「stat」の検索結果

Animation instrumentation: production-level frame timing, scroll state and ownership conflicts. Use when implementing, reviewing or testing animation instrumentation for React, Vite, Next.js or Perfect_AI projects.

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。

Component design system: production-level tokens, variants, slots, state diagrams. Use when implementing, reviewing or testing component design system for React, Vite, Next.js or Perfect_AI projects.

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。

Production forms: production-level constraints, async status, screen reader errors. Use when implementing, reviewing or testing production forms for React, Vite, Next.js or Perfect_AI projects.

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。

Operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, skill sharing, worktree comments, and Orca's embedded browser through the `orca` CLI. Use when the user says "$orca-cli", "Orca worktree", "child worktree", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "handoff" / "handover" / "give this to another agent", "Orca browser", "orca artifacts", or "share skills". Prefer it over raw git worktree, ad hoc PTYs, or Computer Use when Orca state is involved. Use Computer Use only for external windows or desktop UI that needs OS-level control, and Playwright or CDP for external pages.

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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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This skill covers detecting sophisticated cyber-physical attacks that follow the Stuxnet attack pattern of modifying PLC logic while spoofing sensor readings to hide the manipulation from operators. It addresses PLC logic integrity monitoring, physics-based process anomaly detection, engineering workstation compromise indicators, USB-borne attack vectors, and multi-stage attack chain detection spanning IT-to-OT lateral movement through to process manipulation.

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Detects insider data exfiltration by analyzing DLP policy violations, file access patterns, upload volume anomalies, and off-hours activity in endpoint and cloud logs. Uses pandas for behavioral analytics and statistical baselines. Use when investigating insider threats or building user behavior analytics for data loss prevention.

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 unusual API call patterns in AWS CloudTrail logs using boto3, statistical baselining, and behavioral analysis to identify credential compromise, privilege escalation, and unauthorized resource access.

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Detects anomalous authentication patterns using UEBA analytics, statistical baselines, and machine learning models to identify impossible travel, credential stuffing, brute force, password spraying, and compromised account behaviors across authentication logs. Activates for requests involving authentication anomaly detection, login behavior analysis, UEBA implementation, or suspicious sign-in investigation.

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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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Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.

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Detects command-and-control (C2) communications tunneled through DNS protocol including DNS tunneling tools (Iodine, dnscat2, dns2tcp, Cobalt Strike DNS beacon), domain generation algorithms (DGA), encoded payload delivery via TXT/CNAME records, and DNS beaconing patterns. Covers Shannon entropy analysis of query subdomains, statistical anomaly detection, ML-based DGA classification, passive DNS correlation, and Zeek/Suricata signature development. Activates for requests involving DNS-based C2 detection, DNS tunnel identification, suspicious DNS traffic investigation, or DGA domain classification.

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。

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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Implement Microsoft's Enhanced Security Admin Environment (ESAE) tiered administration model for Active Directory. Covers Tier 0/1/2 separation, privileged access workstations (PAWs), administrative f

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Conducts penetration testing of iOS and Android mobile applications following the OWASP Mobile Application Security Testing Guide (MASTG) to identify vulnerabilities in data storage, network communication, authentication, cryptography, and platform-specific security controls. The tester performs static analysis of application binaries, dynamic analysis at runtime, and API security testing to evaluate the complete mobile attack surface. Activates for requests involving mobile app pentest, iOS security assessment, Android security testing, or OWASP MASTG assessment.

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Parse Apache and Nginx access logs to detect SQL injection attempts, local file inclusion, directory traversal, web scanner fingerprints, and brute-force patterns. Uses regex-based pattern matching against OWASP attack signatures, GeoIP enrichment for source attribution, and statistical anomaly detection for request frequency and response size outliers.

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Analyze the threat landscape using MISP (Malware Information Sharing Platform) by querying event statistics, attribute distributions, threat actor galaxy clusters, and tag trends over time. Uses PyMISP to pull event data, compute IOC type breakdowns, identify top threat actors and malware families, and generate threat landscape reports with temporal trends.

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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。

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing patterns.

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Analyzes malicious Linux ELF (Executable and Linkable Format) binaries including botnets, cryptominers, ransomware, and rootkits targeting Linux servers, containers, and cloud infrastructure. Covers static analysis, dynamic tracing, and reverse engineering of x86_64 and ARM ELF samples. Activates for requests involving Linux malware analysis, ELF binary investigation, Linux server compromise assessment, or container malware analysis.

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Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly detection.

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Perform static and symbolic analysis of Solidity smart contracts using Slither and Mythril to detect reentrancy, integer overflow, access control, and other vulnerability classes before deployment to Ethereum mainnet.

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Analyzes malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious document analysis, PDF exploit investigation, or suspicious attachment triage.

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Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.

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。