatile evidence from a potentially compromised host in correct order of volatility: memory, network state, running processes, logged-on users, and open handles, while preserving integrity and minimizing footprint. Activates for requests to collect volatile evidence, perform live response, or capture host state before shutdown.

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Analyzes a PE file's import and export tables to infer capability: mapping imported APIs to behaviors (networking, crypto, injection, persistence), spotting dynamic-resolution stubs, and reading exports of malicious DLLs. Activates for requests to analyze PE imports, inspect the IAT/exports, or infer capability from API usage.

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Analyzes Java/JAR malware (such as Adwind/jRAT-class cross-platform RATs) by inventorying the archive, reading the manifest entry point, detecting obfuscators and string encryption, and flagging suspicious runtime, reflection, and networking class usage. Activates for requests to analyze a malicious JAR, inspect Java malware, or identify a Java RAT.

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The measurement surface for ALL Pulp DSP and audio-pipeline work — read it BEFORE writing or gating DSP, not only when something already sounds wrong. Covers the C++ harness (signal generators, metrics, assertions, RenderScenario, contracts), the offline Audio Doctor (magnitude/frequency response, THD/THD+N, phase/group delay), and their Python sibling the Audio Quality Lab (tools/audio/quality-lab — null residual + alignment, LTAS log-spectral distance, spectral flux/centroid, HNR, Theil-Sen drift slope, Kaiser-sinc resampling, license-guarded corpus, regression-net ratchet). TRIGGER on AUTHORING work — "build/design an oscillator/filter/synth/effect", "add a DSP module", "what should the acceptance gate be", "how do I measure aliasing / anti-aliasing / alias floor", "null against a reference", "is this DSP correct", "choose a tolerance", "golden/regression corpus for audio", "measure drift or jitter", "A/B two renders" — AND on DEBUGGING work — "is there sound / no audio / I hear nothing", "does this filter/compressor/synth/delay produce the right signal", "prove the DSP / prove the contract", "measure the frequency response", "what's the THD / is it distorting", "what's the group delay / phase response / measured latency", "magnitude response curve", "render a test tone and assert", "audio regression", "64-frame works but 128 is silent", "sample-rate change pitch-shifted it", "describe what's in this buffer", "audio doctor", "compare before/after a DSP refactor". Reach for this BEFORE hand-rolling any FFT, null test, alias measurement, pitch tracker, or golden-render script — most of it already exists in one of the two lanes. Test/tool layer over HeadlessHost — deterministic, no audio device, no speakers. Off the realtime thread entirely.

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Implementation guide for common DSP algorithms. Use when the user asks "implement a lowpass filter", "how do I write a compressor", "reverb algorithm", "FFT convolution", "pitch shifter", or "oscillator with no aliasing". Trigger on phrases like "biquad filter", "state variable filter", "feedback delay network", "phase vocoder", "overlap-add", "PolyBLEP", or any request to implement a specific DSP processing block.

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Use when the user encounters VolcEngine errors or needs local troubleshooting for OpenAPI, Python SDK, CLI, IAM, billing, compute, networking, storage, database, CDN, media, AI, security, or VKE cases.

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Use when the user mentions tosutil, TOS object storage, bucket/object operations, batch upload or download, object metadata, TOS connectivity, or errors such as 403/network/argument failures. 围绕火山引擎对象存储 tosutil 生成与校验命令、规划桶/对象操作并诊断错误；当用户提到 tosutil、TOS 桶对象管理、批量上传下载或相关排障时调用。

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Use when the user asks to analyze, consult, setup, manage, configure, or design a Volcengine Landing Zone, including organization, accounts, finance, identity, cloudtrail, or network infrastructure, or to deploy a solution/blueprint.

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Complete methodology for computing publication-quality cumulative abnormal returns with proper event-study test statistics, matching the robustness of Kaspereit's eventstudy2 for Stata. Covers dateline construction, event-date mapping, estimation and event windows, thin-trading adjustment, OLS with Theil prediction error correction, abnormal return computation, CAR/CAAR/AAR accumulation, boundary contamination guards, and common tests such as Patell, BMP, Kolari-Pynnonen, generalized sign, Wilcoxon, and GRANK-T. Use when the user mentions abnormal returns, event windows, market-model regressions, CARs, CAAR, AAR, eventstudy2, thin trading, trade-to-trade returns, or event-study test statistics.

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。