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Security Operations Center skill for alert triage, detection engineering, incident response, log analysis, threat hunting, SIEM queries, EDR investigation, timeline building, IOC handling, escalation notes, containment recommendations, and analyst-ready reporting. Use for blue-team operations, suspicious event analysis, and defensive cybersecurity workflows.

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Detection engineering skill for writing, testing, and tuning Sigma, YARA, YARA-L, Suricata, Snort, Zeek, KQL, SPL, EQL, Chronicle, and Elastic detection rules. Covers ATT&CK coverage mapping, telemetry gap analysis, false-positive tuning, detection-as-code pipelines, and validation with Atomic Red Team and Caldera. Use to design durable detections backed by tests.

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。

Authorized offensive security skill for ethical penetration testing, red-team planning, vulnerability validation, reconnaissance of owned assets, web/API/mobile/cloud assessment, report writing, remediation guidance, and lab-based security testing. Use only for systems the user owns or is authorized to test; focus on safe, scoped, legal assessment and defensive improvement.

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。

Execute commands and binaries on remote Windows systems utilizing PsExec and SMB/RPC mechanisms. This skill details the mechanics behind tools like Sysinternals PsExec, Impacket's psexec.py, and their role in lateral movement via hidden administrative shares.

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。

Test Retrieval-Augmented Generation (RAG) systems for data poisoning, prompt injection via retrieved documents, and data exfiltration through manipulated context windows. Use this skill when assessing RAG-based chatbots, knowledge bases, enterprise AI assistants, or any system that augments LLM responses with external document retrieval. Covers document injection, embedding manipulation, knowledge base poisoning, and cross-document inference 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。

Execute advanced evasion by injecting malicious code into the memory space of a legitimate, suspended process (Process Hollowing). This skill details techniques to bypass static and dynamic analysis by masking malicious activity behind trusted processes like svchost.exe or explorer.exe.

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Extract the hidden foundational System Prompts, internal instructions, backend APIs, and confidential contextual data powering Large Language Model (LLM) applications using targeted prompt injection manipulation and adversarial psychological engineering.

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。

Test Model Context Protocol (MCP) servers and tool-calling systems for security vulnerabilities including tool injection, parameter manipulation, privilege escalation, and data exfiltration through AI agent tool interfaces. Use this skill when assessing MCP server implementations, AI agent tool integrations, or any system that exposes tools to language models. Covers tool confusion attacks, cross-tool exploitation, and MCP server hardening 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。

macOS security bypass playbook. Use when targeting macOS endpoints and need to bypass TCC, Gatekeeper, SIP, sandbox, code signing, or entitlement-based protections during authorized red team or pentest engagements.

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。

Extract sensitive training data and internal capabilities from AI models through repeated programmatic querying. Use this skill when testing LLMs and ML models for data privacy leaks, intellectual property exposure, or unintended memorization. Covers membership inference, prompt extraction, training data reconstruction, and API boundary testing.

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Exploit an application's absolute trust in its underlying LLM (Overreliance). Use this skill to induce critical "hallucinations" (confident falsehoods) that cause downstream logical systems or automated agents tracking the LLM's output to make destructive actions or grant unauthorized 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。

Exploit AI applications using Indirect Prompt Injection. This skill focuses on hiding malicious instructions within data sources (web pages, documents, emails) that the LLM processes, causing the AI to execute unintended actions or leak data without direct user interaction.

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。

Test Large Language Models for direct prompt injection vulnerabilities where user input overrides system instructions, extracts system prompts, bypasses safety filters, or causes unauthorized actions. Use this skill when assessing chatbots, AI assistants, LLM-powered tools, or any application that processes natural language input through an LLM. Covers role-playing attacks, instruction hierarchy exploitation, multi-turn manipulation, and context window abuse for comprehensive AI security testing.

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。

Test for indirect prompt injection vulnerabilities where malicious instructions are injected through external data sources (websites, emails, documents, database records) that the LLM processes. Use this skill when assessing LLM-integrated applications that process user-generated content, retrieve web pages, parse emails, or read documents. Covers injection via web content, email bodies, user profiles, and database records that are fed to LLM context.

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Execute advanced LLM Jailbreaking techniques using roleplay, nested environments (virtual machines), and complex personas to completely bypass safety constraints and ethical alignments embedded in AI models.

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Execute Indirect Prompt Injection attacks against Large Language Models (LLMs) by subtly embedding malicious instructions within external data sources (e.g., websites, documents, databases) that the LLM autonomously ingests. This forces the model to execute attacker-controlled commands under the guise of processing legitimate user requests.

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Execute a Kerberoasting attack to extract Service Principal Name (SPN) ticket hashes from Active Directory and crack them offline. This allows an attacker with any valid domain credentials to escalate privileges by obtaining the plaintext password of highly-privileged service accounts.

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Execute sophisticated Data Extraction and Privacy Leakage attacks explicitly against Large Language Models (LLMs) to natively force the neural network entirely into organically regurgitating exact, verbatim strings of Highly Confidential Personally Identifiable Information (PII), proprietary source code, or copyrighted material categorically memorized intrinsically during its foundational pre-training phase.

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 CVE-2023-36884, a critical Remote Code Execution vulnerability in Windows and Office associated with the Storm-0978 APT. This skill covers the weaponization of malicious Word documents to achieve code execution upon opening, bypassing Mark-of-the-Web (MotW) defenses.

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。

Simulate supply chain and adversarial machine learning attacks by injecting poisoned data or targeted backdoors into training and fine-tuning datasets. Use this skill when assessing the integrity controls of MLOps pipelines or evaluating the resilience of AI models against highly targeted, stealthy manipulation intended to alter model behavior on specific triggers.

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。

Supply-chain testing via package-manager dependency confusion: when internal package names resolve to attacker-controlled public registries, leading to malicious install and script execution. Use for npm/pip/gem/Maven/Composer/Docker manifest review and authorized red-team supply-chain exercises.

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Create and implement Malleable C2 profiles in Cobalt Strike to evade network intrusion detection systems (NIDS/IPS) and endpoint detection architectures. This skill focuses on molding the Beacon's HTTP/HTTPS traffic to resemble legitimate network traffic like Amazon, Google, or jQuery.

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Utilize the native Windows binary `certutil.exe` to download malicious payloads and optionally decode Base64 encoded files as a Living-off-the-Land (LotL) technique. This skill details how attackers bypass application whitelisting and fetch stage-2 implants.

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Exploit Active Directory replication privileges (DS-Replication-Get-Changes) to perform a DCSync attack, allowing an attacker to impersonate a Domain Controller and extract password hashes (like the krbtgt hash for Golden Tickets) without code execution on a DC.

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。