Skill UI

An expert playbook detailing DNS rebinding techniques to bypass the Same-Origin Policy (SOP). This method is used in penetration testing to exploit client-side applications that rely on DNS resolution for origin checks, allowing attackers to trick the browser into sending requests to internal, non-publicly accessible services (like cloud metadata endpoints) while maintaining a seemingly trusted origin.

A comprehensive playbook detailing advanced techniques for attacking Kubernetes clusters. Covers API server access, RBAC privilege escalation, service account token abuse, etcd secrets extraction, Kubelet exploitation, and various container escapes. This guide is essential for security professionals and red teams performing deep security assessments on cloud-native infrastructure.

This skill provides an end-to-end solution to transform existing REST APIs, defined by OpenAPI or Swagger specifications, into functional MCP servers. It maps every API operation to a dedicated, callable LLM tool, automatically generating robust parameter schemas (Zod) and handling authentication wiring. Use this to expose internal or third-party APIs to LLMs, providing a complete workflow from spec ingestion to local testing and cloud deployment.

Stratus Red Team is an open-source tool designed for detection engineering and purple teaming. It programmatically detonates granular, documented offensive techniques across major cloud platforms (AWS, Azure, GCP, and Kubernetes). It validates existing security detections (like CloudTrail/GuardDuty) by simulating real attacker activity in a controlled, reversible environment. The tool ensures deterministic lifecycles, guaranteeing that all created resources are cleaned up after testing.

CloudFox is an open-source, attacker-centric tool designed for authorized cloud penetration testing. It maps attack paths and identifies exploitable misconfigurations across AWS and Azure environments. By simulating an attacker's perspective, it goes beyond simple configuration audits to reveal critical assets, exposed secrets, and lateral movement opportunities (like STS AssumeRole trust relationships), providing comprehensive situational awareness for security assessment.

Pacu is an open-source, modular AWS exploitation framework designed for authorized cloud penetration testing and red-teaming. It functions as a cloud-pentest analogue to Metasploit, enabling users to enumerate AWS resources, scan for privilege escalation paths, and automate the exploitation of IAM vulnerabilities, persistence mechanisms, and data exfiltration. Use this skill to assess the blast radius of compromised credentials in a controlled, authorized environment.

This skill generates robust, production-grade Appium automation scripts for both Android and iOS. It supports multiple languages (Java, Python, JavaScript) and guides users through best practices for cross-platform testing, including proper locator strategies, explicit waiting, and complex gestures. Ideal for automating mobile QA processes on local emulators or cloud real device farms.

This skill generates robust, production-grade End-to-End (E2E) and Component tests using the Cypress framework in JavaScript or TypeScript. It supports local execution and cloud testing environments. Use this skill when you need to write Cypress test cases, set up the Cypress environment, or utilize core commands like `cy.get`, `cy.visit`, and `cy.intercept` for functional validation.

This skill manages the end-to-end lifecycle of cloud test execution using HyperExecute for platforms like LambdaTest/TestMu AI. It provides comprehensive functionality to analyze projects, generate and validate complex YAML configurations, run CLI jobs, and debug failures. Ideal for integrating robust, scalable, and matrix-based testing into CI/CD pipelines.

This skill generates comprehensive visual regression test configurations using SmartUI for accurate screenshot comparison on cloud platforms. It is framework-agnostic, supporting major tools like Playwright, Selenium, Cypress, and Puppeteer. Use it when detecting UI changes, ensuring visual consistency, or running automated visual tests across multiple viewports and browsers.

Dispatches computationally intensive quantitative financial jobs (such as multi-year walk-forward backtesting, large Monte-Carlo simulations, parameter sweeps, and deep model training using neural-trader) to a managed cloud agent. This is necessary for workloads that exceed local computational limits, providing robust, scalable infrastructure for professional quantitative research.