Skill UI

A comprehensive operational runbook for managing outages and errors related to Mistral AI integrations. It provides structured procedures, including severity classification, quick API health checks, decision trees for common errors (401, 429, 5xx), immediate mitigation steps, and post-incident evidence collection and reporting.

This skill analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain framework. It identifies which attack phases an adversary has completed, points where defenses failed or succeeded, and recommends controls to disrupt the attack at earlier stages. It is essential for post-incident analysis, threat intelligence reporting, and designing robust defense-in-depth strategies.

This guide details the end-to-end process of conducting a sophisticated spearphishing simulation campaign, mirroring real red team adversary techniques. It covers initial OSINT research and pretext development, building weaponized payloads that bypass security controls, setting up robust email infrastructure (SPF/DKIM/DMARC), executing the campaign in waves, and performing detailed post-campaign metrics analysis for comprehensive security reporting.

Deploy SailPoint IdentityNow or IdentityIQ to establish robust identity governance and access administration. This comprehensive solution manages the entire identity lifecycle, facilitates access request workflows, conducts certification campaigns, performs role mining, and enforces Separation of Duties (SOD) policies, ensuring continuous compliance reporting for enterprise IAM environments.

A comprehensive guide detailing the use of Tenable Nessus, an industry-leading vulnerability scanner. Learn how to configure advanced scan policies, perform both authenticated and unauthenticated scans across servers, network devices, and web applications. This skill covers end-to-end processes from execution to result analysis and reporting.

A comprehensive guide detailing the workflow for firmware reverse engineering. It uses tools like binwalk to identify embedded filesystems (e.g., SquashFS, CramFS), perform entropy analysis to locate hidden data, and extract components. The process covers deep inspection, credential discovery, and reporting for IoT and embedded security assessments.

This comprehensive guide provides rigorous standards for advanced materials manuscripts. It mandates that structure–property claims must be validated through multiple, complementary characterization techniques (triangulation). It also details best practices for benchmarking against the state-of-the-art, ensuring reproducibility, and correctly partitioning core information between the main text and supplementary materials.

This guide provides expert principles for designing and auditing system-level experiments in computer architecture (e.g., for ASPLOS-level conferences). It details the proper usage of various instruments—from real silicon and FPGAs to cycle-level simulators and analytical models—ensuring that every claim is matched to a valid, stated error model. It emphasizes workload selection, establishing strong baselines, performing rigorous ablation studies, and honestly reporting measurement noise and limitations to maintain scientific credibility.

This guide outlines the rigorous standards for evaluating systems research, particularly for top-tier conferences like ATC. It provides detailed instructions on designing reproducible experiments, establishing fair baselines, utilizing realistic workloads, and reporting critical metrics such as tail latency, variance, and resource cost, ensuring the highest level of scientific rigor.

Provides rigorous guidelines for conducting robust, verifiable, and reproducible evaluations in networking research. It emphasizes moving beyond simple simulations by demanding the use of real target platforms, documenting full system provenance (traces and configs), establishing honestly tuned baselines, and reporting detailed measurement statistics and uncertainty. Essential for authors aiming for top-tier conference submissions.

This guide provides a comprehensive checklist for evaluating Electronic Design Automation (EDA) research manuscripts for top-tier conferences like DAC. It emphasizes the necessity of using standard, recognized benchmark suites (e.g., ISPD, EPFL, TAU), comparing results against the true State-of-the-Art (SOTA), reporting full PPA metrics and runtime, and implementing ablation studies to ensure fairness, reproducibility, and generalizability, especially for ML-based methods.

This guide provides comprehensive standards for designing, auditing, and reporting empirical evaluations in database systems research. It emphasizes the principle that evidence must proportionally match the claim, requiring the use of real-world workloads, fair and tuned baselines, thorough measurement of variance and state (warm/cold), and fully reproducible evaluation harnesses. It also outlines the higher bar for 'Experiments & Analysis' papers.