「poi」の検索結果

Use when testing file upload endpoints for unrestricted file upload, MIME type bypass, magic byte spoofing, polyglot files, SVG XSS, XXE via Office documents, ZIP slip, and path traversal in filenames. Trigger on: multipart/form-data endpoints, avatar/document upload flows, import-from-file features, profile image, CSV/Excel import, DOCX/XLSX parsing, image resizing pipelines, archive extraction, and any endpoint that stores or serves user-supplied files. Detects extension bypass (shell.php.jpg), null byte injection, double extension, ImageMagick exploits, and content-type confusion.

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Simulate supply chain and adversarial machine learning attacks by injecting poisoned data or targeted backdoors into training and fine-tuning datasets. Use this skill when assessing the integrity controls of MLOps pipelines or evaluating the resilience of AI models against highly targeted, stealthy manipulation intended to alter model behavior on specific triggers.

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White-box source code security review structured around OWASP ASVS 5.0 (427 verification requirements across 16 chapters). Reads and understands application source code to build a security-aware knowledge base that enriches all downstream skills. Covers: tech stack identification, route/endpoint mapping, authentication and authorization architecture, dangerous function patterns, source-to-sink data flow tracing, IaC review, dependency analysis, ASVS compliance mapping, and LLM integration security (prompt injection, tool abuse, output handling, RAG poisoning, MCP server patterns). When LLM/AI framework usage is detected, automatically reviews OWASP LLM Top 10 patterns from source code and chains into /ai-redteam with white-box context for live endpoint testing. Chains into /pentester, /threat-modeling, /web-exploit, /api-security, /cloud-security, /analyze-cve, /credential-audit, and /ai-redteam — providing white-box context that transforms black-box testing into targeted, informed assessment.

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Execute and analyze AI Data Poisoning attacks. By subtly injecting malicious or targeted misinformation into an LLM's training or fine-tuning dataset, an attacker can covertly manipulate the model's future outputs, implant backdoors, or enforce biases without altering the model architecture.

日本語の概要は準備中です。原文の説明を表示しています。

Backend specification planning frameworks. Use when a spec touches API endpoints, database schema, middleware, or auth. Covers endpoint contracts with request/response shapes, error catalogs, auth per endpoint, schema design with constraints and indexes, migration strategy, and middleware pipeline ordering.

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Uses x64dbg to dynamically debug Windows malware: setting strategic breakpoints on APIs, stepping through unpacking and decryption, dumping memory at the right moment, and manipulating execution to reach hidden code. Activates for requests to debug malware with x64dbg, set API breakpoints, or step through unpacking in a debugger.

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Maps the entire API surface of a codebase -- route definitions, middleware chains, auth requirements, request/response types, deprecated endpoints, orphaned endpoints, and cross-endpoint inconsistencies..

日本語の概要は準備中です。原文の説明を表示しています。

Manages GenAI tuning jobs in Agent Platform. Use this to list, get, or cancel ongoing model tuning jobs. Don't use for fine-tuning models (use `agent-platform-tuning`), deploying models to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-management`).

日本語の概要は準備中です。原文の説明を表示しています。

Agent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-management`).

日本語の概要は準備中です。原文の説明を表示しています。

Use when configuring Workflow-based Outbound Messages to push SOAP payloads to external endpoints — endpoint setup, field selection, retry behavior, and delivery monitoring. NOT for the listener's session ID callback into Salesforce — use integration/outbound-messages-and-callbacks. NOT for JSON webhooks or Flow-triggered pushes — use integration/outbound-webhook-from-salesforce. Keywords: WorkflowOutboundMessage, outboundMessages, endpointUrl, includeSessionId, integrationUser, useDeadLetterQueue, apiVersion, SOAP Ack, .workflow file, approval outbound message action.

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Use this skill to select the right Salesforce integration pattern — from point-to-point to event-driven to hub-and-spoke — by applying the official Salesforce two-axis decision framework (integration type × timing) to a business integration scenario. Trigger keywords: integration pattern decision, choose integration approach, Salesforce integration architecture, when to use platform events vs API, integration type selection. NOT for implementation of any specific integration pattern (use domain-specific integration skills), MuleSoft architecture (use architect/mulesoft-anypoint-architecture), or middleware vendor selection. More triggers: integration decision record, Bulk API vs REST for a nightly load, external Id upsert, Named Credential vs Remote Site Setting, platform event vs CDC, who calls whom.

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Configure and manage Field Service Lightning work orders: work types, work order line items, service appointments, status flow, and auto-creation via maintenance plans. NOT for choosing which technician gets the appointment (work rules, scheduling policies) — use admin/fsl-scheduling-policies. NOT for setting up the technicians, their skills or capacity — use admin/fsl-resource-management.

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Work with Runpod GPU infrastructure and documentation. Use when Codex needs to create, deploy, manage, debug, or review Runpod Pods, Serverless workers/endpoints, templates, network volumes, Public Endpoints, Flash apps, runpodctl commands, Runpod Python SDK usage, REST/GraphQL API usage, Runpod MCP setup, Docker images for Runpod, endpoint request payloads, logs, billing/cost checks, or Runpod deployment troubleshooting.

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Heuristic story-point estimation for a single Jira ticket via the jira-estimator agent. Read-only. Triggers: 'estimate KEY', 'story points for KEY', 'how complex is KEY'. NOT for complexity-only analysis (mk:jira-evaluator); NOT for full RCA (mk:jira-analyst).

日本語の概要は準備中です。原文の説明を表示しています。

JIRA agile via the jira-as wrapper: epics, sprints, backlog, ranking, story points, subtasks, velocity. Triggers: 'create sprint', 'add KEY to sprint', 'set story points on KEY', 'rank KEY before KEY', 'velocity for board', 'epic add'. Board ID ≠ project key. NOT for issue CRUD (mk:jira-issue); NOT for time tracking (mk:jira-time).

日本語の概要は準備中です。原文の説明を表示しています。

Use when creating an API endpoint or HTTP route handler — detects the project stack and routes to the matching carve-out (laravel-api-endpoint, nextjs-patterns, symfony-workflow).

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[Utilities] Use when you need to save analysis context to a checkpoint file for recovery (user-facing alias for memory-management Part 1 CHECKPOINT_CREATE).

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Detects and prevents code injection attacks targeting serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions) through event source poisoning, malicious layer injection, runtime command execution, and IAM privilege escalation via function modification. The analyst combines static analysis of function code, CloudTrail event correlation, runtime behavior monitoring, and IAM policy auditing to identify injection vectors across the expanded serverless attack surface including API Gateway, S3, SQS, DynamoDB Streams, and CloudWatch event triggers. Activates for requests involving Lambda security assessment, serverless injection detection, function event poisoning analysis, or serverless privilege escalation investigation.

日本語の概要は準備中です。原文の説明を表示しています。

Identify poisoned training data and backdoored models across the ML pipeline.

日本語の概要は準備中です。原文の説明を表示しています。

Configures host-based intrusion detection systems (HIDS) to monitor endpoint file integrity, system calls, and configuration changes for security violations. Use when deploying OSSEC, Wazuh, or AIDE for endpoint monitoring, building file integrity monitoring (FIM) policies, or meeting compliance requirements for change detection. Activates for requests involving HIDS configuration, file integrity monitoring, OSSEC/Wazuh deployment, or host-based detection.

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Responds to malware infections across enterprise endpoints by identifying the malware family, determining infection vectors, assessing spread, and executing eradication procedures. Covers the full lifecycle from detection through containment, analysis, removal, and recovery. Activates for requests involving malware response, malware eradication, trojan removal, worm containment, malware triage, or infected endpoint remediation.

日本語の概要は準備中です。原文の説明を表示しています。

Scan Model Context Protocol servers and tool metadata for poisoning, SSRF, and unauthenticated exposure.

日本語の概要は準備中です。原文の説明を表示しています。

Location, restaurant and hotel search via OpenStreetMap (Nominatim + Overpass API). Returns POIs (Points of Interest) near a location or searches by free text.

日本語の概要は準備中です。原文の説明を表示しています。

Use the WooCommerce REST API v4 (namespace wc/v4, since WC 10.2) alongside or in place of v3 — verified route catalog (Customers, Orders, Refunds, Products, ShippingZones with DELETE, ShippingZoneMethod, Fulfillments, segmented Settings under /wc/v4/settings/<group>), the hook prefix pattern woocommerce_rest_api_v4_<route>_*, shared error codes, and the RestApiCache trait (WC 10.5+) for endpoint response caching. The v4 AbstractController lives under the Internal namespace and is NOT a public extension surface; plugin-defined REST routes use WP_REST_Controller directly. Use when calling WC REST endpoints, when picking v3 vs v4, or when reviewing /wc/v3/ URLs that now have v4 equivalents. Triggers on wc/v4, /wc/v4/, woocommerce_rest_api_v4_*, RestApiCache, customer-owned Woo endpoints, REST API v4 in WooCommerce context.

日本語の概要は準備中です。原文の説明を表示しています。