Skill UI

Security guardrails embedded in the mortgage plugin that block prompt injection and social-engineering tricks, stop system prompt extraction, guard PII and pricing logic, enforce workflow phases, and ensure conversational inputs stay within refinance scope.

A comprehensive collection of six expert-level, structured workflows designed to elevate AI assistance from ad-hoc querying to repeatable, production-grade engineering practices. Users can evaluate prompts, design RAG architectures, plan context budgets, run security audits, build eval harnesses, and coach product strategy.

This comprehensive skill guides users through designing and executing advanced social engineering penetration tests. It covers simulating real-world attacks, including phishing (email), vishing (voice), smishing (SMS), and physical pretexting. The goal is to measure an organization's human security resilience, identify training gaps, and test security controls across multiple vectors using tools like GoPhish and SET.

This skill provides comprehensive guidelines for detecting Business Email Compromise (BEC), a sophisticated fraud scheme. It covers detection techniques using email gateway rules, behavioral analytics, and robust financial process controls. Learn to identify red flags like unusual payment requests, domain mismatches, and patterns of social engineering to protect against financial loss.

This tool automates the extraction of embedded configuration details from Agent Tesla Remote Access Trojan (RAT) samples. It is designed to recover crucial exfiltration credentials (SMTP, FTP, Telegram), keylogger settings, and Command and Control (C2) endpoints by analyzing and deobfuscating the .NET assembly structure. Essential for threat intelligence, incident response, and malware reverse engineering.

This skill guides the implementation of security chaos engineering experiments. It involves deliberately degrading or disabling security controls (like WAF, firewalls, or log pipelines) in a controlled environment to rigorously verify the detection, alerting, and response capabilities of the Security Operations Center (SOC). Users learn to use tools like boto3 and Python to simulate failure scenarios and assess system resilience and compliance posture.

This comprehensive guide details a step-by-step workflow for reverse engineering malware binaries using Ghidra. It guides users through static and dynamic analysis techniques to study internal logic, C2 communication protocols, cryptographic routines, and obfuscation methods at the assembly and pseudo-C code level. Use this when deep code review is required to extract configuration data, understand exploit mechanisms, or develop detection signatures.

A comprehensive deep dive into reverse engineering ransomware encryption mechanisms. It details the analysis of hybrid encryption models (AES/RSA), identifying specific cryptographic APIs (CryptoAPI, CNG), and locating implementation flaws such as weak key generation or IV reuse. This guides authorized security professionals in finding potential decryption opportunities without paying a ransom.

A comprehensive workflow and guide for reverse engineering malware compiled using the Rust language. It specifically addresses complex challenges unique to Rust binaries, including non-null-terminated fat-pointer strings, monomorphization artifacts, and intricate error handling chains (Result/Option). Ideal for security analysts and red teams performing deep analysis of modern, resilient attack artifacts.

This skill acts as an anti-over-engineering guardrail, instructing AI coding agents to maintain strict scope control and minimalism. It guides the AI to only modify the files and lines explicitly requested by the user, avoiding unnecessary abstractions, unrequested refactors, or scope creep. Use it when you prefer the simplest, most direct solution and want to prevent the agent from 'grinding' the code base.

A comprehensive guide to advanced development practices on the Snowflake platform. Covers best practices for SQL (MERGE, semi-structured data, colon prefix rule), modern data pipeline construction (Dynamic Tables, Streams/Tasks, Snowpipe), and deep integration with Cortex AI functions and Snowpark Python. Essential knowledge for data engineers building robust, scalable, and intelligent data applications.

An expert guide for reducing large-scale LLM API costs (40-80%). Learn engineering techniques like model routing, prompt caching, and output length control to make every token count. Essential for engineers building cost-efficient AI features and robust endpoints.