6,629 件 ・ 関連度順
概要と使いどころ
Race condition (TOCTOU) testing checklist: identifying timing windows, Burp Suite Turbo Intruder, Last-Byte sync technique, rate limit bypass, double-spend attacks, and concurrent request exploitation. Use for web app race condition testing or bug bounty time-of-check-to-time-of-use bugs.
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。
Time-of-Check / Time-of-Use (TOCTOU) race condition exploitation methodology across binary, kernel, filesystem, web, and container layers. Covers symbolic-link races (open/access/stat split), file-descriptor races, fopen/realpath traversal races, /proc and procfs races, FUSE-backed slow-fs races to widen the window, ptrace and signal races, kernel double-fetch / userspace pointer races, container/runc/symlink escape primitives, kubernetes admission/authz TOCTOU, web auth-vs-authz TOCTOU, JWT-claim TOCTOU at gateway vs service, payment/idempotency races, and modern race-amplification techniques (single-packet attack, slow loris, FUSE pause, cgroup freeze, scheduler shaping). Use when you've identified a 'check then act' pattern in code, when fuzzing for race conditions, or when exploiting concurrency bugs in privileged binaries / kernel / orchestrators.
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。
Systematic methodology for identifying and exploiting cryptographic implementation weaknesses in real-world applications. Covers padding oracle attacks against CBC-mode ciphers with PKCS7 padding (Vaudenay's original attack through modern padbuster automation), ECB mode exploitation including block cut-and-paste and byte-at-a-time decryption, hash length extension attacks against SHA1/SHA256/MD5-based MACs using HashPump, RSA vulnerabilities including small public exponent, common modulus, Bleichenbacher PKCS1v1.5 padding oracle, and Coppersmith's method for partial key recovery. Addresses weak PRNG exploitation targeting time-seeded generators and Mersenne Twister MT19937 state recovery from observed outputs, timing side-channel attacks against comparison operations, nonce reuse in AES-GCM leading to authentication key recovery, and key derivation weaknesses including insufficient iteration counts and missing salts. Primary tooling includes padbuster, RsaCtfTool, hashpump, and PyCryptodome for building c...
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。
Fix common cron job failures in Clawdbot/Moltbot - message delivery issues, tool timeouts, timezone bugs, and model fallback 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。
Local speech-to-text using faster-whisper. 4-6x faster than OpenAI Whisper with identical accuracy; GPU acceleration enables ~20x realtime transcription. Supports standard and distilled models with word-level timestamps.
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。
Google Analytics 4, Search Console, and Indexing API toolkit. Analyze website traffic, page performance, user demographics, real-time visitors, search queries, and SEO metrics. Use when the user asks to: check site traffic, analyze page views, see traffic sources, view user demographics, get real-time visitor data, check search console queries, analyze SEO performance, request URL re-indexing, inspect index status, compare date ranges, check bounce rates, view conversion data, or get e-commerce revenue. Requires a Google Cloud service account with GA4 and Search Console access.
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。
Create a verbatim transcript for a YouTube URL using Google Gemini (speaker labels, paragraph breaks; no time codes). Use when the user asks to transcribe a YouTube video or wants a clean transcript (no timestamps).
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。
Read, post, and interact with Bluesky (AT Protocol) via CLI. Use when user asks to check Bluesky, post to Bluesky, view their Bluesky timeline, search Bluesky, or check Bluesky notifications. Supports timeline, posting, profile lookup, search, and notifications.
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。
Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that actually work for neurodivergent minds.
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。
X Intelligence CLI — search, analyze, and engage on X/Twitter from the terminal. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", "search x", "find tweets about", "monitor x for", "track followers", (2) user is working on something where recent X discourse would provide useful context (new library releases, API changes, product launches, cultural events, industry drama), (3) user wants to find what devs/experts/community thinks about a topic, (4) user needs real-time monitoring ("watch"), (5) user wants AI-powered analysis ("analyze", "sentiment", "report"). Also supports: bookmarks, likes, following (read/write), trending topics, Grok AI analysis, and cost tracking. Export as JSON, JSONL (pipeable), CSV, or Markdown. Non-goals: Not for posting tweets, not for DMs, not for enterprise features. Requires OAuth for user-context operations (bookmarks, likes, following, diff).
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。
Personal AI agent visual diary. Auto-records all agent activity, generates daily narrative summaries, visual timeline replay, and AI first-person journal. Use /diary for today's summary, /diary:thoughts for AI personal journal, /diary:replay for visual timeline, /diary:stats for analytics, /diary:persona to view/edit AI personality.
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。
Fast X Intelligence CLI (Rust) — search, analyze, and engage on X/Twitter from the terminal. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", "search x", (2) user wants real-time monitoring with "watch", (3) user needs AI-powered analysis with Grok ("analyze", "sentiment"), (4) user needs intelligence reports ("report"), (5) user wants to track followers ("diff"), (6) user needs trending topics ("trends"). Also supports: bookmarks, likes, following (OAuth), x-search, collections, CSV/JSON/JSONL export. Non-goals: Not for posting tweets, not for DMs, not for enterprise features.
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。
Classify reply sentiment and determine next action
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。
OpenClawのテスト中に起きるメモリ増加や不足を調べます。測定結果やメモリ内の記録を比較し、実際の解放漏れとテスト実行側の保持を見分け、修正を検証します。
運用者が設定したTeamサーバーの更新を、指定担当のNight Watchに引き継ぎ、既存の更新機構による検証・復旧・完了確認まで進めるスキル。
Web検索とページ本文の抽出を使い分け、調査に必要な情報を集めるスキル。期間やサイトを絞った検索、指定URLからの関連部分の取得にも対応します。
OpenClawのリリース候補を人が試すために、隔離コピーなどの検証環境を準備し、テストの進行とフィードバック整理を支援します。公開前の報告確認も扱います。
指定した会話と期間で共有されたOpenClawの変更提案や課題を集め、GitHubで状態と根拠を確認し、影響度と対応準備に応じて優先順位を付けるスキル。
macOS上のOpenClawをmainの最新版へ更新し、Gatewayとアプリの動作を確認します。CIの失敗修正や、公開を伴わないリリース検証も扱います。
OpenClawへの自然な言葉の依頼をClaude Codeなどの外部コーディングエージェントへ振り分け、作業の開始や継続、スレッド内の会話をつなぐスキルです。
Cloud Workerで使うツールを事前に組み込んだイメージを作成・選択し、起動時間と稼働を検証。失敗時の切り戻しや、承認後の旧イメージ削除も扱います。
互いに依存しない不具合やテスト失敗を別々のエージェントに割り当て、並行して調査・修正するスキル。担当範囲を明確にし、結果の確認と変更の統合まで案内します。
コードレビューの指摘を実際のコードや対応環境と照らし合わせ、妥当性を確認します。不明点の整理、根拠を示した返答、修正ごとのテストまで進めるスキルです。
機能追加やバグ修正を、失敗するテストと最小限の実装の順に進めます。利用者が使う公開インターフェースを通じて動作を確かめ、内部構造に依存しないテストを作るスキルです。