「execution」の検索結果

Complete guide for TUnit new-generation testing framework. Use when creating test projects with TUnit or migrating from xUnit to TUnit. Covers Source Generator driven test discovery, AOT compilation support, fluent async assertions. Includes project creation, [Test] attribute, lifecycle management, parallel control, and xUnit syntax comparison. Keywords: TUnit, tunit testing, source generator testing, AOT testing, new generation testing framework, [Test], [Arguments], TUnit.Assertions, Assert.That, Before(Test), After(Test), NotInParallel, TUnit.Templates, Microsoft.Testing.Platform, TUnit vs xUnit, parallel execution

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Build a minimal context pack and recommend the correct specialist path for token-efficient execution. Use when the task is non-trivial, spans multiple domains, or should reduce token usage before implementation.

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。

Plan and sequence complex implementation work into deterministic, testable steps. Use when the user asks for planning, roadmap breakdown, execution strategy, effort estimation, or multi-step delivery coordination across domains.

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。

Route tasks using the repository's static routing catalog and load only the minimal context pack. Use before execution when the task spans multiple domains or the correct instruction set is unclear.

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 for non-trivial feature, behavior, workflow, or architecture work before execution planning. Create or update a versioned spec under planning/specs/active with design intent, alternatives, risks, acceptance criteria, and planning readiness.

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 for non-trivial, design-bearing, or architecture-affecting work before execution planning. Creates or updates a versioned spec under planning/specs/active/ with design intent, alternatives, risks, and acceptance criteria.

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。

Plan and sequence complex implementation work into deterministic, testable steps for this repository. Use when the user asks for planning, roadmap breakdown, execution strategy, effort estimation, or multi-step delivery coordination across domains.

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 as the single visible starter and controller for workspace work that may change files, runtime assets, planning state, docs, settings, or governance. Normalize the request into the Super Agent lifecycle: intake, spec registration for non-trivial work, planning registration, specialist routing, execution, testing, review, closeout, and planning-state updates before implementation begins.

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。

Create or update active planning documents under `planning/active`, then define the execution slices, validations, specialist handoff, and closeout expectations. Use when the task is non-trivial, multi-step, or explicitly asks for planning.

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。

Identifying and exploiting insecure deserialization vulnerabilities in Java, PHP, Python, and .NET applications to achieve remote code execution during authorized penetration tests.

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Identifies and exploits SQL injection vulnerabilities in web applications during authorized penetration tests using manual techniques and automated tools like sqlmap. The tester detects injection points through error-based, union-based, blind boolean, and time-based blind techniques across all major database engines (MySQL, PostgreSQL, MSSQL, Oracle) to demonstrate data extraction, authentication bypass, and potential remote code execution. Activates for requests involving SQL injection testing, SQLi exploitation, database security assessment, or injection vulnerability verification.

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Detecting and exploiting Server-Side Template Injection (SSTI) vulnerabilities across Jinja2, Twig, Freemarker, and other template engines to achieve remote code execution.

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Detect abuse of legitimate Windows binaries (LOLBins) used for living off the land attacks. Monitors process creation, command-line arguments, and parent-child relationships to identify suspicious LOLBin execution patterns.

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Detect DLL side-loading attacks where adversaries place malicious DLLs alongside legitimate applications to hijack execution flow for defense evasion.

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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.

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Detect lateral movement in network traffic using Zeek (formerly Bro) log analysis. Parses conn.log, smb_mapping.log, smb_files.log, dce_rpc.log, kerberos.log, and ntlm.log to identify SMB file transfers, NTLM account spray activity, remote service execution, and anomalous internal connections.

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。

Detect unauthorized modifications to running containers by monitoring for binary execution drift, file system changes, and configuration deviations from the original container image.

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Performs memory forensics analysis using Volatility 3 to extract evidence of malware execution, process injection, network connections, and credential theft from RAM dumps captured during incident response. Covers memory acquisition, process analysis, DLL inspection, and malware detection. Activates for requests involving memory forensics, RAM analysis, Volatility framework, memory dump investigation, volatile evidence analysis, or live memory acquisition.

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Analyzes network traffic generated by malware during sandbox execution or live incident response to identify C2 protocols, data exfiltration channels, payload downloads, and lateral movement patterns using Wireshark, Zeek, and Suricata. Activates for requests involving malware network analysis, C2 traffic decoding, malware PCAP analysis, or network-based malware detection.

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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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Analyzes malicious VBA macros embedded in Microsoft Office documents (Word, Excel, PowerPoint) to identify download cradles, payload execution, persistence mechanisms, and anti-analysis techniques. Uses olevba, oledump, and VBA deobfuscation to extract the attack chain. Activates for requests involving Office macro analysis, VBA malware investigation, maldoc analysis, or document-based threat examination.

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。

AEM Cloud Service expert skill for OSGi Event Admin handlers (non-resource events). Covers migration of javax.jcr.observation.EventListener (residual non-resource cases) and OSGi EventHandler with inline business logic to the lightweight EventHandler + JobConsumer split. Includes routing rules (resource events go to resource-change-listener, external notification goes to AEM Eventing), TopologyEventListener for leader-only execution, replication and workflow event patterns, service-user setup, review checklist, troubleshooting, and common pitfalls.

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Generate or materially revise a repository-local test plan, QA plan, acceptance matrix, or regression checklist on explicit request or when one concrete testability gap blocks formal DEFINE; do not trigger for ordinary implementation, test execution, TDD, review, or completion claims.

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Optimizes CI pipelines for monorepos by detecting affected packages/apps and running only necessary builds and tests. Includes Turborepo/Nx strategies, caching, and parallel execution. Use for "monorepo CI", "affected detection", "incremental builds", or "workspace optimization".

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。