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概要と使いどころ
Purple team automation skill that links offensive emulation (Atomic Red Team, Caldera, Stratus Red Team, Leonidas) with detection validation, telemetry-gap analysis, and continuous control testing. Use to design adversary emulation plans tied to MITRE ATT&CK, execute safe tests in lab or controlled environments, and produce evidence-backed detection coverage reports.
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。
Assistant-behavior design skill for approximating a Claude-like analytical, careful, conversational style without claiming to be Claude or Anthropic. Use when the user asks to duplicate, emulate, adapt, or recreate a Claude-style "mythos" or persona for prompts, agent specs, writing style, reasoning discipline, safety posture, or UX behavior.
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。
Server-Side Template Injection (SSTI) occurs when user input is embedded directly into a template engine (Jinja2, Twig, Freemarker, Pebble, Velocity, Smarty, Mako) and evaluated, enabling remote code execution. Detect via math expressions `{{7*7}}` returning `49`, or `${7*7}`, `<%= 7*7 %>`. Leads to full RCE via template sandbox escape, Python `__class__.__mro__` traversal, and Java reflection chains. Tools: tplmap, Burp Suite.
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。
Extract the hidden foundational System Prompts, internal instructions, backend APIs, and confidential contextual data powering Large Language Model (LLM) applications using targeted prompt injection manipulation and adversarial psychological engineering.
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。
Detects weak or misconfigured cryptography in mobile apps (Android/iOS). Trigger on: hardcoded keys, ECB mode, DES, 3DES, RC4, MD5, SHA-1, SecureRandom misuse, static IV, reused IV, Math.random, arc4random, CommonCrypto, CryptoKit, Android Keystore, SecKey, AES-ECB, RSA without OAEP, insufficient key size, predictable seed, insecure key storage, broken hash, PBKDF2 iteration count. Covers MASVS-CRYPTO-1 (algorithm choice) and MASVS-CRYPTO-2 (key management).
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。
Comprehensive LLM security testing prompts for bias detection, data leakage, alignment testing, and adversarial prompt resistance.
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。
Deep OAuth 2.0 / OpenID Connect security assessment. Covers the full attack surface: redirect_uri validation bypass (path traversal, open redirect chains, subdomain confusion, URL parsing tricks, parameter pollution, response mode switching), missing/broken state parameter CSRF, PKCE downgrade and absent-challenge attacks, implicit grant token leakage (Referer, browser history, XSS fragment theft), authorization code injection, scope escalation, client confusion attacks, mutable-claims account takeover (iss+sub confusion, email-keyed identity merging), pre-account takeover via unverified registration, OpenID Connect dynamic client registration SSRF (logo_uri, jwks_uri, sector_identifier_uri, request_uri), nonce replay, ID token validation failures, Device Code phishing flow, mobile custom URI scheme hijacking, refresh token persistence, token introspection enumeration, consent screen clickjacking, host header injection, and cross-IdP mix-up attacks. Uses KOAuth, jwt_tool, nuclei oauth templates, and manual http(action="request", ...) payloads. Every technique includes actual request payloads and verification logic. Chains from /pentester or /api-security when OAuth endpoints are discovered. Chains into /web-exploit for open redirect, XSS, and SSRF chaining. Chains into /post-exploit when full account takeover is achieved. Chains into /credential-audit when access tokens or refresh tokens are recovered.
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。
Execute advanced Man-in-the-Middle (MITM) NTLM Relay attacks specifically targeting environments where SMB Signing is purportedly enabled but improperly configured (e.g., exclusively required on Domain Controllers but NOT enforced universally on standard Workstations or File Servers). Utilize powerful tools like Responder and Impacket's NTLMRelayX to coercively capture NTLMv2 authentications (via LLMNR, WPAD, or Coercion methods like PetitPotam) and seamlessly relay them across the network identically yielding immediate Local Administrator command execution.
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。
Detects insecure platform interaction in mobile apps (Android/iOS). Trigger on: exported Activity, exported Service, exported BroadcastReceiver, Content Provider, Intent injection, deep link hijacking, WebView JavaScript enabled, JavascriptInterface, addJavascriptInterface, setJavaScriptEnabled, intent:// scheme, file:// scheme, WKWebView, WKScriptMessageHandler, UIPasteboard, URL scheme hijacking, Universal Links, PendingIntent, FLAG_IMMUTABLE, overlay attack, tapjacking, screenshot prevention, FLAG_SECURE, Broadcast sniffing, IPC data exposure. Covers MASVS-PLATFORM-1/2/3.
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。
iOS pentesting playbook. Use when testing iOS applications for keychain extraction, URL scheme hijacking, Universal Links exploitation, runtime manipulation, binary protection analysis, data storage issues, and transport security bypass during authorized mobile security assessments.
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 testing file upload endpoints for unrestricted file upload, MIME type bypass, magic byte spoofing, polyglot files, SVG XSS, XXE via Office documents, ZIP slip, and path traversal in filenames. Trigger on: multipart/form-data endpoints, avatar/document upload flows, import-from-file features, profile image, CSV/Excel import, DOCX/XLSX parsing, image resizing pipelines, archive extraction, and any endpoint that stores or serves user-supplied files. Detects extension bypass (shell.php.jpg), null byte injection, double extension, ImageMagick exploits, and content-type confusion.
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。
Lattice-based cryptanalysis playbook. Use when attacking RSA via Coppersmith small roots, recovering DSA/ECDSA nonces from bias, solving knapsack problems, or applying LLL/BKZ reduction to cryptographic constructions.
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。
Java "Ghost Bits" / Cast Attack playbook (Black Hat Asia 2026). Use when attacking Java services where 16-bit char is silently narrowed to 8-bit byte to bypass WAF/IDS for SQL injection, deserialization RCE, file upload (Webshell), path traversal, CRLF injection, request smuggling, and SMTP injection. Affects Tomcat, Spring, Jetty, Undertow, Vert.x, Jackson, Fastjson, Apache Commons BCEL, Apache HttpClient, Angus Mail, JDK HttpServer, Lettuce, Jodd, XMLWriter and re-enables many "patched" CVEs through WAF bypass.
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 organizational egress controls by executing various data exfiltration techniques during a red team engagement. Use this skill to simulate an adversary attempting to steal sensitive data without triggering DLP (Data Loss Prevention) or network monitoring alerts. Covers exfiltration over DNS, ICMP, HTTP/S, alternative protocols (SSH/FTP), cloud services, and physical methods.
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。
AI/ML security playbook. Use when assessing model supply chain attacks (pickle RCE, poisoned weights), adversarial examples, model poisoning, model stealing, data privacy attacks (membership inference, model inversion), and autonomous agent security risks.
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。
《辩论筑基》体系辩论审问——引导出论与攻防处理。基于 grill-me 审问模式，完整内置《辩论筑基》(Debate Universal Grammar) 全套体系。自包含，不需另行学习。
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。
Build a roll-forward schedule for a balance-sheet account or account group, tying beginning balance, activity, reversals, payments, adjustments, and ending balance to GL support. Use for month-end close packages and audit support.
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。
An adversarial job search that gets better as it goes. Set up a job-search workspace, search a careers board and score roles against the realistic applicant pool, build a resume and cover letter, review them with seven agents that return a verdict per submission channel, then write what the review finds back into the profile. Invoke with /slushpile and name what you want to do.
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。
Build a targeted resume and cover letter for a role folder that already has a job description and role analysis. Runs iterative adversarial review rounds until the materials stabilize, then hands off for human review before submission.
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。
Interview the user to surface experience that is real but undocumented, mapped against a specific role's requirements, then update the profile. Use when a fit assessment or an adversarial review flags a section as thin.
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。
Deep linking patterns - Universal Links (iOS), App Links (Android), URI schemes, expo-linking API, React Navigation linking config, Expo Router automatic linking, AASA/assetlinks.json setup, deferred deep links, testing
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。
Tamagui universal UI - styled(), tokens, themes, optimizing compiler, responsive media queries, animations, Sheet/Dialog components
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。
ElevenLabs voice AI SDK patterns for TypeScript/Node.js -- text-to-speech, streaming, voice cloning, speech-to-speech, pronunciation control, and conversational AI
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。
Canonical entry point for the full Gaia evidence verification pipeline. Invoke as /evidence-verification-pipeline or /ev-pipeline — both names trigger this skill. Use whenever you need to run the evidence phases end-to-end: collecting raw evidence from the data lake, verifying live GitHub star counts, running Phase 2B benchmark-source verification, running adversarial auditing for noise and URL errors, and checking link health via Firecrawl. Also use when someone says "run the evidence pipeline", "verify the evidence lake", "audit evidence", "run ev-pipeline", "full evidence check", "pipeline run", "prepare evidence for ingestion", or "refresh the data lake". This is the pre-ingestion step — run it before importing any evidence into the registry.
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。