「time」の検索結果

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for CI/CD, registry, dependency drift, artifact provenance, image build, release pipeline, and runtime consumer challenges. Use when the user asks to trace dependency drift, registry pulls, malicious packages, build or release tampering, CI execution, artifact signing, or which shipped artifact the runtime actually consumes. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Reverse JavaScript-based custom DSL/VM interpreters, non-standard WASM-like runtimes, and risk-control engines. Use when analyzing IIFE or switch-based opcode dispatchers, extracting instruction tables, recovering bytecode semantics, capturing VM state at runtime, or reconstructing execution flow.

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。

Python resilience patterns including automatic retries, exponential backoff, timeouts, and fault-tolerant decorators. Use when adding retry logic, implementing timeouts, building fault-tolerant services, or handling transient failures.

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。

Execute database migrations across ORMs and platforms with zero-downtime strategies, data transformation, and rollback procedures. Use when migrating databases, changing schemas, performing data transformations, or implementing zero-downtime deployment strategies.

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。

Upgrade GitHub Actions to supported runtimes by selecting safe action versions, preserving workflow behavior, and validating post-upgrade execution.

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 the PROVIDER half of getting a locally running CopilotKit Channels agent to answer in Slack, when no Slack app exists yet — setting up a Channels bot in Slack for the first time, creating the Slack app and its tokens, attaching it to a managed Intelligence Channel, or when a Channel reports setup_required, sits at "Waiting for runtime", the Channel is Online but a Slack mention gets no reply, or a Slack app was built with Socket Mode instead of an Intelligence Request URL. Scoped to an OpenTag checkout, or the OpenTag example inside a channels-sdk clone — the phases assume those conventions (app/channel.tsx, app/env.ts, INTELLIGENCE_CHANNEL_NAME, a local agent on port 8123) and do not describe a project scaffolded by copilotkit init, which already ships its own channel host. If the Slack app and Channel already exist and the question is about declaring or customising the Channel in code, use the copilotkit-channels skill instead.

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。

Detects ransomware encryption activity in real time using entropy analysis, file system I/O monitoring (Sysmon, watchdog, psutil), and behavioral scoring to identify mass file modification, abnormal entropy spikes in written data, and suspicious process behavior characteristic of encryption routines. Use when building real-time ransomware detection, tuning entropy thresholds, or investigating suspected active encryption on an endpoint.

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。

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。

Writes and tunes Falco rule syntax for container escape detection - conditions, macros, lists, priorities, and output fields - covering host filesystem mounts, sensitive host path access, kernel module loading, and privileged capability abuse, including how to drive down false positives. Use when authoring or tuning a specific Falco rule for breakout behaviour, or triaging a noisy escape-related Falco alert. Keywords: Falco rule, macro, list, condition, priority, falco_rules.local.yaml, tuning, false positive. Do not use for deploying and operating Falco itself - use detecting-container-runtime-threats-with-falco; for tool-agnostic escape signals use detecting-container-escape-attempts.

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。

Deploy and operationalize Amazon GuardDuty, covering protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity, and building automated response with EventBridge and Lambda. Use when establishing threat detection for AWS accounts, investigating findings on compromised instances or credential abuse, or building automated incident-response playbooks.

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。

Build automated AWS GuardDuty finding response pipelines using EventBridge and Lambda to trigger real-time incident response, automatically quarantine compromised resources, and route security notifications. Use when designing automated remediation playbooks for GuardDuty findings across VPC Flow Logs, CloudTrail, DNS, EKS, or S3 data events, or when reducing mean time to respond to cloud threats.

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。

Implement a vulnerability aging dashboard and SLA tracking system that measures time-to-remediation against severity-based deadlines (e.g. 14 days critical, 30 days high, 60 days medium, 90 days low), with automated escalations and compliance metrics reporting. Use when designing SLA policies, building aging/remediation dashboards, or proving compliance with remediation timelines.

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。

Builds SOC performance metrics and KPI tracking dashboards measuring Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), alert quality ratios, analyst productivity, and detection coverage using SIEM data. Use when SOC leadership needs operational visibility, continuous improvement tracking, or executive-level reporting on security operations effectiveness.

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。

Builds real-time incident response dashboards in Splunk, Elastic, or Grafana to provide SOC analysts and leadership with situational awareness during active incidents, tracking affected systems, containment status, IOC spread, and response timeline. Use when IR teams need unified visibility during incident coordination and post-incident reporting.

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。

Correlate Windows registry keys (USBSTOR, MountedDevices), Event Logs, and setupapi.dev.log to reconstruct USB device connection history, first/last-plugged timestamps, and drive letter mappings. Use when investigating removable media usage, tracking device provenance, or building a timeline for suspected data exfiltration.

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。

Runtime iOS app security testing with Objection (Frida): inspect keychain and filesystem data, explore app internals at runtime, and validate/bypass client-side protections during authorized mobile assessments.

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。

Investigate compromised Docker containers by analyzing images, layers, volumes, logs, and runtime artifacts to identify malicious activity and evidence.

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。

Analyze the NTFS Master File Table ($MFT) with MFTECmd, analyzeMFT, and X-Ways Forensics to recover metadata and content of deleted files by examining MFT record entries, $LogFile, $UsnJrnl, and MFT slack space. Use when recovering evidence of deleted files, reconstructing NTFS file-system timelines, or detecting anti-forensic timestomping during a Windows forensic 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。

Internal helper contract for calling the codex-companion runtime from Claude Code

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。

NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filtering, toxicity detection. Uses Colang 2.0 DSL for programmable rails. Production-ready, runs on T4 GPU.

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。

Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B - collaborative MLOps platform

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 recurring focus time blocks on Google Calendar to protect deep work hours.

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。

Run initial NanoClaw setup. Use when user wants to install NanoClaw, configure it, or go through first-time setup. Triggers on "setup", "install", "configure nanoclaw", or first-time setup requests.

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。

Save and load timestamped reports. Keyword routing for fast lookup. Cron jobs save output as reports; the agent or user queries them by keyword. Includes the Actionability Gate: delivery-time link checks (Broken/Dead/Indirect/ Missing) for briefings, meeting digests, and research reports.

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。