1,486 件 ・ 関連度順
概要と使いどころ
Implementing AWS CloudTrail log analysis for security monitoring, threat Tespit, and forensic investigation using Athena, CloudWatch Logs Insights, and SIEM integration to identify unauthorized access, privilege escalation, and suspicious API activity.
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。
Perform forensic investigation of AWS environments using CloudTrail logs to reconstruct attacker activity, identify compromised credentials, and analyze API call 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。
tespit etmelateral 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。
tespit etmeunusual 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。
tespit etmerisky 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。
Tespit etme data exfiltration attempts from AWS S3 buckets by analyzing CloudTrail S3 data events, VPC Flow Logs, GuardDuty Bul:ings, 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。
Tests API authentication mechanisms for weaknesses including broken token validation, missing authentication on endpoints, weak password policies, credential stuffing susceptibility, token leakage in URLs or logs, and session management flaws. The tester evaluates JWT implementation, API key handling, OAuth flows, and session token entropy to identify authentication bypasses. Maps to OWASP API2:2023 Broken Authentication. Activates for requests involving API authentication testing, token vali...
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。
tespit etmeabnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly Tespit.
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。
Provides digital forensics and signal analysis techniques for CTF challenges. Use when analyzing disk images, memory dumps, event logs, network captures, cryptocurrency transactions, steganography, PDF analysis, Windows registry, Volatility, PCAP, Docker images, coredumps, side-c
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。
YouTube transcripts to summaries, threads, blogs.
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。
Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.
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。
Backport fixes from main onto release/YYYY.WW in the ai repo with cherry-pick and rebase merge so release-please changelogs stay correct. Use when hotfixing a release branch, cherry-picking to release/*, or preparing a release backport PR.
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。
Install and wire a Telegram MCP server (chigwell/telegram-mcp, MTProto user account, not a bot) so Claude Code, Claude Desktop, Codex or any MCP client can read your chats and send replies. Use when connecting an agent to a personal Telegram account, applying the kit patches (shared SSE daemon, search_dialogs, multi-account), generating a session string, or debugging file tools that silently refuse, orphaned uv processes, database is locked, AuthKeyDuplicated or flood-wait.
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。
Generates and maintains changelogs following Keep a Changelog format. Use when updating release notes, finishing tasks, or tagging versions. For version bumps, see semantic-versioning.
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。
Complaint/ticket triage-and-dispatch App-in-Skill (Busabase App-in-Skill) for property managers, facilities teams, and helpdesk leads. Use when the user invokes $kelly-tickets or /kelly-tickets, or asks for complaint triage, ticket dispatch, 投诉, 工单, 派单, property management complaints, helpdesk queue, intake from WeChat exports/call logs/front-desk forms, crew assignment, SLA board, dispatch approval, or ticket resolution tracking.
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 asked to map, crosswalk, align, compare, or gap-analyze any two cybersecurity frameworks, control catalogs, or regulatory requirements using NIST IR 8477 Set-Theory Relationship Mapping (STRM). Triggers on terms like "map controls", "crosswalk", "framework alignment", "gap analysis", or producing a STRM CSV output file.
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。
Disciplined diagnosis workflow for hard, intermittent, or multi-component bugs and performance regressions: inspect logs and existing evidence, build a feedback loop, test falsifiable hypotheses, instrument gaps, and verify the outcome. Use when the root cause is unclear, reproduction is unreliable, several causes or components are plausible, or performance has regressed. Do NOT use for obvious single-cause errors, straightforward configuration or syntax fixes, planned feature work, or broad architecture review. Diagnosis-only requests stop after reporting the root cause and evidence; apply a fix only when the user requested one.
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。
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。
Detect OAuth access token theft and misuse by analyzing sign-in logs for impossible travel, new device patterns, token replay from unusual IPs, and anomalous scope requests via Microsoft Graph and Okta APIs.
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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 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。
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。
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。