「threat」の検索結果

Traces ransomware cryptocurrency payment flows using blockchain analysis tools such as Chainalysis Reactor, WalletExplorer, and blockchain.com APIs. Identifies wallet clusters, tracks fund movement through mixers and exchanges, and supports law enforcement attribution. Activates for requests involving ransomware payment tracing, bitcoin wallet analysis, cryptocurrency forensics, or blockchain intelligence gathering.

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 PowerShell Empire framework artifacts in Windows event logs by identifying Base64 encoded launcher patterns, default user agents, staging URL structures, stager IOCs, and known Empire module signatures in Script Block Logging events.

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 typosquatting, homograph phishing, and brand impersonation domains using dnstwist to generate domain permutations and identify registered lookalike domains targeting your organization.

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 and analyze Linux persistence mechanisms including crontab entries, systemd service units, LD_PRELOAD hijacking, bashrc modifications, and authorized_keys backdoors using auditd and file integrity monitoring

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 Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.

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 and analyze Cobalt Strike beacon configuration from PE files and memory dumps to identify C2 infrastructure, malleable profiles, and operator tradecraft.

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 malicious VBA macros embedded in Microsoft Office documents (Word, Excel, PowerPoint) to identify download cradles, payload execution, persistence mechanisms, and anti-analysis techniques. Uses olevba, oledump, and VBA deobfuscation to extract the attack chain. Activates for requests involving Office macro analysis, VBA malware investigation, maldoc analysis, or document-based threat examination.

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 malware command-and-control (C2) communication protocols to understand beacon patterns, command structures, data encoding, and infrastructure. Covers HTTP, HTTPS, DNS, and custom protocol C2 analysis for detection development and threat intelligence. Activates for requests involving C2 analysis, beacon detection, C2 protocol reverse engineering, or command-and-control infrastructure mapping.

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。

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection 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。

Parse and analyze Cobalt Strike Malleable C2 profiles using dissect.cobaltstrike and pyMalleableC2 to extract C2 indicators, detect evasion techniques, and generate network detection signatures.

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。

Knowledge base from NIST Secure Software Development Framework (SSDF) v1.1 (SP 800-218). Use for secure software development practices, SDLC security integration, software supply chain security, vulnerability disclosure, SBOM, threat modelling, secure coding, build hardening, EO 14028 compliance. Covers the four SSDF practice groups (PO, PS, PW, RV) only; does not cover NIST CSF, SP 800-53 controls, or cloud-specific security frameworks in depth.

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。

Knowledge base from NIST SP 800-160 Vol 1 (Engineering Trustworthy Secure Systems) and Vol 2 (Developing Cyber-Resilient Systems). Use for systems security engineering (SSE): the three SSE framework contexts (problem/solution/trustworthiness), the 30+ design principles for trustworthy secure design, trustworthiness and assurance/assurance cases, security across the ISO/IEC/IEEE 15288 life-cycle process groups, and the Vol 2 cyber-resiliency engineering framework — 4 goals (anticipate/withstand/recover/adapt), objectives, 14 techniques, implementation approaches, and design principles for the APT/adverse-conditions threat model. Bridges systems engineering and the NIST security cluster (CSF/SSDF/RMF). Does not reproduce ISO/IEC/IEEE 15288 process text, nor cover SP 800-53 control catalogs in depth.

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。

- Investigator OPSEC — threat-model who might notice you, control your attribution surface across IP, ASN, browser and TLS fingerprint, timing and logged-in accounts, separate research identity from… Use when setting up a research account, avoiding tipping off a subject, worrying about LinkedIn profile-view leakage, needing a burner phone or email, or hardening a research VM or browser profile

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 PR intake and multi-agent governance for deployless repositories. Use when a repo has high-volume bot or agent PRs, parallel agent work, noisy low-context PRs, merge-queue pressure, CI exhaustion, duplicate fixes, ownership confusion, or review bottlenecks that threaten a single-mainline delivery model.

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 comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.

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 audit, hardening, threat modeling (STRIDE/PASTA), Red/Blue Team, OWASP checks, code review, incident response, and infrastructure security for any project.

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 comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.

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 working with Cloudflare Cdn — cloudflare CDN management including zone configuration, cache purging, page rules, firewall rules, SSL/TLS settings, and performance optimization. Covers cache analytics, bandwidth usage, threat detection, and edge certificate management. Use when managing Cloudflare CDN zones, analyzing cache performance, configuring page rules, or troubleshooting delivery issues.

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 working with Chronicle — google Chronicle SIEM security operations, threat detection, asset investigation, and log analysis. Covers UDM search queries, detection rule management, asset and IOC lookups, reference list management, and retrohunt execution. Use when investigating security events, reviewing detection rules, searching for IOCs, or analyzing Chronicle data ingestion health.

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 working with Aws Guardduty — aWS GuardDuty finding analysis, detector management, suppression rule review, and member account oversight. Covers threat detection summary, finding severity distribution, finding type breakdown, trusted IP lists, and organization-wide security posture.

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 comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.

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 and removes infostealer malware (credential stealers, data exfiltrators) via full-system file search, cryptographic hashing, and public threat-intelligence cross-checks (VirusTotal, MalwareBazaar). Primary method is always custom hash-based detection. Windows Defender (or any platform-native AV) is allowed **only when necessary** (e.g. inconclusive hashes or deep remediation) and **must never be the default option**. The agent must exhaust the custom workflow first. Works on Windows/macOS/Linux.

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。

Structured 3-phase peer review of a diff or PR — intent, issues by severity, then pointed merge-readiness questions and a verdict. Use for general code review. Not for AI workflow self-fix-and-edit (ai-systems-review) or no-edit devil's-advocate threat models (adversarial-challenge). Phase 3 asks questions only; it is not the adversarial-challenge skill.

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。

Devil's-advocate attack on AI workflow designs — threat model, assumption challenges, code critiques, and hypothetical redesigns with no file edits. Use for "attack this design", devil's advocate, or hostile challenge on agents/tools/summarization/tokens. Not for PR peer review (code-review) or self-review that applies fixes (ai-systems-review). Prefer: this skill → decide → ai-systems-review.

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。