3,605 件 ・ 関連度順
概要と使いどころ
Detect DNS-based data exfiltration by analyzing Zeek dns.log for high-entropy subdomains, oversized TXT/NULL records, and anomalous query volume or patterns. Use when investigating suspected DNS tunneling, covert C2 over DNS, or data exfiltration hidden in DNS queries against network traffic captured by Zeek.
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 anomalies in DNP3 communications used in SCADA/ICS systems by monitoring unauthorized control commands, firmware update attempts, protocol violations, and deviations from baseline traffic using deep packet inspection and machine learning approaches. Use when securing energy-sector or other OT/ICS networks, investigating suspicious DNP3 master/outstation activity, or building an anomaly-based IDS for industrial control traffic.
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 analyzes Bluetooth Low Energy (BLE) security attacks including sniffing, replay attacks, GATT enumeration abuse, and Man-in-the-Middle interception. Uses Ubertooth One and nRF52840 sniffers for packet capture, the bleak Python library for GATT service enumeration, and crackle for BLE encryption cracking. Use when assessing IoT device BLE security, monitoring for BLE-based attacks on wireless infrastructure, or performing authorized BLE penetration testing. Activates for requests involving BLE security assessment, Ubertooth sniffing, GATT enumeration, or BLE replay 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。
Detects fileless malware and in-memory attacks that execute entirely in RAM without writing persistent files to disk, evading traditional antivirus. Use when building detections for PowerShell-based attacks, reflective DLL injection, WMI persistence, and registry-resident malware. Activates for requests involving fileless malware detection, in-memory attacks, PowerShell exploitation, or living-off-the-land techniques.
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-and-control (C2) traffic tunneled over DNS from tools like Iodine, dnscat2, dns2tcp, and Cobalt Strike DNS beacon, using Shannon entropy analysis of query subdomains, ML-based DGA classification, passive DNS correlation, and Zeek/Suricata signatures. Use when investigating suspected DNS tunneling, classifying DGA domains, detecting DNS beaconing, or building DNS anomaly rules for a SOC/SIEM.
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 Golden Ticket attacks in Active Directory using Splunk and KQL queries against domain controller event logs, looking for Kerberos TGT anomalies such as mismatched encryption types, impossible ticket lifetimes, non-existent accounts, and forged PAC signatures. Use when hunting for Kerberos ticket forgery or krbtgt-based persistence (MITRE T1558.001) in AD environments.
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 Palo Alto Networks Prisma Access for SASE-based zero trust network access, configuring GlobalProtect agents, ZTNA Connectors, security policy enforcement, and Strata Cloud Manager integration for unified management. Use when implementing enterprise-grade SASE with integrated ZTNA/SWG/CASB/FWaaS, replacing both VPN and branch firewalls with cloud-delivered security, or integrating ZTNA with an existing Palo Alto NGFW estate.
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。
Designs and implements VLAN-based (802.1Q) network segmentation on managed switches to isolate zones such as corporate, servers, DMZ, guest, and IoT, and to limit lateral movement paths. Use when segmenting an enterprise network into isolated security zones, meeting compliance mandates (PCI-DSS, HIPAA, SOC 2) for network isolation, or reducing blast radius from a security incident.
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。
Configures Google Cloud Identity-Aware Proxy (IAP) via gcloud to enforce per-request identity verification on Compute Engine, App Engine, Cloud Run, and GKE, including IAM bindings, Access Context Manager access levels, session/reauth settings, and service-account programmatic access. Use when replacing VPN access with identity-based access to GCP backends or configuring context-aware, zero-trust policies for Google Cloud services.
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 a Software-Defined Perimeter per the CSA v2.0 specification, configuring Single Packet Authorization, mutual TLS, and SDP controller/gateway components to enforce zero trust network access. Use when building or hardening zero trust network architecture, implementing SPA-based "invisible" infrastructure that cloaks services from unauthenticated scanning, or meeting compliance requirements for 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。
Deploys and configures Suricata IDS/IPS with Emerging Threats rulesets, EVE JSON logging, and custom rules for high-throughput, protocol-aware traffic inspection (HTTP, TLS, DNS, SMB) and SIEM integration. Use when running Suricata in IDS or inline IPS mode to detect or block malicious traffic, or when combining signature-based and protocol anomaly detection with file extraction.
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。
Plants Canarytokens-based decoy artifacts (honey credentials, DNS tokens, web-bug URLs, AWS keys, documents, kubeconfigs) using Thinkst's open-source Canarytokens project and alerts via email or webhook when a token is touched. Use for high-fidelity intrusion detection in low-telemetry areas like file shares or credential stores, or to catch credential dumping and data-theft staging.
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。
Detects prompt injection using regex signature matching, heuristic scoring for structural anomalies, and DeBERTa-based transformer classification, flagging direct injections (system-prompt overrides, role-play escapes) and indirect injections (encoded payloads, obfuscation) per OWASP LLM Top 10 (LLM01:2025). Use for input validation layers in chatbots/agents/RAG pipelines, or for retrospectively classifying injection attempts in logs or incident investigations.
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。
Configures Zscaler Private Access (ZPA) to replace traditional VPN with zero trust network access by deploying App Connectors, defining application segments, configuring identity- and device-posture-based access policies, and integrating with IdPs. Use when replacing VPN concentrators with ZTNA or providing remote users secure access to internal applications without network-level connectivity.
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。
Installs, configures, and tunes Snort 3 to monitor network traffic for malicious activity using custom and community rulesets, preprocessors, and alert output plugins. Use when deploying network-based intrusion detection at key boundaries, writing custom Snort rules, tuning rulesets to reduce false positives, or integrating Snort alerts with a SIEM.
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 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.
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。
Configures Hardware Security Modules for cryptographic key storage using the PKCS#11 standard interface, covering key generation, signing, encryption, and key management on physical HSMs and SoftHSM2 for development. Use when protecting cryptographic keys so they never leave a hardened device boundary, or when building and testing PKCS#11-based key management workflows.
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 and configures Tailscale (or self-hosted Headscale) as a WireGuard-based zero trust mesh VPN, setting up identity-aware ACLs, exit nodes, subnet routers, and MagicDNS for encrypted peer-to-peer connectivity. Use when replacing traditional VPN servers with an identity-authenticated mesh network or enforcing granular per-device access control lists.
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 anomaly detection for OT/ICS environments using machine learning on OT network baselines, physics-based process models, and Modbus/DNP3/OPC UA traffic analysis to flag deviations, rogue devices, and mismatches against historian data. Use for continuous OT monitoring, baselining deterministic SCADA polling, or investigating alerts from Nozomi Guardian/Dragos needing deeper protocol 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。
Build structured communication templates for malware incidents (ransomware, wiper, trojan, worm), covering internal stakeholder notifications, executive briefings, technical advisories for IT teams, customer notifications, and regulatory disclosures, with severity-based escalation procedures. Use when drafting or standardizing incident communications and notification workflows for a malware outbreak.
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。
Establish a repeatable operational process for triaging, testing, and deploying Microsoft Patch Tuesday security updates (Windows, Office, Exchange, SQL Server, Azure) via WSUS/SCCM within risk-based remediation SLAs, from advisory review through validation. Use when building or improving a monthly patch management workflow or prioritizing which CVEs to remediate first.
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 harden a Sliver C2 team server (BishopFox's Go-based adversary emulation framework) with multi-protocol listeners (mTLS, HTTP/S, DNS, WireGuard), redirectors, domain fronting, and multi-operator support for authorized red-team operations. Use when standing up resilient C2 for a red-team engagement or generating beacon/session implants that must survive blue-team 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。
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。