「then」の検索結果

Authentication and credential security assessment. Tests password brute-force, credential stuffing, password spraying, default credential testing, credential harvesting, lockout analysis, MFA bypass, OAuth/OIDC abuse, session token entropy, Kerberos attacks, and intelligent wordlist generation. Uses hydra, john, ncrack, medusa, cewl, crunch, netexec, impacket, kerbrute, and nuclei default-login templates. Covers OWASP A07:2021 Identification and Authentication Failures.

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Authentication bypass testing playbook. Use when assessing login flows, password reset logic, account recovery, MFA bypass, token predictability, brute-force resistance, and session boundary flaws.

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Cloud security posture assessment for AWS, Azure, and GCP. Tests IAM privilege escalation paths, public storage exposure, serverless attack surface, database exposure, logging gaps, container registry security, and cloud-specific attacks. Both authenticated (with cloud credentials) and unauthenticated (external) modes. Uses nuclei cloud templates, Prowler, ScoutSuite, manual IMDS/metadata probing, and deep AWS/Azure/GCP CLI enumeration. Produces: cloud architecture diagram, attack path map, findings per category, compliance mapping (SOC 2, PCI DSS 4.0, HIPAA, CIS), PoCs for confirmed exploits. Chains into /gh-export for issue filing.

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Execute AS-REP Roasting to extract and crack the NTLM hashes of Active Directory user accounts that have the "Do not require Kerberos preauthentication" flag explicitly enabled. This attack generates a recoverable Ticket Granting Ticket (TGT) without requiring the attacker to authenticate first.

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Bypass authentication via forced browsing to protected URLs, parameter tampering (authenticated=yes, debug=true, fromtrustIP=true), session ID prediction from linear/incremental cookies, SQL injection on login forms, PHP unserialize() boolean type juggling (b:1 payload), and credential transport over HTTP. Detectable with Burp Suite, OWASP ZAP, WebGoat.

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Build/test/lint verification pass for this Flutter app — runs codegen, analyze, test, then iOS + Android native builds in parallel, then `dart format`. Does NOT commit anything; leaves the working tree dirty so the user can review and commit on demand. Used at the end of the prd → techspec → tasks → implement-tasks-sequence flow before `pr-review`, and can also be invoked manually when the user says "verify build", "run full verification", or "check everything".

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Use when implementing Django authentication - local accounts, OAuth, email verification, MFA, OIDC, django-organizations

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Use when building Django applications - security hardening, authentication and permissions, ORM optimization, PostgreSQL features, Django 6.0, migrations, testing, and ecosystem libraries

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Drive the user's real, logged-in browser from the shell via the reins CLI. Because it's their actual browser, every site is already authenticated — so you can scrape behind logins, read cookies/tokens/localStorage, watch and replay live API traffic, call a site's own API as the signed-in user, and click/type/screenshot. Use whenever asked to interact with, test, scrape, extract data from, or automate a live webpage or authenticated site in the user's browser.

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Continuously monitor a GitHub PR for merge conflicts, CI failures, and CodeRabbit review comments, then automatically fix any issues found. Polls every 5 minutes and loops until every check is green. Use this skill whenever a PR has just been created or code has been pushed to a PR branch — it should be the default follow-up action after any PR creation or push. Also trigger on: "watch this PR", "guard this PR", "monitor CI", "keep fixing until green", "PRを監視して", "CIが通るまで 直して", /pr-guardian. When a PostToolUse hook reports that a push or PR creation just happened, proactively invoke this skill to start monitoring without waiting for the user to ask.

Run the speckit implementation phase chunk-by-chunk in clean-context subagents, then review, then produce a final report. Picks up from an existing tasks.md.

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Full quality pass -- chains parallel UX + scalability audit, then QA verification, then consistency gate. Fixes everything it finds. Works with any stack.

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Review then build — chains architecture review into implementation. Accepts any spec format (ticket, PRD, engineering spec, feature description, screenshot) and autonomously reviews the design, resolves gaps, then implements with tests and a PR.

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Run an adversarial two-phase code review of a change with TWO independent reviewers — Claude and Codex — who review alone, then cross-examine each other's findings, then Claude synthesizes a single weighted verdict. Use when the user says "/adversarial-review", "adversarial review", "review this with Codex", "get Codex to review", "two-reviewer review", "cross-examine this PR", or wants a second independent model to grade a change before merge.

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Diagnoses Workload Identity Federation for GKE authentication failures for Pods (403 "iam.serviceAccounts.getAccessToken" / permission denied, "could not find default credentials", or GKE metadata server unreachable) by verifying cluster and node-pool Workload Identity configuration, the Kubernetes ServiceAccount (KSA) to IAM binding (direct principal binding and legacy Google ServiceAccount impersonation), target-resource IAM roles, and gke-metadata-server health. Use when a Pod cannot authenticate to Google Cloud APIs even though Workload Identity is expected to be in effect. Don't use for in-cluster Kubernetes RBAC errors (API-server authorization), general workload crashes (use gke-workload-troubleshooting), or Workload Identity setup and hardening (use gke-workload-security).

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Use this skill when designing the human-executable UAT test cases that prove a Salesforce feature works for a specific persona — the per-persona scripts with preconditions, data setup, permission setup, ordered steps, and pass/fail evidence that close out an RTM row. Trigger keywords: UAT test case salesforce, user acceptance test script salesforce, manual test salesforce feature, UAT script per persona, UAT precondition data setup, UAT permission set assignment for testing, negative path UAT case. NOT for high-level UAT planning, defect classification, regression strategy, or sign-off (use admin/uat-and-acceptance-criteria). NOT for the Given/When/Then technique used to write the AC the case is derived from (use admin/acceptance-criteria-given-when-then). NOT for Apex test method generation (use agents/test-class-generator). NOT for test data factory patterns (use templates/apex/tests/TestDataFactory.cls). NOT for performance or load testing.

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Use this skill when writing acceptance criteria for Salesforce features, structuring UAT test scripts from user stories, classifying defects found during UAT, or planning regression testing before a Salesforce release. Trigger keywords: UAT, user acceptance testing, test script, acceptance criteria, defect classification, regression testing, test plan, test case. NOT for Given/When/Then AC syntax — use admin/acceptance-criteria-given-when-then. NOT for the per-case field schema and AC-to-case decomposition — use admin/uat-test-case-design. NOT for automated Flow or Apex test coverage — use flow/flow-testing. Also covers: UAT plan record, sandbox selection for UAT, pre-UAT environment checklist, sandbox email deliverability for testers, test-user personas, negative and bulk coverage, defect triage categories, go/no-go sign-off, quick-deploy window.

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Assemble a finished piece from human-written fragments via an orchestrated two-loop pipeline - an assembly loop (assembler + cold reviewer) that sequences the fragments into a draft, then a polish loop (polisher + cold reviewer), then frequency analysis and a catalog-deslop pass with a regression gate. Two modes with opposite fidelity contracts - stitch mode preserves the author's exact wording, narrative mode preserves every idea but may rewrite freely. Use when the user says "mosaic", "assemble my fragments", "stitch these notes into a post", or provides a fragments file to turn into a finished piece. For writing from a topic with research, use article-factory; for prose from scratch, use the prose skill.

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Remove AI-generated code smells (slop) from branch changes or an explicit file list. Locks behavior with regression tests FIRST, then runs categorized cleanup via parallel `deep` agents in batches of 5, then verifies with quality gates. Covers 10 slop categories including performance equivalences, excessive complexity (object annotations, if/elif variant chains), and oversized modules (250+ pure LOC with mandatory modular refactoring). MUST USE when the user asks to "remove slop", "clean AI code", "deslop", "clean up AI-generated code", "remove AI slop", or wants to clean up AI-generated patterns from recent changes. Triggers - "remove ai slops", "clean ai code", "deslop", "cleanup AI generated", "remove AI slop", "clean up AI-generated code", "strip slop", "ai-slop cleanup".

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Draft the QA scope and plain-language Given/When/Then test scenarios for a Jira ticket, built from the full ticket, the decisions made in its comments, and the actual code change read commit by commit (open PR, the ticket's merged PR, the branch against its base, or a named commit range). Saves a Markdown draft under docs/, iterates with the user, then posts it to the ticket as a new Jira comment only after explicit approval. Use on "QA scope for PROJ-123", "what should QA test", "write test scenarios for QA", "hand this ticket to QA", "prep the QA handoff", "gherkin scenarios for this ticket", or when a branch is ready for manual testing — even when the user only names the ticket or says "this branch".

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Generate non-binding follow-up action suggestions from lead summaries or lead lists. Use when users ask for next best actions, call list for hot leads, or follow-up draft plan without automatic execution. Recommended chain: summary-generator then action-suggester then supervisor approval. Do not use for parsing, storage, or autonomous action execution.

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Guide building a minimum viable product through manual-first, then processized, then productized stages. Use when someone is ready to build their first product or struggling with scope.

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Own goal-first engineering outcomes: investigate, find root cause, design, plan, then delegate implementation unit-by-unit to cursor-implementation-loop, this plugin's kernel skill, with verification and honest reporting. Use to fix, build, or own an outcome end to end; investigate-and-fix; "make X work"; or plan-then-execute in one request. A request with an approved plan or equivalently precise spec that needs nothing beyond implementation belongs directly to cursor-implementation-loop. Requires this plugin's cursor-implementation-loop skill; they ship together.

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Azure Identity SDK for Rust authentication. Use for DeveloperToolsCredential, ManagedIdentityCredential, ClientSecretCredential, and token-based authentication.

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。