「ace」の検索結果

Design banners for social media, ads, website heroes, creative assets, and print. Multiple art direction options with optional generated or supplied visuals. Actions: design, create, generate banner. Platforms: Facebook, Twitter/X, LinkedIn, YouTube, Instagram, Google Display, website hero, print. Styles: minimalist, gradient, bold typography, photo-based, illustrated, geometric, retro, glassmorphism, 3D, neon, duotone, editorial, collage.

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 Spark engineering knowledge must be placed, deduplicated, migrated, or validated across AGENTS, Notes, Roles, Skills, and Workflows.

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 a high-stakes analysis, citation set, or decision should be checked by a second independent AI agent that verifies rather than decides, or when disagreement between agents must be surfaced for the human to adjudicate.

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 a draft in Turkish, English, or both reads as AI-generated and needs revision that removes machine writing patterns and translation calques while preserving meaning, citations, statistics, and the author's voice.

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 building slides, a poster, or a lightning talk from a manuscript, when a presentation must exist in Turkish and English, or when conference visuals need a traceability check so every number on a slide matches the analysis behind it.

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 before sensitive, clinical, identifying, or raw interview data is placed in front of an AI tool, when transcripts or student materials need de-identification, or when a data-minimization gate must run before any analysis or drafting.

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 sources must stay traceable across sessions and years, when each reference needs a passport recording where it was found, how it was verified, and where it is cited, or when a draft needs a cited-but-unverified sweep 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。

Use when reviewer comments arrive and each one needs a tracked decision, when a revise and resubmit letter must map every comment to a manuscript change, or when contradictory reviewer demands need evidence-based, editor-facing framing.

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。

You are helping a penetration tester exploit browser-based attack surfaces. This

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 WebSocket vulnerabilities — Cross-Site WebSocket Hijacking (CSWSH), missing/weak Origin validation on the WS handshake, no per-message authentication, message tampering, socket.io namespace/room authorization bypass, and handshake-layer Upgrade smuggling. Use when target has WebSocket endpoints (ws:// or wss://), socket.io / SignalR / Phoenix Channels, real-time features, chat, live dashboards, notifications, or trading platforms.

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Comprehensive API security testing methodology covering REST, gRPC, and WebSocket attack surfaces. Addresses the full OWASP API Security Top 10 2023 including BOLA/IDOR, broken authentication, excessive data exposure, rate limiting bypass, BFLA, mass assignment, SSRF, and security misconfiguration. Includes REST-specific attacks such as HTTP verb tampering, content-type switching, and parameter pollution. Covers gRPC exploitation through protobuf interception, reflection API enumeration, and metadata injection. Addresses WebSocket vulnerabilities including origin bypass, message injection, and cross-site WebSocket hijacking. Provides tooling guidance for Burp Suite, Postman, grpcurl, websocat, and mitmproxy. Each technique includes detection signatures and defensive indicators so you understand what artifacts your testing leaves behind. Designed for authorized penetration testing engagements against API-driven architectures.

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 Laravel specific vulnerabilities — Debug mode leakage (APP_DEBUG=true exposes full stack trace + env vars), Laravel Telescope/Horizon dashboard unauthorized access, Ignition RCE (CVE-2021-3129), Signed URL manipulation, Queue Worker abuse, mass assignment via Eloquent, deserialization via cookies, .env file exposure. Use when target runs Laravel (PHP) — detected via X-Powered-By, Laravel session cookies, or /storage/ paths.

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Hunt Spring Boot specific vulnerabilities — Actuator endpoints (heapdump, env, loggers, mappings, shutdown), Spring Expression Language (SpEL) injection → RCE, H2 console RCE, Jolokia JMX exposure, Spring4Shell (CVE-2022-22965), Spring Cloud Function SPEL (CVE-2022-22963), heap dump credential extraction. Use when target runs Spring Boot — detected via X-Application-Context header, /actuator, Whitelabel Error Page, or Java stack traces.

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。

Hunting skill for sqli vulnerabilities. Built from 12 public bug bounty reports including modern NoSQL injection (Rocket.Chat CVE-2021-22911 MongoDB $regex, Mongoose ORM CVE-2024-53900 $where bypass), modern ORM raw-fragment SQLi (Django CVE-2024-42005, Sequelize GHSA-wrh9-cjv3-2hpw), second-order SOQL injection (HackerOne Salesforce), time-based blind SQLi in GraphQL resolvers, and SQLi on OIDC-proxy backends. Use when hunting SQLi on any target. Dedicated NoSQL operator injection (MongoDB/CouchDB $where/$regex/$ne) is owned by hunt-nosqli — NoSQL appears here only as adjacent ORM/WAF context.

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。

Advanced API exploitation methodology focused on business logic abuse and sophisticated attack patterns that bypass traditional security controls. Covers business logic bypass through API call chaining and workflow manipulation. Addresses GraphQL-specific attacks including batching for credential brute-force, query depth exploitation, and introspection abuse. Includes pagination exploitation for data exfiltration, webhook hijacking for SSRF and data interception, and resource exhaustion through algorithmic complexity attacks. Covers race conditions in API transactions using parallel request techniques. Provides comprehensive JWT manipulation including algorithm confusion, kid injection, jku/x5u abuse, and claim tampering. Details API key leakage detection across source repositories, client-side code, and error messages. Covers undocumented endpoint discovery through predictable naming, debug routes, and source map analysis. Tooling includes Arjun, ParamSpider, jwt_tool, and GraphQL Voyager. Designed for a...

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 shadow / zombie / undocumented API surface (OWASP API9 Improper Inventory Management) — enumerate the full API version history (v1/v2/beta/legacy paths, header- and subdomain-based versioning), pull and diff every reachable OpenAPI/Swagger spec (including ones only findable via the Wayback Machine), and behaviorally diff old vs. current versions for auth/rate-limit/validation regressions rather than just response-shape differences. Distinct from hunt-api-misconfig, which owns exploitation once you have a spec or endpoint (mass assignment, JWT, OData, Swagger-chain attacks); distinct from hunt-subdomain, which owns host-level discovery. This skill owns the version-inventory and behavioral-diff workflow itself. Use when the target has versioned API paths, multiple specs, a changelog referencing deprecated endpoints, or a mobile app whose hardcoded backend calls look older than the current web app's.

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 HTML Injection — user-supplied input is rendered as raw HTML in the response without sanitisation, allowing an attacker to inject arbitrary HTML tags (but not necessarily JavaScript). Lower severity than XSS but enables phishing, UI manipulation, and credential harvesting via injected forms. Use when testing text-display surfaces (search results, profile fields, comments, error messages, feedback forms). For markup that executes JavaScript, escalate to hunt-xss.

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。

File upload vulnerability checklist: MIME type bypass, extension bypass, magic byte manipulation, path traversal in filenames, stored XSS via SVG/HTML upload, server-side processing attacks, and race conditions. Use for assessing file upload endpoints in web app pentests or bug bounty.

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Triage ASM/recon output for ownership before testing — separate the target's real assets from namespace-collision noise. Automated recon keyword-matches on the brand name, so for any target whose name is a common/dictionary word, the output is dominated by assets belonging to UNRELATED same-named companies (repos, cloud buckets, mobile apps, breach corpora, typosquats). Built from an authorized engagement where an ASM report's 'Criticals' were overwhelmingly false positives and the combo/repos/mobile/bucket lists were polluted with unrelated same-named orgs. Use at the START of any engagement, immediately on receiving any ASM/recon/OSINT dataset, BEFORE testing anything.

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 Windows privilege escalation methodology for offensive security engagements. Covers the full attack surface from a standard user shell to NT AUTHORITYSYSTEM: token impersonation via SeImpersonate and SeAssignPrimaryToken privileges using JuicyPotato, PrintSpoofer, GodPotato, SweetPotato, and RoguePotato; service misconfigurations including unquoted service paths, weak service DACLs, writable service binaries, and insecure service creation permissions; AlwaysInstallElevated MSI exploitation; DLL hijacking through search order abuse, phantom DLL loading, and writable PATH directory injection; UAC bypass techniques via fodhelper.exe, eventvwr.exe, CMSTP, and environment variable manipulation; scheduled task abuse for writable task actions and new task creation; registry autorun exploitation for persistence and escalation; PrintNightmare (CVE-2021-34527) for remote and local privilege escalation; and credential harvesting from SAM database extraction, DPAPI blob decryption, LSA secret dumping,...

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 Linux privilege escalation methodology for offensive security engagements. Covers the full attack surface from a low-privilege shell to root: SUID/SGID binary abuse via GTFOBins, Linux capabilities exploitation (cap_setuid, cap_dac_override, cap_dac_read_search), sudo misconfigurations including NOPASSWD rules and Baron Samedit (CVE-2021-3156), cron job abuse through writable scripts, PATH hijacking, and wildcard injection with tar/rsync/chown. Includes writable /etc/passwd attacks, NFS no_root_squash exploitation, kernel exploits (DirtyPipe CVE-2022-0847, DirtyCow CVE-2016-5195, PwnKit CVE-2021-4034), Docker group container escapes, LD_PRELOAD and LD_LIBRARY_PATH hijacking for shared library injection, systemd service misconfigurations, and sensitive file enumeration for credential harvesting. Integrates automated enumeration with LinPEAS, linux-exploit-suggester, pspy for process monitoring, and GTFOBins for binary exploitation. Each technique includes detection signatures and defender-sid...

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 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。

Web2 recon pipeline — subdomain enumeration (subfinder, Chaos API, assetfinder), live host discovery (dnsx, httpx), URL crawling (katana, waybackurls, gau), directory fuzzing (ffuf), JS analysis (LinkFinder, SecretFinder), continuous monitoring (new subdomain alerts, JS change detection, GitHub commit watch). Use when starting recon on any web2 target or when asked about asset discovery, subdomain enum, or attack surface mapping.

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。

Hunting skill for business logic vulnerabilities. Built from 12 public bug bounty reports. Covers coupon-race-stacking (Instacart, Stripe, Reverb), negative-quantity-in-cart price tampering (Upserve, Eternal/Zomato), decimal/fraction price-field overflow (Shipt), client-side checkout amount trust on PayPal redirect (WordPress.org), price-per-unit mass-assignment (Krisp), and archived-price swap / cart-TOCTOU (Stripe). Use when hunting business logic — heavy emphasis on financial-impact-demonstrated cases.

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。