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Deep-dive offensive methodology for dependency confusion and namespace attacks across all major package ecosystems. Covers npm scope confusion exploiting the gap between public and private scoped packages and .npmrc misconfigurations where registry mappings fail to pin internal scopes exclusively. Addresses PyPI namespace attacks through --extra-index-url resolution ordering, NuGet feed priority exploitation when multiple package sources are configured without clear directives, Maven and Gradle repository ordering where artifact resolution traverses repositories sequentially, Go module proxy abuse through GOPROXY misconfiguration, Ruby gems namespace squatting, and Docker image tag confusion with unqualified image references. Provides complete proof-of-concept methodology using safe callbacks including DNS canary via interactsh or Burp Collaborator and HTTP beacon with no destructive payload. Covers reconnaissance techniques for discovering internal package names through GitHub repository analysis, error ...

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Hunt source code and build artifact leakage — JavaScript source maps (.js.map) reconstructing TypeScript/ES6 source, Swagger/OpenAPI JSON endpoint discovery, .env/.git exposure, webpack chunks with hardcoded secrets, robots.txt/security.txt recon, build-info files, asset-manifest.json API route discovery, .DS_Store file listing. Use at the START of every recon session — these findings often unlock the entire attack surface.

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 TLS/SSL and DNS misconfigurations — missing HSTS (downgrade attack), weak cipher suites, expired/invalid certificates, mTLS bypass, missing SPF/DKIM/DMARC (email spoofing), DNS Zone Transfer (AXFR), dangling CNAME subdomain takeover, CAA records. Most of these are Info/Low on their own — this skill is opinionated about which findings actually pay (spoofable DMARC with delivered-to-inbox proof, AXFR returning internal hosts, dangling-CNAME takeover) versus which get rejected as best-practice noise (missing CAA, missing HSTS with no MitM position). Use during recon to find infrastructure weaknesses, and to TRIAGE them honestly before reporting.

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Red-team operator discipline — the mindset corrections that separate offensive testing from defensive WAPT. Built from authorized red-team work where conservative defaults caused multiple findings to be missed and one to be incorrectly retracted. Use at the START of any red-team engagement and again whenever feeling stuck or considering 'stopping' on a defended target. The single most important skill to load when scope is 'external red team' not 'bug bounty / WAPT'.

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。

Methodology for detecting client SOC patches, attacker activity, and security-state changes that occur DURING a red-team engagement — and converting those observations into deliverable findings. Built from authorized red-team work where the client patched a confirmed SQLi within 30 minutes of detection AND an external attacker locked multiple new accounts during a single test session. Use when (a) running ANY active engagement against a monitored target, (b) a previously-confirmed finding stops reproducing, (c) baseline timing shifts unexpectedly, or (d) you notice response patterns changing during 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。

Detect Regular Expression Denial of Service (ReDoS) where crafted input causes catastrophic backtracking in regex patterns applied to user-controlled strings.

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。

Exploit development curriculum covering core vulnerability classes with real-world CVE case studies: stack/heap buffer overflows, use-after-free, integer overflows, format strings, type confusion, and race conditions. Use when learning or teaching vuln classes, researching specific CVE patterns, or building exploit dev knowledge.

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Systematic false positive elimination for security findings. 6-gate verification, 13-item checklist, devil's advocate questioning. MANDATORY before any CVE submission.

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Cross-cutting methodology for the CVE-hunting pipeline (ported from find-cve-agent): when a bug is design-vs-real, false-positive avoidance, version checking before reporting, responsible disclosure norms, acceptance-rate expectations per vuln class, vulnerability chaining playbook, known false-positive patterns, maintainer-response patterns, secure-pattern reference (what NOT to flag), and a self-criticism checklist to run before claiming a finding. Use this alongside the cve-hunter/cve-exploiter/cve-validator agents and the /cve-hunt pipeline — load it whenever judging if a finding is real, worth reporting, or already fixed.

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。

Okta-as-IdP red-team attack chain — tenant discovery, user enumeration (multiple vectors), authentication flow analysis (factors enumeration, push-notification fatigue, SMS bypass), password spray with lockout discipline, Okta-specific phishing primitives (kits, FastPass abuse, OIDC redirect_uri tampering), MFA enumeration, post-compromise admin API surface. Many enterprise orgs use Okta instead of (or alongside) Entra ID. Distinct endpoints, distinct rate-limiting, distinct factor flows. Use when recon shows `<tenant>.okta.com`, `<tenant>.okta-emea.com`, `<tenant>.oktapreview.com`, or autodiscover-style records pointing at Okta IdP.

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。

Cross-pollination multiplier technique: find a vulnerability in one package, then search for the same pattern across all similar packages to multiply findings.

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。

Internationalization and localization patterns. Detecting hardcoded strings, managing translations, locale files, RTL 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。

Research any topic across Reddit, X/Twitter, and the web from the last 30 days. Synthesizes findings into actionable insights or copy-paste prompts.

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。

Git-Notes-Based knowledge graph memory system. Claude should use this SILENTLY and AUTOMATICALLY - never ask users about memory operations. Branch-aware persistent memory using git notes. Handles context, decisions, tasks, and learnings across sessions.

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。

Autonomous financial research agent for stock analysis, financial statements, metrics, prices, SEC filings, and crypto data.

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。

Calendar management and scheduling. Create events, manage meetings, and sync across calendar providers.

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。

Backup and restore openclaw configuration, skills, commands, and settings. Sync across devices, version control with git, automate backups, and migrate to new machines.

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Build backend AI with Vercel AI SDK v6 stable. Covers Output API (replaces generateObject/streamObject), speech synthesis, transcription, embeddings, MCP tools with security guidance. Includes v4→v5 migration and 15 error solutions with workarounds. Use when: implementing AI SDK v5/v6, migrating versions, troubleshooting AI_APICallError, Workers startup issues, Output API errors, Gemini caching issues, Anthropic tool errors, MCP tools, or stream resumption failures.

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Make your AI agent learn and improve automatically. Reviews sessions, extracts learnings, updates memory files, and compounds knowledge over time. Set up nightly review loops that make your agent smarter every day.

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。

Navigate and understand codebases using agentlens hierarchical documentation. Use when exploring new projects, finding modules, locating symbols in large files, finding TODOs/warnings, or understanding code structure.

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。

Plan, execute, and measure business events — conferences, webinars, workshops, product launches, networking events, trade shows, and corporate gatherings. Complete event lifecycle from concept to post-event ROI analysis.

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Calculate ROI for AI-as-a-Service (managed AI agents). Estimates cost savings, efficiency gains, and payback period for deploying AI agents across business operations. Use when evaluating whether managed AI agents make financial sense for a company.

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。

Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.

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。