「detecting」の検索結果

This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.

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。

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.

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。

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.

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。

Detecting compromised cloud credentials across AWS, Azure, and GCP by analyzing anomalous API activity, impossible travel patterns, unauthorized resource provisioning, and credential abuse indicators using GuardDuty, Defender for Identity, and SCC Event Threat Detection.

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。

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.

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。

Scans GitHub Actions workflows and CI/CD pipeline configurations for supply chain attack vectors including unpinned actions, script injection via expressions, dependency confusion, and secrets exposure. Uses PyGithub and YAML parsing for automated audit. Use when hardening CI/CD pipelines or investigating compromised build systems.

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 WAF (ModSecurity/AWS WAF/Cloudflare) logs to detect SQL injection attack campaigns. Parses ModSecurity audit logs and JSON WAF event logs to identify SQLi patterns (UNION SELECT, OR 1=1, SLEEP(), BENCHMARK()), tracks attack sources, correlates multi-stage injection attempts, and generates incident reports with OWASP 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。

Detect NTLM relay attacks through Windows Security Event correlation by analyzing Event 4624 LogonType 3 for IP-to-hostname mismatches, identifying Responder/LLMNR poisoning artifacts, auditing SMB and LDAP signing enforcement across the domain, and detecting NTLM downgrade attacks from NTLMv2 to NTLMv1 using event log analysis.

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 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。

This skill covers detecting anomalies in Modbus/TCP and Modbus RTU communications in industrial control systems. It addresses function code monitoring, register range validation, timing analysis, unauthorized client detection, and deep packet inspection for malformed Modbus frames. The skill leverages Zeek with Modbus protocol analyzers, Suricata IDS with OT rules, and custom Python-based detection using Markov chain models for normal Modbus transaction sequences.

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。

Detecting misconfigured Azure Storage accounts including publicly accessible blob containers, missing encryption settings, overly permissive SAS tokens, disabled logging, and network access violations using Azure CLI, PowerShell, and Microsoft Defender for Storage.

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。

Detecting data exfiltration attempts from AWS S3 buckets by analyzing CloudTrail S3 data events, VPC Flow Logs, GuardDuty findings, Amazon Macie alerts, and S3 access patterns to identify unauthorized bulk downloads and cross-account data transfers.

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。

Detecting exposed AWS credentials in source code repositories, CI/CD pipelines, and configuration files using TruffleHog, git-secrets, and AWS-native detection mechanisms to prevent credential theft and unauthorized account access.

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。

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.

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。

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.

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。

Detecting compromised cloud credentials across AWS, Azure, and GCP by analyzing anomalous API activity, impossible travel patterns, unauthorized resource provisioning, and credential abuse indicators using GuardDuty, Defender for Identity, and SCC Event Threat Detection.

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。

This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.

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。

コマンド実行やファイル編集、入力・終了時のイベントを条件で検知し、危険な操作や機密ファイルの変更に警告・ブロックを設定するルールを作るスキル。

• 危険なコマンドをブロックしたいとき
• 機密ファイルの編集に警告したいとき
• 編集時のデバッグコード検知

Creates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph file formats, or drawing network topologies. Common applications include social, biological, transportation, and citation networks.

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。

Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity 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。

Audit MCP (Model Context Protocol) server configurations for security issues. Use this skill when: - Reviewing .mcp.json files for security risks - Checking MCP server args for hardcoded secrets or shell injection patterns - Validating that MCP package-runner dependencies use exact reviewed versions, not bare names, @latest, or ranges - Detecting mutable npm/npx, bunx, pnpm dlx, yarn dlx, and npm exec references in MCP configurations - Auditing which MCP servers a project registers and whether they're on an approved list - Checking for environment variable usage vs. hardcoded credentials in MCP configs - Any request like "is my MCP config secure?", "audit my MCP servers", or "check .mcp.json" keywords: [mcp, security, audit, secrets, shell-injection, supply-chain, governance]

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 git commit with conventional commit message analysis, intelligent staging, and message generation. Use when user asks to commit changes, create a git commit, or mentions "/commit". Supports: (1) Auto-detecting type and scope from changes, (2) Generating conventional commit messages from diff, (3) Interactive commit with optional type/scope/description overrides, (4) Intelligent file staging for logical grouping

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。

Verify supply chain integrity for AI agent plugins, tools, and dependencies. Use this skill when: - Generating SHA-256 integrity manifests for agent plugins or tool packages - Verifying that installed plugins match their published manifests - Detecting tampered, modified, or untracked files in agent tool directories - Auditing dependency pinning and version policies for agent components - Building provenance chains for agent plugin promotion (dev → staging → production) - Any request like "verify plugin integrity", "generate manifest", "check supply chain", or "sign this plugin"

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 process injection techniques (T1055) - including DLL injection, process hollowing, and APC injection - by analyzing Sysmon Event IDs 1, 7, 8, 10, and 25 for cross-process memory operations, remote thread creation, and anomalous DLL loads. Use when hunting defense-evasion activity that hides code inside legitimate processes, investigating an EDR alert on suspicious cross-process access, or validating Sysmon coverage for injection detection.

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。