Skill UI

This comprehensive guide serves as a reference for offensive security professionals developing custom x86/x64 shellcode. It details advanced concepts including Position-Independent Code (PIC), PEB traversal for API resolution, safe memory allocation (avoiding RWX), and sophisticated process injection methods (e.g., APC injection, threadless techniques). Learn how to bypass modern AV/EDR detection using advanced evasion techniques like API hashing, encryption, direct syscalls, and abusing PE structures.

This comprehensive checklist details advanced methods for bypassing Web Application Firewalls (WAFs) during security assessments. Techniques covered include encoding bypass (URL, Unicode, double encoding), HTTP header manipulation, IP rotation, payload obfuscation, and fingerprinting specific WAF vendors (e.g., Cloudflare, Akamai). It is essential for penetration testers evaluating the robustness of web defenses.

A comprehensive guide for optimizing OneNote Graph API interactions at scale. It addresses common performance bottlenecks such as slow data retrieval from large notebooks, handling excessive image sizes, implementing efficient payload selection ($select), and paginating massive data sets using $top. Essential for building stable, high-performance automation workflows.

This skill provides comprehensive functionality for provisioning, managing, and scaling Oracle Cloud Infrastructure (OCI) compute instances using the Python SDK. It addresses common challenges like "out of host capacity" errors by implementing robust retry logic across multiple Availability Domains (ADs). Users can select optimal Flex shapes (AMD, ARM, Intel), manage the entire instance lifecycle (start, stop, reboot, terminate), and retrieve network details, ensuring reliable cloud workload deployment.

This skill provides a comprehensive guide and code examples for designing robust and scalable Identity and Access Management (IAM) structures within Oracle Cloud Infrastructure (OCI). It covers establishing secure compartment hierarchies, understanding complex policy inheritance rules, implementing least-privilege access controls, and utilizing dynamic groups for service authentication, ensuring best practices for enterprise cloud governance.

This skill provides comprehensive techniques for building highly resilient clients when interacting with Oracle Cloud Infrastructure (OCI) APIs. It addresses the common 429 TooManyRequests throttling errors by implementing custom exponential backoff with jitter, utilizing the SDK's advanced retry configuration, and integrating circuit breaker patterns for large-scale, high-volume operations. Use this guide when automating bulk OCI tasks to ensure reliable data retrieval and prevent API failure due to rate limits.

A comprehensive checklist and guide for deploying Persona identity verification features into a production environment. It covers prerequisites, API integration steps using Python examples, error handling (401, 429, 404), and critical post-deployment tasks like compliance review, webhook setup, and monitoring for secure, scalable identity solutions.

This skill provides robust implementation patterns for integrating with the Podium API. It covers core business functionalities such as messaging, review management, and payment processing. By utilizing REST API calls and OAuth2 authentication, developers can establish secure, scalable connections, along with detailed error handling for common issues like expired tokens or rate limiting.

This guide provides the comprehensive reference architecture and implementation patterns for integrating with the Podium REST API. It details secure OAuth2 authentication, covering how to manage core business functions such as messaging, handling customer reviews, and processing payments. Use this when building scalable applications that require deep communication platform connectivity.

A comprehensive guide for diagnosing and reducing high memory consumption in Qdrant. This resource is crucial when dealing with reports of 'memory leak', 'out of memory', or excessive RAM growth. It details how Qdrant manages resident memory and OS page cache, and provides advanced techniques such as quantization, using float16/int8 data types, and strategically storing components on disk (like HNSW indexes or sparse vectors) to minimize the memory footprint and ensure stable, scalable operation.

This mechanism is designed to optimize Qdrant's performance when handling queries with very large limits or when paginating results across multiple shards. Instead of forcing every shard to transfer the full requested limit (which is bandwidth-intensive), it uses Poisson distribution statistics to calculate smaller, optimized limits for each shard. This significantly reduces inter-shard data transfer and improves the efficiency of large-scale vector search, while maintaining a very high degree of accuracy.

This comprehensive guide details advanced strategies for managing time-series data and data retention in vector databases (like Qdrant). It is designed for scenarios where only recent data is relevant (e.g., social media feeds, news articles). Three core methods are presented: Shard Rotation (recommended for natural time boundaries), Collection Rotation (for per-period configuration needs), and Filter-and-Delete (for simple cleanup). The guide also covers hot/cold tiering to optimize performance.