Skill UI

This skill performs comprehensive static analysis of Android APK malware. It utilizes industry-standard tools like androguard and apktool to decompile resources, inspect manifests, and identify dangerous permissions, obfuscated code patterns, dynamic loading mechanisms, and suspicious API calls without executing the sample. It is essential for security analysts, SOC teams, and threat hunters building detection rules or triaging suspicious malware samples.

This skill details the process of reverse engineering Go-compiled malware using Ghidra. It involves parsing Go-specific metadata structures like buildinfo and pclntab to recover stripped or obfuscated function names. Users can also extract embedded module paths and dependency strings, providing critical insight into the malware's capabilities and third-party dependencies.

This skill implements the CISA Zero Trust Maturity Model (ZTMM) v2.0. It provides a structured framework to assess, gap-analyze, and roadmap the adoption of zero trust architecture across five core pillars: Identity, Devices, Networks, Applications, and Data. It guides organizations from Traditional to Optimal maturity, aiding compliance with NIST standards and federal mandates.

A comprehensive toolkit for analyzing ELF binaries to locate memory-corruption vulnerabilities, such as buffer overflows and ROP chains. This skill is vital for authorized penetration testing and CTF challenges, allowing users to evaluate compiler mitigations (ASLR, NX, Canary, PIE) and develop robust proof-of-concept exploits.

A structured, multi-phase skill that systematically audits and provides actionable fixes for all four Lighthouse pillars: Performance, Accessibility, Best Practices, and SEO. It analyzes Core Web Vitals, render-blocking resources, security headers, and ARIA compliance to significantly boost site speed and quality.

This guide provides comprehensive best practices for ensuring scientific reproducibility in technical papers, particularly for electronics and information processing fields. It covers the critical pillars of documentation: environment setup, data sourcing and preprocessing, full algorithmic disclosure (including pseudo-code and hyperparameters), and robust statistical evaluation. By adopting these standards, authors can transform their work from potentially unverifiable results into credible, verifiable scientific contributions suitable for top-tier journals.

A comprehensive guide for responding to peer reviews and compiling revision manuscripts for high-impact academic journals, specifically tailored for the Journal on Communications (JOC). It teaches authors how to structure closed-loop responses (Opinion—Response—Location), maintain a professional tone, provide verifiable evidence, and systematically address complex or conflicting critiques throughout the multi-round publication process.

A comprehensive guide for microarchitecture researchers on achieving rigorous scientific reproducibility. It mandates tracking every critical artifact—including simulator commits, workload traces, power/area models, and RTL toolchains—and compiling them into a single run manifest, ensuring any reported result can be verified by a third party.

This guide addresses the stringent requirements for empirical evaluation in compiler and runtime systems, aligning with SIGPLAN's guidelines. It covers critical aspects such as proper warmup discipline, reporting variance and confidence intervals, selecting principled benchmarks, pinning toolchains, and ensuring cross-platform validity. It provides a protocol for generating verifiable measurement logs for academic publications.

This guide outlines the necessary steps to ensure that parallel computing performance papers are scientifically reproducible. Since parallel results depend heavily on machine architecture, topology, and runtime conditions, proper documentation must cover everything from CPU/GPU specifications and interconnects to thread pinning policies, random seeds, and compiler flags. The focus is on proving the scaling trend, not just the absolute numbers, allowing results to hold true across different hardware platforms.

This guide helps researchers determine the correct academic venue for their work in parallel and concurrent computing. It clarifies the scope of PPoPP versus related conferences (CGO, PLDI, ASPLOS, HPCA, POPL, etc.) by asking: 'Is the parallelism the point, or is it the setting?' Use this framework to distinguish contributions focused on parallel algorithms, compiler optimization, concurrency theory, or hardware microarchitecture.

A comprehensive guide for performing reverse engineering using Ghidra. This skill is essential for scenarios where commercial tools like IDA are unavailable, or when performing large-scale, automated headless analysis. It covers the entire workflow, from project setup and function decompilation to advanced headless scripting and integration with other exploit tools.