'feeds' 검색 결과

Conduct a defensible cybersecurity risk assessment using the NIST SP 800-30 Rev 1 methodology: prepare scope and a risk model, identify threat sources and threat events, identify vulnerabilities and predisposing conditions, determine likelihood and impact, compute risk, and communicate results as a prioritized risk register. Use when an organization needs an actual risk *assessment* (not a maturity score), when a control framework (CSF, ISO 27001, RMF, SOC 2, PCI) requires a documented risk analysis as input, when leadership asks "what are our top risks and how bad are they", when assessing risk for a new system or major change, or when building a risk register from scratch. This is the methodology that feeds framework selection, ATO packages, and treatment decisions. Keywords: risk assessment, NIST 800-30, threat modeling, likelihood and impact, risk register, risk analysis, threat sources, vulnerabilities, risk determination, qualitative risk, risk matrix, residual risk, risk treatment.

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Build an automated pipeline to defang indicators of compromise (URLs, IPs, domains, emails) for safe sharing and distribute them in STIX format through TAXII feeds and threat intelligence platforms.

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Automates the enrichment of raw indicators of compromise with multi-source threat intelligence context using SOAR platforms, Python pipelines, or TIP playbooks to reduce analyst triage time and standardize enrichment outputs. Use when building automated enrichment workflows integrated with SIEM alerts, email submission pipelines, or bulk IOC processing from threat feeds. Activates for requests involving SOAR enrichment, Cortex XSOAR, Splunk SOAR, TheHive, Python enrichment pipelines, or automated IOC processing.

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Deploy MISP (Malware Information Sharing Platform) to aggregate, correlate, and distribute threat intelligence feeds from multiple sources for centralized IOC management and automated SIEM integration.

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Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment pipelines.

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Monitor blogs and RSS/Atom feeds for updates using the blogwatcher CLI.

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Researches what prompts people ask AI engines (ChatGPT, Gemini, Perplexity, Claude) about a product category and produces a prompts.csv artifact — a prioritized, strictly-schema'd list of the queries where the brand should be cited. Feeds the monitor workflow.

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Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.

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Creates a personalised daily newspaper from RSS feeds and web sources. Ported from the BACH news system (news.py + newspaper_generator.py). Own SQLite store (no Origin-DB). feedparser optional — XML fallback via stdlib. PDF export via Edge Headless (msedge.exe).

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Incrementally studies git history across tagged or pattern-matched intervals (e.g., creation of planning artifacts like EXECUTION_PLAN_N.md, release tags, or milestone commits). Extracts commit diffs, file churn, and subsystem shifts to track feature evolution and architectural convergence, providing structured feeds for ADR distillation.

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Mutate WooCommerce variation prices via filters — pick the right layer (woocommerce_product_get_price for simple/non-variation products, woocommerce_product_variation_get_price for variations, the woocommerce_variation_prices_* family for the parent min/max aggregation that feeds the catalog "From X to Y" range), and the critical step of filtering woocommerce_get_variation_prices_hash whenever your price logic depends on context outside the default cache key (user role, custom toggle, time of day) — otherwise one user's filtered price gets cached and served to everyone. Use for role-based pricing, time-based discounts, or "filter variation prices but the min/max range doesn't update" debugging. Triggers on woocommerce_product_get_price, woocommerce_product_variation_get_price, woocommerce_variation_prices_*, woocommerce_get_variation_prices_hash, wc_var_prices.

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Handle UTF-8 and text encoding safely in WordPress plugins, especially on WP 6.9+ where wp_is_valid_utf8(), wp_scrub_utf8(), and noncharacter helpers replace older seems_utf8-style checks. Covers when to validate, scrub, reject, or preserve invalid bytes; wp_check_invalid_utf8 behavior; XML/JSON/feed/export boundaries; and avoiding data loss from premature replacement. Use when processing imported text, CSV, XML, feeds, email, REST payloads, AI prompts, logs, filenames, or external API data.

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Use when the user asks to "grow my email list", "design a lead magnet / signup incentive", "set up double opt-in", or "plan a referral / recommendation loop"; produces a list-growth plan — acquisition channels, lead-magnet / incentive concepts, a compliant double-opt-in capture-flow spec, referral-loop mechanics, and subscriber-growth / cost-per-opt-in targets (labeled Estimated) — that feeds SEND-S (consent quality captured at acquisition) and SEND-N (lifecycle entry). Not for the signup page/popup UX itself — use landing-optimizer; not for recording the opt-in — use consent-registry; not for the confirmation-email copy — use email-creative-builder. 邮件列表增长/lead magnet/双重确认/推荐环

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TanStack Virtual headless virtualization for React. Use when rendering large lists (100+ items), implementing virtual scroll, building infinite scroll feeds, virtualizing grids or tables, using window-level scrolling, or implementing masonry/lane layouts with @tanstack/react-virtual. Triggers on: useVirtualizer, useWindowVirtualizer, virtual list, virtual scroll, list virtualization.

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Use when working with Bloomreach — bloomreach commerce search and merchandising platform management including catalog feeds, search configuration, autosuggest, category pages, SEO, A/B testing, pixel tracking, and recommendation widgets. Covers search relevance, catalog health, widget performance, and content personalization metrics.

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Use when turning something that happened into something that makes the next run better - "write a retro", "record this paper cut", "this bug escaped verification", "make this an eval", "why do we keep hitting this", "did that change actually help", "scorecard", "what did we learn from that run", "lessons keep getting re-learned". Covers the six-step loop (capture, classify, convert, change, measure, retro), the repo artifact each step produces, and how escaped bugs become eval cases. Do NOT use to design or judge a single workflow experiment (see `workflow-experimentation`, which this loop feeds), to decide where to run work (see `dogfooding`), or to debug one failed execution in the moment.

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Weekly review partner that compounds productivity gains over time. Tracks velocity, logs friction, sets next-week targets, recognizes patterns across weeks, and feeds insights back to the audit for the next loop. Use when you want a weekly review, need to identify friction, want to see patterns, or want to update your system map. Part of the architect-system loop. Outputs to system/compounder/week-{date}.md.

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Weekly review partner that compounds productivity gains over time. Use when: (1) "weekly review", "what did I accomplish this week?", "compound my gains", (2) End of work week to review progress, (3) "what patterns are emerging?", (4) "update the system map", (5) Feeling stuck and need to identify friction. Reads all system/ files to synthesize progress. Outputs to system/compounder/week-{date}.md. Feeds insights back to /audit.

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Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.

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Use when you need to run real accessibility tests — Playwright keyboard interactions, axe-core scanning, visual regression, and WCAG 2.2 compliance checks. The measurement layer that feeds evidence into a11y-critic reviews.

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Assess a company's economic moat, EBITA margin trajectory, and organic growth trajectory from analyst reports, earnings transcripts, or long-form articles. Produces structured qualitative outlook that feeds into the Financial Modeling skill's assumption generation.

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Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.

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Deploy MISP (Malware Information Sharing Platform) to aggregate, correlate, and distribute threat intelligence feeds from multiple sources for centralized IOC management and automated SIEM integration.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build an automated pipeline to defang indicators of compromise (URLs, IPs, domains, emails) for safe sharing and distribute them in STIX format through TAXII feeds and threat intelligence platforms.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.