インフラ・DevOpsのスキル

Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.

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 command injection attacks against Modbus TCP/RTU protocol in ICS environments by monitoring for unauthorized write operations, anomalous function codes, malformed frames, and deviations from established communication baselines using ICS-aware IDS and protocol deep packet inspection.

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Detect anomalies in DNP3 (Distributed Network Protocol 3) communications used in SCADA systems by monitoring for unauthorized control commands, firmware update attempts, protocol violations, and deviations from baseline traffic patterns using deep packet inspection and machine learning approaches.

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Detect unauthorized SaaS and cloud service usage (shadow IT) by analyzing proxy logs, DNS query logs, and netflow data using Python pandas for traffic pattern analysis and domain classification.

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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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Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests targeting service accounts with SPNs for offline password cracking.

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Deploys deception-based honeytokens in Active Directory including fake privileged accounts with AdminCount=1, fake SPNs for Kerberoasting detection (honeyroasting), decoy GPOs with cpassword traps, and fake BloodHound paths. Monitors Windows Security Event IDs 4769, 4625, 4662, 5136 for honeytoken interaction. Use when implementing AD deception defenses for detecting lateral movement, credential theft, and reconnaissance.

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Deploys and configures CrowdStrike Falcon EDR agents across enterprise endpoints to enable real-time threat detection, behavioral analysis, and automated response. Use when onboarding endpoints to EDR coverage, configuring detection policies, or integrating Falcon telemetry with SIEM platforms. Activates for requests involving CrowdStrike deployment, Falcon sensor installation, EDR policy configuration, or endpoint detection and response.

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Deploys and monitors ransomware canary files across critical directories using Python's watchdog library for real-time filesystem event detection. Places strategically named decoy files that mimic high-value targets (financial records, credentials, database exports) in locations ransomware typically enumerates first. Monitors for any read, modify, rename, or delete operations on canary files and triggers immediate alerts via email, Slack webhook, or syslog when interaction is detected, providing early warning before full encryption 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。

Deploys canary files (honeytokens) across file systems to detect ransomware encryption activity in real time. Uses strategically placed decoy documents monitored via file integrity monitoring or OS-level watchdogs to trigger alerts when ransomware modifies or encrypts them. Activates for requests involving ransomware canary deployment, honeyfile setup, deception-based ransomware detection, or file integrity monitoring for encryption.

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 teaches security teams how to detect and respond to unauthorized cryptocurrency mining operations in cloud environments. It covers identifying cryptomining indicators through compute usage anomalies, network traffic patterns to mining pools, GuardDuty CryptoCurrency findings, and runtime process monitoring on EC2, ECS, EKS, and Azure Automation workloads.

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Container escape is a critical attack technique where an adversary breaks out of container isolation to access the host system or other containers. Detection involves monitoring for escape indicators

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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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Deploying Cloudflare Access with Cloudflare Tunnel to provide zero trust access to self-hosted and private applications, configuring identity-aware access policies, device posture checks, and WARP client enrollment for VPN replacement.

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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.

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This skill teaches security teams how to deploy and operationalize Amazon GuardDuty for continuous threat detection across AWS accounts and workloads. It covers enabling protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity levels, and building automated response workflows using EventBridge and Lambda.

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Audit Azure Blob and ADLS storage accounts for public access exposure, weak or long-lived SAS tokens, missing encryption at rest, disabled HTTPS-only traffic, and outdated TLS versions using the azure-mgmt-storage Python SDK.

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Detect and investigate Azure service principal abuse including privilege escalation, credential compromise, admin consent bypass, and unauthorized enumeration in Microsoft Entra ID environments.

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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.

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Detect DCSync attacks where adversaries abuse Active Directory replication privileges to extract password hashes by monitoring for non-domain-controller accounts requesting directory replication via DsGetNCChanges.

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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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Configuring Zscaler Private Access (ZPA) to replace traditional VPN with zero trust network access by deploying App Connectors, defining application segments, configuring access policies based on user identity and device posture, and integrating with IdPs.

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Detect and prevent ARP spoofing attacks using ARPWatch, Dynamic ARP Inspection, Wireshark analysis, and custom monitoring scripts to protect against man-in-the-middle interception.

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 a Software-Defined Perimeter using the CSA v2.0 specification with Single Packet Authorization, mutual TLS, and SDP controller/gateway configuration to enforce zero trust network 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。