You are helping a penetration tester exploit stored (persistent) cross-site
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。
2,196 件 ・ 関連度順
概要と使いどころ
You are helping a penetration tester exploit stored (persistent) cross-site
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。
Mobile (Android + iOS) application penetration testing methodology. Covers static analysis (apktool/jadx for Android, class-dump/Hopper/IDA for iOS), dynamic instrumentation with Frida and Objection, SSL pinning bypass strategies, root/jailbreak detection bypass, deep-link / URL-scheme abuse, exported component attacks (Android activities, services, providers, receivers; iOS XPC, URL schemes, universal links), insecure data storage (SharedPrefs, KeyStore misuse, NSUserDefaults, Keychain ACL bypass), IPC / Intent redirection, WebView vulnerabilities (JavaScriptInterface, file:// access), Firebase/AWS/Azure misconfiguration leakage, mobile API testing, biometric/Face ID/Touch ID bypass, app-cloning and runtime patching, and mobile malware/RAT analysis primitives. Use for mobile pentest, bug bounty mobile triage, or app-store reconnaissance.
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。
End-to-end Android APK red-team pipeline — automated APK acquisition (Play Store + apkpure + apkmirror fallback), jadx decompilation, secret/URL/JWT/Firebase grep, pinned-cert extraction, exported-component enumeration, Frida runtime instrumentation templates, intent-injection probes. Built from an authorized external red-team engagement where 7 APKs were pulled manually, 4 download attempts truncated, and a hardcoded JWT + 30 internal API endpoints were recovered from one of the apps. Use when target has a mobile app catalogue (Play Store developer page), when you find an APK URL hosted on a web server, or when post-recon mentions 'mobile app' in scope.
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。
End-to-end iOS red-team pipeline — IPA acquisition (App Store extraction, TestFlight, enterprise/ad-hoc sideload), class-dump/Hopper/Ghidra static analysis, Info.plist + entitlements + Keychain secret extraction, App Transport Security (ATS) misconfig + certificate-pinning bypass (frida-ios-dump, objection, SSL Kill Switch 2), URL-scheme / Universal Link hijack, exported-service enumeration, Frida runtime instrumentation. Companion to apk-redteam-pipeline for the iOS side of a mobile app catalogue. Use when target has an iOS app (App Store listing, TestFlight link, enterprise MDM distribution), when an IPA URL is found hosted on a web server, or when post-recon mentions 'iOS app' / 'mobile app' in scope alongside an Apple developer account.
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。
Hunt LDAP Injection and XPath Injection — authentication bypass, blind char-by-char attribute exfiltration, AD user/group enumeration, XML-store XPath bypass. Covers the LDAP special-character set (* ( ) NUL /), search-filter-context vs DN-injection, parenthesis-balancing, AND/OR filter logic, and {SSHA}/{CRYPT} userPassword exfil on non-AD directories. Use when target uses LDAP/AD authentication, corporate SSO with a directory backend, an address-book/people-search API, or XML-based data stores queried with XPath.
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。
Firebase gives you a complete backend in minutes - auth, database, storage, functions, hosting. But the ease of setup hides real complexity. Security rules are your last line of defense, and they're often wrong. Firestore queries are limited, and you learn this after you've designed your data model. This skill covers Firebase Authentication, Firestore, Realtime Database, Cloud Functions, Cloud Storage, and Firebase Hosting. Key insight: Firebase is optimized for read-heavy, denormalized data. I
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。
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm
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。
Store, verify, and manage AI data on the Ethereum blockchain (Base network) using the ERCData standard. Use when an agent needs to store data fingerprints on-chain, verify data integrity, create audit trails, manage access control for private data, or interact with the ERCData smart contract. Supports public and private storage, EIP-712 verification, snapshots, and batch operations.
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。
Data structures and algorithms for AI agent episodic memory. Covers vector stores (HNSW, IVF, PQ), temporal indexing, knowledge graphs with triple stores, hierarchical summarization, forgetting curves, working/long-term/ procedural memory, and memory consolidation. Deep analysis of MemGPT/Letta, Zep/Graphiti, Mem0, and the Stanford generative agents memory architecture. Teaches the CS fundamentals behind how agents remember, retrieve, and forget. Activate on: "agent memory", "episodic memory", "vector search algorithm", "HNSW", "memory retrieval", "forgetting curve", "knowledge graph memory", "MemGPT", "Letta", "Zep", "Mem0", "memory consolidation", "temporal retrieval", "agent long-term memory", "memory layer". NOT for: conversation protocol design (use agent-conversation-protocols), agent infrastructure selection (use agentic-infrastructure-2026), building RAG pipelines (use ai-engineer).
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。
Designs and audits data retention and file compaction for an embedded SQLite datastore in a long-lived service — a unified retention registry (one declared policy per table), TTL / absolute-age / row-count-cap policies, a fail-loud coverage guard, WAL/checkpoint tuning, and auto_vacuum/incremental-vacuum so pruning actually shrinks the file. Use when a SQLite DB grows unbounded, a table has an index but no DELETE, a pruned DB never shrinks on disk, metrics are stored as raw events forever, or a new table needs bounding. Keywords retention policy, TTL, reaper, prune, VACUUM, auto_vacuum, incremental_vacuum, WAL checkpoint, freelist, DB bloat, row cap, per-tenant quota. NOT for Postgres/MySQL/server-DB partitioning or TTL, log-line rate-limiting/sampling, backup/replication, schema migrations, or query-performance indexing.
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。
CQRS pattern, event stores, projections, eventual consistency. Activate on: CQRS, event sourcing, event store, read model, projection, aggregate, domain event, command handler. NOT for: message broker setup (use event-driven-architecture-expert), database optimization (use data-warehouse-optimizer).
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。
Undo a haircut trim. Puts back the skills, commands, subagents, MCP servers, hooks, plugins and files that haircut parked into a dated bag, using the receipt it wrote at the time. Use this skill whenever the user says undo the cleanup, undo the haircut, put my config back, restore what was trimmed, I need that MCP server again, that skill is gone and I want it back, roll the trim back, what is in the bag, or which files were moved. Use it also when something stopped working right after a config cleanup and they suspect the cleanup caused it, and whenever they ask how to reverse a config cleanup they regret.
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。
Slackの認証やメッセージ操作、OpenClawの受信・返信を検証するスキル。APIで確かめた結果と実際の画面操作を区別し、証拠と後片付けを確認します。
Notionのローカル保存データを検索し、ページやデータベースの一覧・件数・同期状況を確認して、必要に応じてMarkdownを書き出すスキル。
1Password CLIの導入と認証を確認し、保存したパスワードやAPIキーをコマンドや設定へ渡します。デスクトップ連携やサービスアカウントにも対応します。
Claude CodeでGitの送信や変更破棄などを実行前にブロックするフックを設定します。プロジェクト単位か全体への適用を選び、対象コマンドの調整と動作確認まで行います。
Verify a local agent API, temporary gateway tunnel, and remote sandbox callback with a tool-free task, then restore the original app connection.
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。
Swiftのactorで共有データへのアクセスを管理し、メモリ内キャッシュとJSONファイル保存を組み合わせて、同時アクセス時のデータ競合を避ける保存処理を設計するスキル。
React NativeとExpoのアプリで、画面遷移・状態管理・データ取得を設計します。長い一覧の表示、フォーム、端末機能の利用、認証情報の保存方法も扱います。
NanoClawの対話環境で、Markdownに保存したセッションの再開・分岐・横断検索・履歴圧縮・書き出しを扱い、モデル切り替えやスキル読み込みも支援します。
複数店舗の販売データや商品の特性をもとに、需要予測、安全在庫、発注量を検討するスキル。販促後の需要減少や季節商品の値下げ時期まで計画を支援します。
文書や会話、仕事の情報を内容に合う保存先へ整理し、ローカルファイルや知識ベース、GitHubなどを横断して重複確認、同期、検索を進めるスキル。
ボタンやフォームの操作後に状態がどう変わるかを順に追い、共有状態の意図しないリセットや非同期処理の競合で画面が期待どおりに動かない原因を調べるスキル。
Webページの表示や操作、APIの応答、ビルド・テストの所要時間を計測するスキル。変更前後の結果を比較し、Gitで共有する基準値をもとに性能の悪化を確認します。