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概要と使いどころ
AWS Bedrock AgentCore comprehensive expert for deploying and managing AI agents at scale. Use when working with any AgentCore service including Gateway, Runtime, Memory, Identity, Code Interpreter, Browser, Observability, Agent Registry, or Evaluations.
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。
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.
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。
实战 SRC / 众测 / Bug bounty 漏洞挖掘工作流 skill。包含：5 阶段方法论（intake → recon → enum → hunt → report）、19 个攻击类 playbook（SQLi/XSS/RCE/SSRF/IDOR/CSRF/Path Traversal/File Upload/SSTI/XXE/Race/HTTP Smuggling/OAuth/JWT/SAML/GraphQL/Mobile/LLM/DoS）、305 个结构化 payload、263 个 WAF/EDR 绕过变体、2887 份 HackerOne 真实 High/Critical 已披露案例、77,000+ WooYun 案例统计、国产 OA / 中间件指纹库、银行 / 电信行业垂直 playbook。当用户提到 "src 挖洞 / src 漏洞挖掘 / bug bounty / 众测 / hackerone / 漏洞赏金 / SRC / 任意 X 漏洞 / 渗透测试" 或问"如何挖某个目标 / 怎么测某个 API / 如何绕过 WAF" 时触发。
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。
Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.
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 map and remove malware, backdoors, and attacker persistence mechanisms (registry Run keys, scheduled tasks, WMI subscriptions, services, cron/init.d) from infected Windows and Linux systems using Autoruns, EDR/AV, and YARA, restoring a clean state while preventing re-infection. Use after containment and forensic analysis have identified all compromised systems and persistence mechanisms and you are ready to eradicate and recover.
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 privilege escalation attempts across Windows and Linux, including access token manipulation, UAC bypass, unquoted service path abuse, kernel exploits, and sudo/doas abuse. Use when threat hunting for T1068-style privilege escalation, triaging EDR/SIEM alerts on suspicious privilege changes, scoping compromise during incident response, or validating detection coverage in a purple team exercise.
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 (T1550.002) attacks by analyzing NTLM authentication patterns, flagging Type 3 logons using NTLM where Kerberos would be expected, and correlating with credential-dumping indicators. Use when threat hunting for lateral movement via stolen NTLM hashes, triaging EDR/SIEM alerts on suspicious NTLM logons, scoping compromise during incident response, or validating detection coverage in a purple team exercise.
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 process injection techniques (T1055) - including DLL injection, process hollowing, and APC injection - by analyzing Sysmon Event IDs 1, 7, 8, 10, and 25 for cross-process memory operations, remote thread creation, and anomalous DLL loads. Use when hunting defense-evasion activity that hides code inside legitimate processes, investigating an EDR alert on suspicious cross-process access, or validating Sysmon coverage for injection 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 rootkit presence on compromised systems by identifying hidden processes, hooked system calls, modified kernel structures, and covert network connections using Volatility memory forensics, cross-view detection, and tools like GMER, rkhunter, chkrootkit, and RootkitRevealer. Use when standard tools (Task Manager, netstat, AV/EDR) show nothing abnormal but compromise is suspected.
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 by hunting for anomalous interactive logons, privilege escalation, and lateral movement using EDR/SIEM telemetry (CrowdStrike Falcon, Microsoft Defender, Splunk, Elastic Security, Sysmon, Velociraptor) and Sigma detection rules. Use when hunting for service-account misuse or investigating a service account performing unexpected interactive logons.
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 container escape at runtime across tooling - namespace manipulation, capability abuse, kernel exploits, sensitive host mounts, and anomalous syscalls - and explains which signals matter regardless of whether Falco, Sysdig, auditd, or an EDR is doing the collection. Use when deciding what breakout behaviour to monitor, investigating a suspected Docker or Kubernetes breakout, or comparing escape coverage across runtime sensors. Keywords: container escape, breakout, namespaces, CAP_SYS_ADMIN, privileged, hostPath, kernel exploit, syscall. Do not use for Falco rule syntax itself - use detecting-container-escape-with-falco-rules; for a static configuration sweep use performing-container-escape-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 defense evasion techniques used by adversaries in endpoint logs including log tampering, timestomping, process injection, and security tool disabling. Use when investigating suspicious endpoint behavior, building detection rules for evasion tactics, or conducting threat hunting for stealthy adversary activity. Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.
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 (e.g. via Mimikatz) using Sysmon Event ID 10 process-access logging, Windows Security logs, and SIEM correlation rules. Use when hunting for credential-theft activity on Windows/Active Directory hosts or triaging EDR alerts on LSASS 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 using Python's watchdog library, placing decoy files mimicking high-value targets (financial records, credentials, database exports) where ransomware enumerates first, and alerting via email, Slack, or syslog on any read/modify/rename/delete. Use for early-warning ransomware detection on file servers, NAS, or endpoints, or to supplement EDR where agents can't be deployed.
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 Microsoft Sentinel as a cloud-native SIEM/SOAR by configuring multi-cloud data connectors (AWS, Azure, GCP), writing KQL detection and hunting queries, and building automated Logic Apps response playbooks. Use when establishing a centralized SOC for multi-cloud environments, migrating from a legacy SIEM, or performing petabyte-scale threat hunting; not for AWS-only setups where Security Hub/GuardDuty suffice or for endpoint EDR needs.
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 a systematic threat-hunt workflow that turns threat intelligence and ATT&CK gap analysis into testable hypotheses, then executes and validates them via EDR/SIEM queries (CrowdStrike, Defender, Splunk, Elastic, Sysmon, Velociraptor, Sigma) and documents findings in a standardized hunt report. Use when planning or running a proactive threat hunt or scoping compromise from an intel- or anomaly-driven lead.
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。
Analyzes bootkit and advanced rootkit malware infecting the Master Boot Record (MBR), Volume Boot Record (VBR), or UEFI firmware for below-OS persistence, covering boot sector analysis, UEFI module inspection, and anti-rootkit detection. Use when compromise survives OS reinstallation or antivirus/EDR fails to detect malware despite clear infection signs.
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。
Prepare a defense-contractor environment for CMMC Level 2 certification: scope CUI and FCI, implement the 110 NIST SP 800-171 Rev 2 security requirements across 14 families, compute the SPRS score with the DoD Assessment Methodology, manage a compliant POA&M, and ready the organization for a C3PAO assessment. Use when an organization handles Controlled Unclassified Information (CUI) under a DoD contract, when a contract carries DFARS clause 252.204-7012/7019/7020/7021, when preparing for or responding to a CMMC assessment, when computing or improving an SPRS score, when building a System Security Plan or POA&M for 800-171, or when scoping which systems are in the CUI boundary. Keywords: CMMC, CMMC Level 2, NIST 800-171, SP 800-171 Rev 2, CUI, FCI, SPRS, DFARS 7012, C3PAO, POA&M, System Security Plan, DoD Assessment Methodology, 110 controls, defense industrial base, DIB, FedRAMP equivalency.
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。
AI image generation with OpenAI GPT Image 2.5, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
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。
Guide the user through an independent iFixAi audit of their own agent, checking whether it does the job it is supposed to do given their business rules and org structure. Prefer pointing it at the user's REAL deployed agent over its HTTP endpoint (its actual tools, retrieval, and governance) with `--provider http --endpoint <url>`; only when no endpoint is reachable, fall back to replicating the model beneath as a bare stand-in (Anthropic, OpenAI, Gemini, Azure, Bedrock, etc.). Graded by the judge(s) of their choice (the same model, one independent judge, or a cross-vendor panel). You are the operator who walks them through it and explains the scorecard, running the SAME `ifixai run` engine as the guided CLI. Use when the user asks to run iFixAi or to audit an agent.
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。
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.
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。
Comprehensive red team operations methodology covering full engagement lifecycle from planning through reporting. Addresses engagement scoping and rules of engagement negotiation, multi-tier C2 infrastructure design with redirectors and domain fronting, malleable traffic profiles and beacon tradecraft, OPSEC discipline including attribution avoidance and indicator management, EDR and AMSI evasion techniques using direct syscalls and unhooking, data collection with chain-of-custody controls, and structured reporting with purple team debrief workflows. Covers assumed-breach, external-to-internal, insider threat, and hybrid physical-cyber engagement scenarios with MITRE ATT&CK mapping throughout. Targets operators planning or executing adversary simulation engagements against mature defenders.
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。
Shellcode development reference for offensive security engagements. Use when writing custom x86/x64 shellcode, implementing position-independent code (PIC), building shellcode loaders, evading AV/EDR detection, or converting PE files to shellcode. Covers null byte avoidance, API hashing, encoder/decoder patterns, staged vs stageless payloads, Windows PEB traversal, and cross-platform shellcode 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。
Practical offensive fuzzing methodology covering target identification, fuzzer selection (AFL++, libFuzzer, Honggfuzz, Boofuzz, syzkaller), harness writing, corpus curation, mutation strategies, coverage measurement, and crash triage. Use when setting up or running fuzz campaigns against any target: file parsers, network protocols, kernel drivers, EDR engines, embedded firmware, or language runtimes.
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。