4K skills · sorted by relevance
Installs, configures, and tunes Snort 3 intrusion detection system to monitor network traffic for malicious activity using custom and community rulesets, preprocessors, and alert output plugins on authorized network segments.
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This skill covers detecting cyber attacks targeting Supervisory Control and Data Acquisition (SCADA) systems including man-in-the-middle attacks on industrial protocols, unauthorized command injection into PLCs, HMI compromise, historian data manipulation, and denial-of-service against control system communications. It leverages OT-specific intrusion detection systems, industrial protocol anomaly detection, and process data analytics to identify attacks that traditional IT security tools miss.
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Deploys and configures osquery for real-time endpoint monitoring using SQL-based queries to inspect running processes, open ports, installed software, and system configuration. Use when building visibility into endpoint state, threat hunting across fleet, or implementing compliance monitoring. Activates for requests involving osquery deployment, endpoint visibility, fleet management, or SQL-based endpoint querying.
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Configures Windows Event Logging with advanced audit policies to generate high-fidelity security events for threat detection and forensic investigation. Use when enabling audit policies for logon events, process creation, privilege use, and object access to feed SIEM detection rules. Activates for requests involving Windows audit policy, event log configuration, security logging, or detection-oriented logging.
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Builds a structured vulnerability scanning workflow using tools like Nessus, Qualys, and OpenVAS to discover, prioritize, and track remediation of security vulnerabilities across infrastructure. Use when SOC teams need to establish recurring vulnerability assessment processes, integrate scan results with SIEM alerting, and build remediation tracking dashboards.
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Facilitate structured post-incident reviews to identify root causes, document what worked and failed, and produce actionable recommendations to improve future incident response.
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Collect volatile forensic evidence from a compromised system following order of volatility, preserving memory, network connections, processes, and system state before they are lost.
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Leverages Splunk Enterprise Security and SPL (Search Processing Language) to investigate security incidents through log correlation, timeline reconstruction, and anomaly detection. Covers Windows event logs, firewall logs, proxy logs, and authentication data analysis. Activates for requests involving Splunk investigation, SPL queries, SIEM log analysis, security event correlation, or log-based incident investigation.
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Build effective detection rules using Splunk Search Processing Language (SPL) correlation searches to identify security threats in SOC environments.
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Executes malware samples in Cuckoo Sandbox to observe runtime behavior including process creation, file system modifications, registry changes, network communications, and API calls. Generates comprehensive behavioral reports for malware classification and IOC extraction. Activates for requests involving dynamic malware analysis, sandbox detonation, behavioral analysis, or automated malware execution.
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Performs Linux memory acquisition using LiME (Linux Memory Extractor) kernel module and analysis with Volatility 3 framework. Extracts process lists, network connections, bash history, loaded kernel modules, and injected code from Linux memory images. Use when performing incident response on compromised Linux systems.
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Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.
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[BETA] Implement custom AEM Workflow Java components on AEM as a Cloud Service. This skill is in beta. Verify all outputs before applying them to production projects. Use when writing WorkflowProcess steps, ParticipantStepChooser implementations, registering services via OSGi DS R6 annotations, reading step arguments from MetaDataMap, accessing JCR payload via WorkflowSession adapter, reading and writing workflow metadata and variables, and handling errors with WorkflowException for retry behavior.
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Design and create AEM Workflow models on AEM as a Cloud Service. Use when creating workflow models via the Workflow Model Editor or content package XML, defining step types (PROCESS, PARTICIPANT, DYNAMIC_PARTICIPANT, OR_SPLIT, AND_SPLIT), configuring step properties, declaring workflow variables, and deploying models through the Cloud Manager pipeline.
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Publish, deactivate, and delete AEM content programmatically via the Cloud Service Replication API (com.day.cq.replication). Covers single-path and bulk activation, preview-tier targeting with AgentFilter, synchronous/async options, ReplicationStatus checks, permission validation, workflow process steps, and replication event handling. Use when the user needs to publish pages, activate or deactivate content, check replication status, build workflow steps that replicate content, listen to replication events, query batch publication state, or work with Replicator, ReplicationOptions, or ReplicationStatusProvider in AEM Cloud Service.
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Apply a Content Driven Development process to AEM Edge Delivery Services development. Use for ALL code changes - new blocks, block modifications, CSS styling, bug fixes, core functionality (scripts.js, styles, etc.), or any JavaScript/CSS work that needs validation.
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Set up CI/CD pipelines for Adobe App Builder projects. Generates GitHub Actions workflows using adobe/aio-cli-setup-action@3 and adobe/aio-apps-action@3.3.0, plus patterns for Azure DevOps and GitLab CI. Handles OAuth S2S secrets injection, multi-workspace promotion (stage → prod), deploy gating with manifest validation. Use this skill whenever the user mentions CI/CD for App Builder, GitHub Actions for aio deploy, automated deployment pipelines, continuous integration, continuous delivery, deploy automation, multi-environment promotion, aio app add ci, or wants to automate their App Builder build and release process. Also trigger when users mention deploy workflows, release pipelines, or GitHub secrets for App Builder.
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AEM Cloud Service expert skill for the Asset Manager API (com.day.cq.dam.api.AssetManager). Covers two migration paths — Path A (create/upload, replacing createAssetForBinary/getAssetForBinary/client-facing createAsset with Direct Binary Access via @adobe/aem-upload) and Path B (delete, replacing removeAssetForBinary with in-JVM resolver.delete() + commit or external HTTP Assets API with IMS bearer tokens). Covers IMS authentication, service-user setup with crx delete permissions, asset processing pipeline, common pitfalls (hardcoded credentials, AEM calling its own HTTP API), and composition with replication/event-migration skills.
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Single entry point for all AEM as a Cloud Service Workflow skills. Covers workflow model design, custom process step and participant chooser development, launcher configuration, workflow triggering, and production support including debugging stuck/failed workflows, triaging incidents with Cloud Manager logs, thread pool analysis, and Sling Job diagnostics for the Granite Workflow Engine.
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Handle an explicit Git intent such as branch/worktree setup, commit organization, history archaeology, conflict resolution, PR preparation, or versioning; do not trigger as a process skill for every code or file change.
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Converts documents into clean, chunked datasets suitable for embeddings and vector search. Produces chunked JSONL files with metadata, deduplication logic, and quality checks. Use when preparing "training data", "vector datasets", "document processing", or "embedding data".
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Establishes git workflow guardrails including conventional commits, commit message hooks, branch naming conventions, PR templates, and code review processes. Provides hook configurations, workflow templates, and emergency bypass instructions. Use when users request "setup git hooks", "enforce commit conventions", "add PR templates", or "standardize git workflow".
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Builds document embedding pipelines with text chunking, embedding generation, indexing, and retrieval optimization. Use when users request "embedding pipeline", "document indexing", "text chunking", "RAG preprocessing", or "semantic indexing".
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Builds multi-step forms with validation schemas (Zod/Yup), step components, shared state management, progress indicators, review steps, and error handling. Use when creating "multi-step forms", "wizard flows", "onboarding forms", or "checkout processes".
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