「threat」の検索結果

Applies the reasoning style of Geoffrey Hinton, deep learning pioneer and 2018 Turing Award winner. Use this skill whenever evaluating AI safety, existential risk, neural network architectures, cognitive science, or tech regulation. Reach for this when the user is discussing LLM capabilities (understanding vs. autocomplete), the biological vs. digital intelligence divide, AI alignment strategies, or the societal/economic impacts of automation. It is highly applicable when dealing with contrarian scientific ideas, hardware/software integration (mortal vs. immortal computing), or global cooperation on technological threats. Do not wait for the user to name Hinton; trigger this skill proactively for any deep learning or AI existential risk analysis.

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。

OSS-only security for OWASP Top 10, pentest, vuln testing (XSS, SSRF, CSRF, business-logic, Host header), threat modeling (STRIDE, ATT&CK), Sigma rules, SAST, code audit, AI/LLM red-team, or replacing paid tools (Burp, Nessus, Splunk) with OSS.

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 a broad, authorized security audit across application, infrastructure, identity, dependencies, and operations. Use when the user needs a scoped security posture review; use the SAST, DAST, dependency-scanning, or threat-modeling skill when the request is limited to one specialist 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。

Threat-model and harden AI agents, RAG systems, assistants, and tool-using workflows against direct, indirect, stored, cross-agent, and multimodal prompt injection. Use when reviewing an agent architecture, isolating untrusted content, constraining tools and egress, protecting secrets, adding injection-focused tests, investigating a suspected injection incident, or documenting residual prompt-injection risk.

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。

Think and work like an expert Computer Security Researcher. Use when a task calls for Computer Security Researcher judgment. Reasons from explicit threat models and CIA/STRIDE through AFL++/libFuzzer triage, ASan/KASAN oracles, ProVerif/Tamarin proofs, CVE/CWE/CAPEC taxonomies, CyberGym dual-execution benchmarks, Menlo/CVD ethics, and USENIX open-science artifact norms.

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。

Assesses genetic health of populations for conservation using effective population size estimation (GONE2 for recent Ne trajectory, NeEstimator for contemporary Ne, Stairway Plot 2 and PSMC for historical Ne), F-statistics (hierfstat), runs of homozygosity (detectRUNS), and genetic diversity metrics. Use when estimating effective population size, detecting inbreeding or bottlenecks, or assessing genetic diversity in threatened species from microsatellite or SNP 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。

Comprehensive security auditing framework for LLM applications covering OWASP Top 10 for LLMs, threat modeling, penetration testing, and compliance with NIST AI RMF and ISO 42001Use when "security audit, llm pentest, ai security assessment, compliance audit, vulnerability assessment, security, audit, compliance, penetration-testing, owasp, llm" mentioned.

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。

Security engineering that protects applications, data, and users from real-world threatsUse when "security, authentication, authorization, encryption, OWASP, vulnerability, XSS, SQL injection, CSRF, secrets, password, JWT, OAuth, permissions, audit, compliance, security, authentication, authorization, encryption, vulnerabilities, OWASP, compliance, audit" mentioned.

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。

Designing anatomically plausible, visually distinctive creatures that communicate threat, personality, and role through form - from terrifying bosses to collectible companionsUse when "creature design, design a creature, design a monster, monster design, boss design, enemy creature, companion creature, pet design, wildlife design, alien creature, fantasy creature, horror monster, cute creature, pokemon style, creature anatomy, creature silhouette, creature movement, hybrid animal, ecosystem creatures, creature family, mount design, dragon design, beast design, creature, monster, boss, enemy, companion, wildlife, horror, cute, pokemon, anatomy, silhouette, locomotion, ecosystem, hybrid, fantasy, sci-fi, kaiju, cryptid" mentioned.

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。

Security vulnerabilities in AI-generated code and LLM applications, covering OWASP Top 10 for LLMs, secure coding patterns, and AI-specific threat modelsUse when "ai code security, llm vulnerabilities, ai generated code review, owasp llm, secure ai development, security, ai, llm, owasp, code-review, vulnerabilities" mentioned.

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。

Applies the reasoning style of Geoffrey Hinton, deep learning pioneer and 2018 Turing Award winner. Use this skill whenever evaluating AI safety, existential risk, neural network architectures, cognitive science, or tech regulation. Reach for this when the user is discussing LLM capabilities (understanding vs. autocomplete), the biological vs. digital intelligence divide, AI alignment strategies, or the societal/economic impacts of automation. It is highly applicable when dealing with contrarian scientific ideas, hardware/software integration (mortal vs. immortal computing), or global cooperation on technological threats. Do not wait for the user to name Hinton; trigger this skill proactively for any deep learning or AI existential risk analysis.

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 professional-grade security standards to any web application task. Use this skill when writing code that handles authentication, authorization, user input, APIs, file uploads, sessions, secrets, payments, or any data from external sources. Also use when the user asks to review, audit, or assess security of code or a web app. Covers OWASP Top 10 (2025), secure coding, threat modeling, and defensive architecture. Activate even when security is not explicitly mentioned — treat every web feature as a security surface.

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。

Reusable writing-style contract for agent outputs (reports, ARCH docs, verdicts, threat models). Forces direct prose with concrete evidence, no marketing voice, no hedge words. The single most-referenced skill across the pipeline — used by 28 agents.

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。

Engineering detection rules (Sigma/YARA), detection coverage mapping, threat hunting hypotheses, Purple Team Blue side, Detection-as-Code CI/CD. Use when defensive verification is needed.

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。

Designing red team attack scenarios, threat models, MITRE ATT&CK/OWASP application, Purple Team exercises, and AI/LLM red teaming. Use when adversarial security validation is needed.

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。

Retroactively verify threat mitigations for a completed 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。

MITRE ATT&CK framework reference — tactics, techniques, and tool-to-TTP mappings for pentest documentation and detection rule writing

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。

CVSS 3.1 vector examples, executive summary template, full technical finding template, and remediation language bank for pentest reports

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-DB and searchsploit reference — EDB→Metasploit module mappings, PoC reliability rubric, CVSS tier quick reference, and searchsploit usage 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。

Active Directory attack reference — BloodHound Cypher queries, Kerberos attack decision tree, ACE/ACL abuse, ADCS ESC1-8, and AD misconfig checklist

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。

SecLists path map, hashcat rules, CeWL usage, and custom wordlist generation for all attack categories

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。

A C-level strategy advisory board, run as a team of named specialist agents, that takes an executive from a raw strategic question to a defended, board-ready recommendation. Use this skill whenever the user faces a significant business decision or wants strategic analysis — market entry, build-vs-buy, M&A, digital transformation, annual planning, portfolio prioritization, pricing, a big investment, a competitive threat, a turnaround. Trigger on requests like "should we invest in / build / buy / enter…", "develop a strategy for…", "evaluate this opportunity", "make the business case", "stress-test this plan", "run a pre-mortem", or "prepare a board presentation" — in any language, even when the user doesn't say the word "strategy". Also trigger when the user names a board member (Drucker, Porter, Christensen, Graham, Grove, Wack, Taleb, Minto) or asks to convene the board / open a boardroom session.

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 and describes vulnerabilities for specific assets and threats within an insurance company risk register context. The output must be highly professional, eloquent, and grammatically impressive, utilizing labelled headings and subheadings.

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。

Quantify cyber risk using FAIR methodology with Monte Carlo simulation, assess control effectiveness against NIST CSF/CIS/ISO 27001 frameworks, evaluate risk appetite alignment, and analyze cyber insurance coverage adequacy. Covers threat landscape mapping, asset valuation, loss event frequency and magnitude estimation, annualized loss expectancy calculation, control gap analysis with ROI ranking, residual risk assessment, and insurance policy gap modeling at 90th/95th/99th percentile loss scenarios. Use when building risk registers, preparing board-level risk dashboards, evaluating security investment priorities, assessing cyber insurance coverage, or auditing any organization's risk quantification maturity per NIST RMF, ISO 27005, or FAIR standards.

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。