1.1万 件 ・ 関連度順
概要と使いどころ
Close out a completed workstream by updating README artifacts when needed, producing a commit message, and applying changelog-ready content when the work is ready for commit. Use after review when a stable checkpoint is ready.
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。
Use when wiring shadcn/ui primitives, forms or admin UI in site-os — the component mechanics, the VBField validation layer, and the UI bugs that have actually shipped here. For brand identity (colour, type, logo, voice) load brand instead; that skill wins on any disagreement.
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。
Apply this site's visual identity — colours, type, logo files and fixed brand strings. Use for any page, component, social asset or document that should look like the site.
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。
Update GSD to latest version with changelog display
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。
Automatically advance to the next logical step in the GSD workflow
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 risky OAuth application consent grants in Azure AD / Microsoft Entra ID using Microsoft Graph API, audit logs, and permission analysis to identify illicit consent grant 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。
Tests APIs for injection vulnerabilities including SQL injection, NoSQL injection, OS command injection, LDAP injection, and Server-Side Request Forgery (SSRF) through API parameters, headers, and request bodies. The tester crafts malicious payloads targeting different backend technologies and injection contexts to extract data, execute commands, or access internal services. Maps to OWASP API8:2023 Security Misconfiguration and API7:2023 SSRF. Activates for requests involving API injection testing, SQLi in APIs, NoSQL injection, SSRF testing, or API input validation assessment.
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。
Executes comprehensive red team exercises that simulate real-world adversary operations against an organization's people, processes, and technology. The red team operates with stealth as a primary objective, employing the full attack lifecycle from initial reconnaissance through objective completion while testing the organization's detection and response capabilities. This differs from penetration testing by focusing on adversary emulation rather than vulnerability identification. Activates for requests involving red team exercise, adversary simulation, adversary emulation, or full-scope offensive security assessment.
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。
Exploit PHP type juggling vulnerabilities caused by loose comparison operators to bypass authentication, circumvent hash verification, and manipulate application logic through type coercion 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。
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。
Detect DNS-based data exfiltration by analyzing Zeek dns.log for high-entropy subdomains and anomalous query patterns
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。
Identifies lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek, Velociraptor, and SIEM correlation rules to detect attackers moving between 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。
Detect adversary lateral movement across networks using Splunk SPL queries against Windows authentication logs, SMB traffic, and remote service abuse.
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 LSASS credential dumping, SAM database extraction, and NTDS.dit theft using Sysmon Event ID 10, Windows Security logs, and SIEM correlation rules
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 Zeek (formerly Bro) network security monitor to passively analyze network traffic, generate structured logs, detect anomalous behavior, and create custom detection scripts for threat hunting and incident response.
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 compromised O365 and Google Workspace email accounts by analyzing inbox rule creation, suspicious sign-in locations, mail forwarding rules, and unusual API access patterns via Microsoft Graph and audit logs.
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 Pass-the-Hash attacks by analyzing NTLM authentication patterns, identifying Type 3 logons with NTLM where Kerberos is expected, and correlating with credential dumping.
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 abuse of service accounts through anomalous interactive logons, privilege escalation, lateral movement, and unauthorized access patterns.
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。
Deobfuscates malicious JavaScript code used in web-based attacks, phishing pages, and dropper scripts by reversing encoding layers, eval chains, string manipulation, and control flow obfuscation to reveal the original malicious logic. Activates for requests involving JavaScript malware analysis, script deobfuscation, web skimmer analysis, or obfuscated dropper 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。
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。
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.
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 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。