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Analyze Chromium-based browser artifacts using Hindsight to extract browsing history, downloads, cookies, cached content, autofill data, saved passwords, and browser extensions from Chrome, Edge, Brave, and Opera for forensic investigation.
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Analyzes malicious VBA macros embedded in Microsoft Office documents (Word, Excel, PowerPoint) to identify download cradles, payload execution, persistence mechanisms, and anti-analysis techniques. Uses olevba, oledump, and VBA deobfuscation to extract the attack chain. Activates for requests involving Office macro analysis, VBA malware investigation, maldoc analysis, or document-based threat examination.
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Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.
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Analyzes malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious document analysis, PDF exploit investigation, or suspicious attachment triage.
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Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.
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Analyzes RAM memory dumps from compromised systems using the Volatility framework to identify malicious processes, injected code, network connections, loaded modules, and extracted credentials. Supports Windows, Linux, and macOS memory forensics. Activates for requests involving memory forensics, RAM analysis, volatile data examination, process injection detection, or memory-resident malware investigation.
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Crawl an existing website (capped, multi-page) and seed stardust/current/ with PRODUCT.md, DESIGN.md, DESIGN.json, a per-page inventory, and the consolidated brand surface.
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Crawl and validate all internal and external links across an AEM Edge Delivery Services site. Uses the query index or sitemap to discover pages, extracts links from .plain.html renditions, checks HTTP status codes, and produces a prioritized report of broken, redirecting, and insecure links. Use when auditing link health before launch, after a migration, or as a periodic maintenance check.
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Audit and optimize headings across AEM Edge Delivery Services pages for search intent, hierarchy, and consistency. Extracts all headings (H1-H6), evaluates uniqueness, keyword alignment, specificity, and structural correctness, then generates optimized heading suggestions per page. Use when improving on-page SEO, fixing heading hierarchy issues, or standardizing heading patterns across a site.
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Orchestrate the migrate-prep cascade — extract --prep → direct --prep → prototype --prep → assets prep — with confirmation gates between phases. Builds the data structure migrate consumes.
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Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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Generate JSON-LD structured data for AEM Edge Delivery Services pages. Analyzes page content and metadata to determine the appropriate schema.org types, extracts relevant properties, and produces validated JSON-LD snippets ready for implementation in head.html or scripts.js. Use when adding rich results support, improving search appearance, or auditing existing structured data.
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Scrape webpage content, extract metadata, download images, and prepare for import/migration to AEM Edge Delivery Services. Returns analysis JSON with paths, metadata, cleaned HTML, and local images.
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Analyze source data, tables, CSV/XLSX extracts, metrics, or experiment results with explicit data-authenticity checks. Use for profiling, cleaning assumptions, statistical summaries, segmentation, trend analysis, or "analyze this data"; do not use for spreadsheet file surgery, chart design only, database migrations, or claims without data provenance.
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Refactors brittle snapshot tests into resilient, focused assertions. Provides strategies for reducing snapshot size, extracting meaningful assertions, and maintaining snapshots. Use for "snapshot testing", "snapshot refactoring", "brittle tests", or "assertion improvement".
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Refactors route handlers into service layer with clean boundaries, dependency injection, testability, and separation of concerns. Provides service interfaces, folder structure, testing strategy, and migration plan. Use when refactoring "fat controllers", "business logic", "service layer", or "architecture cleanup".
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Generates Postman collection JSON files from Express, Next.js, Fastify, Hono, or other API routes. Scans route definitions, extracts endpoints, methods, params, and creates importable collections. Use when users request "generate postman collection", "export to postman", "create postman file", or "postman import".
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Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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Bluetooth Low Energy (BLE) attack methodology — GATT enumeration, characteristic read/write without auth, pairing downgrade (Just Works forced), LE Secure Connections bypass, MITM via active relay, sniffing with Sniffle (TI CC1352) / Ubertooth / Frontline, encryption key extraction (LE Legacy Pairing crackable, LE Secure Connections strong), proximity authentication abuse (cars, locks), and companion-app trust analysis. Use for IoT BLE devices, smart locks, fitness trackers, medical devices, BLE beacons, or any device pairing over BLE.
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IoT and embedded device security testing methodology. Covers hardware reconnaissance (UART, JTAG, SWD, SPI flash, I2C EEPROM, eMMC chip-off), firmware acquisition (vendor portals, OTA capture, flash dump, binwalk extraction), firmware analysis (filesystem mounting, binary triage, hardcoded secrets, default credential discovery), bootloader attacks (U-Boot console, secure-boot bypass, fault injection), runtime attacks on embedded Linux/RTOS (busybox CVEs, MTD writes, /dev/mem), wireless protocol attacks (Zigbee, BLE, Z-Wave, LoRaWAN, Thread/Matter, sub-GHz), MQTT/CoAP/Modbus/BACnet/OPC-UA exploitation, mobile companion app analysis, cloud-IoT API abuse, and side-channel/glitching basics. Use for IoT pentest, smart-home assessment, ICS/OT testing, or embedded vulnerability research.
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JWT attack methodology for penetration testers. Covers algorithm confusion (alg:none, RS256→HS256), weak HMAC secret brute force, kid parameter injection (SQLi, path traversal), jku/x5u/jwk header injection, JWKS cache poisoning, JWS/JWE confusion, timing attacks, and mobile JWT storage extraction. Use when testing JWT-based authentication, hunting auth bypass via token manipulation, or evaluating JWT implementation security in web or mobile apps.
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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.
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You are helping a penetration tester find and extract locally stored credentials on a
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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,...
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