「agent」の検索結果

Configure microsegmentation policies to enforce least-privilege workload-to-workload access using tools like VMware NSX, Illumio, and Calico, preventing lateral movement in zero trust architectures.

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 Cisco Duo multi-factor authentication across enterprise applications, VPN, RDP, and SSH access points. This skill covers Duo integration methods, adaptive authentication policies, device trust

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 Microsoft Defender for Endpoint (MDE) advanced protection settings including attack surface reduction rules, controlled folder access, network protection, and exploit protection. Use when hardening Windows endpoints beyond default Defender settings, deploying enterprise-grade endpoint protection, or meeting compliance requirements for advanced malware defense. Activates for requests involving Windows Defender configuration, ASR rules, MDE tuning, or Microsoft endpoint security.

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 AWS IAM privilege escalation paths using boto3 and Cloudsplaining policy analysis to identify overly permissive policies, dangerous permission combinations, and least-privilege 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。

Designs and implements VLAN-based network segmentation on managed switches to isolate network zones, enforce access control between segments, and reduce the attack surface by limiting lateral movement paths in enterprise network 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。

Detect unauthorized modifications to running containers by monitoring for binary execution drift, file system changes, and configuration deviations from the original container image.

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。

TLS 1.3 (RFC 8446) is the latest version of the Transport Layer Security protocol, providing significant improvements over TLS 1.2 in both security and performance. It reduces handshake latency to 1-R

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。

Configure secure OAuth 2.0 authorization flows including Authorization Code with PKCE, Client Credentials, and Device Authorization Grant. This skill covers flow selection, PKCE implementation, token

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。

Correlates disparate security incidents, IOCs, and adversary behaviors across time and organizations to identify unified threat campaigns, attribute them to common threat actors, and extract shared indicators for improved detection. Use when multiple incidents exhibit overlapping indicators, when sector-wide attack campaigns require cross-organizational analysis, or when building campaign-level intelligence products. Activates for requests involving campaign analysis, incident clustering, cross-organizational IOC correlation, or MISP correlation engine.

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 pfSense firewall rules, NAT policies, VPN tunnels, and traffic shaping to enforce network segmentation, control traffic flow, and protect internal network zones in enterprise and small-to-medium business 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。

Detect lateral movement in Azure AD/Entra ID environments using Microsoft Graph API audit logs, Azure Sentinel KQL hunting queries, and sign-in anomaly correlation to identify privilege escalation, token theft, and cross-tenant pivoting.

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 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.

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。

Detects prompt injection attacks targeting LLM-based applications using a multi-layered defense combining regex pattern matching for known attack signatures, heuristic scoring for structural anomalies, and transformer-based classification with DeBERTa models. The detector analyzes user inputs before they reach the LLM, flagging direct injections (system prompt overrides, role-play escapes, instruction hijacking) and indirect injections (encoded payloads, multi-language obfuscation, delimiter-based escapes). Based on the OWASP LLM Top 10 (LLM01:2025 Prompt Injection) and Simon Willison's prompt injection taxonomy. Activates for requests involving prompt injection detection, LLM input sanitization, AI security scanning, or prompt attack 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 and test for OWASP API3:2023 Broken Object Property Level Authorization vulnerabilities including excessive data exposure and mass assignment attacks.

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。

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

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 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.

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。

Systematically deobfuscate multi-layer PowerShell malware using AST analysis, dynamic tracing, and tools like PSDecode and PowerDecode to reveal hidden payloads and C2 infrastructure.

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。

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。

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。

Business Email Compromise (BEC) is a sophisticated fraud scheme where attackers impersonate executives, vendors, or trusted partners to trick employees into transferring funds, sharing sensitive 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。

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。

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