Detect LSASS credential dumping, SAM database extraction, and NTDS.dit theft using Sysmon Event ID 10, Windows Security logs, and SIEM correlation rules
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Detect LSASS credential dumping, SAM database extraction, and NTDS.dit theft using Sysmon Event ID 10, Windows Security logs, and SIEM correlation rules
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。
Deploys and monitors ransomware canary files across critical directories using Python's watchdog library for real-time filesystem event detection. Places strategically named decoy files that mimic high-value targets (financial records, credentials, database exports) in locations ransomware typically enumerates first. Monitors for any read, modify, rename, or delete operations on canary files and triggers immediate alerts via email, Slack webhook, or syslog when interaction is detected, providing early warning before full encryption begins.
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。
Conducts external reconnaissance using Open Source Intelligence (OSINT) techniques to map an organization's external attack surface without directly interacting with target systems. The tester gathers information from public sources including DNS records, certificate transparency logs, search engines, social media, code repositories, and data breach databases to build a comprehensive target profile. Activates for requests involving OSINT reconnaissance, external footprinting, attack surface mapping, or passive information gathering.
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Parses Software Bill of Materials (SBOM) in CycloneDX and SPDX JSON formats to identify supply chain vulnerabilities by correlating components against the NVD CVE database via the NVD 2.0 API. Builds dependency graphs, calculates risk scores, identifies transitive vulnerability paths, and generates compliance reports. Activates for requests involving SBOM analysis, software composition analysis, supply chain security assessment, dependency vulnerability scanning, CycloneDX/SPDX parsing, or CVE correlation.
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。
Test vector stores for embedding inversion, cross-tenant leakage, and poisoning.
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Run Tamanu pre-release verification checks: verify that hotfixes on the current release branch are merged forward to main, and that hotfixes from prior release branches are included in the current release. Use when the user wants to run "pre-release checks", verify hotfix integrity before cutting or shipping a Tamanu release, confirm a release/X.YY branch is safe to release, or check that no hotfix has been orphaned (left on neither main nor the current release). Handles Tamanu's train-release model (release/X.YY branches vs vX.YY.Z patch tags) and the cherry-pick model where the same logical fix has different SHAs on different branches. Purely git-based — no live database or Canopy access needed. Not for deciding which tests to run (see scope-tamanu-release-tests).
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。
Run the Tamanu release-branch CUTOFF checks when preparing to cut a new release/X.YY branch: confirm the previous release's hotfixes are merged to main, reconcile the commits since the previous release against the "Merged to main" card list from Linear, and scan for data/reporting/schema changes. Use when the user is cutting a Tamanu release and wants to verify the codebase is ready, wants to check main against the previous release branch, or wants to reconcile commits with a Linear "Merged to main" column (they should paste the card list). Handles Tamanu's train-release model (release/X.YY branches vs vX.YY.Z patch tags) and the cherry-pick model where the same logical fix has different SHAs on different branches. Purely git-based — no live database or Canopy access needed. Not for verifying an existing release branch's hotfix integrity (see pre-release-checks) or for deciding which tests to run (see scope-tamanu-release-tests).
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Check upgrade safety for a Tamanu upgrade that spans many versions: verify that every intermediate hotfix is included in the target version, and surface the new configuration/settings, data migrations, and FHIR rematerialisation impact the upgrade brings. Use when the user wants to check an upgrade from one Tamanu version to another (e.g. "check hotfixes from v2.31 to v2.47"), confirm no intermediate hotfix was dropped, or understand what config, migrations, and FHIR rework a multi-version jump requires. Handles Tamanu's train-release model (release/X.YY branches vs vX.YY.Z patch tags) and the cherry-pick model where the same logical fix has different SHAs on different branches. Purely git-based — no live database or Canopy access needed. Not for cutting a release (see release-cutoff-checks) or deciding which tests to run (see scope-tamanu-release-tests).
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。
Manage Things 3 via the `things` CLI on macOS (add/update projects+todos via URL scheme; read/search/list from the local Things database). Use when a user asks SolanaOS to add a task to Things, list inbox/today/upcoming, search tasks, or inspect projects/areas/tags.
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。
Notion API for creating and managing pages, databases, and blocks.
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。
Use when working with Nuxt Content v3 - provides collections (local/remote/API sources), queryCollection API, MDC rendering, database configuration, NuxtStudio integration, hooks, i18n patterns, and LLMs integration
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Correlate events across multiple log files from different sources, systems, or time periods. Build unified timelines, identify causal relationships between events, and highlight anomalies that span multiple data sources. Supports timezone normalization and gap detection. Use when analyzing logs from multiple systems (frontend, backend, database, infrastructure), investigating distributed system failures, or building event timelines across services. Triggers: "correlate these logs", "build timeline from multiple logs", "cross-system analysis", "find related events across logs", "multi-source log analysis", "distributed trace analysis"
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Use when designing, reviewing, modifying, migrating, optimizing, securing, operating, troubleshooting, or decommissioning data architectures across data model exploration, SQL, ISO SQL conformance, NoSQL, vector, graph, document, time-series, NewSQL, search, in-memory, SQLite, CDC/Debezium, DBMS storage/query/recovery internals, database incident prevention, hardware acceleration, cache, big-data, lakehouse, and warehouse systems.
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Choose the design and the numbers a research run can honestly claim — write the structured METHOD RECORD (databases, date of access, search string, criteria, screening counts) that r0 validates, pick the claim strength a design can actually carry, record a statistic as data rather than prose, route to the reporting guideline the design owes, and decide what to preregister. Use when a run's question, design, search or statistics have to be settled before the writing, or when a claim needs a strength or a number attached to it.
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Add or improve canonical data catalog collections, fields, aliases, relations, evidence tags, docs, and tests.
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Review storage placement across framework global data, workspace data, host state, sidecars, caches, vaults, and external sources.
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。
Specialist for the entire job application process. Analyzes job postings, optimizes profiles (LinkedIn/CV), and generates tailored cover letters. Generates ASCII CVs from a SQLite database and folder structure. cv_generator.py is ported standalone -- no BACH runtime required.
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Mine any Telegram channel or chat for signal in one command: incremental zero-token scrape, deterministic detector shortlist, LLM judge for what is genuinely valuable to this owner, then linked vault notes, a database row, a map-of-content entry and reindex. Triggers: "/mine-channel <@channel|id>", "alpha from <channel>".
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Report what is genuinely new in the last 30 days on a topic, by slicing locally collected nightly channel databases with no live crawling. Run it before a strategic decision, as the fresh-signal feed for the gap phase. Triggers: "/last30days <topic>", "trendwatch <topic>", "what changed last 30 days on X".
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Read the system-architect map: a deterministic catalog of everything the setup is made of (vault, import scripts, scheduled tasks, MCP servers, SQLite databases, hooks, skills, dashboards), what is healthy and what fell off. Consult it before changing shared infrastructure and re-scan after. Triggers: "/arch", "/arch broken", "/arch scan", "what broke in the system".
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Senior engineer CLI expertise for AI agents — workflows, safety guardrails, gotchas, and anti-patterns across cloud, IaC, containers, databases, dev tools, and platforms
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Bring an EPA SWMM (.inp) or EPANET (.inp) model into MIKE+ via the mike-plus MCP server — the bridge from an INP builder such as SWMMCanada or agentic-swmm into a MIKE+ database that mike_model_info / mike_run can use. Use when the user has an .inp and wants it in MIKE+. Requires MIKE+ installed + a checked-out license (demo mode caps the model size).
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Search the live web and 36+ specialised data sources including SEC filings, PubMed, ChEMBL, clinical trials, FRED economic indicators, and patent databases. Use when current, authoritative, or paywalled data is required.
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Deploy web apps with backend APIs, database, and file storage. Use when the user asks to deploy or publish a website or web app and wants a public URL. Uses HTTP API via curl.
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。