「sms」の検索結果

Configures Hardware Security Modules for cryptographic key storage using the PKCS#11 standard interface, covering key generation, signing, encryption, and key management on physical HSMs and SoftHSM2 for development. Use when protecting cryptographic keys so they never leave a hardened device boundary, or when building and testing PKCS#11-based key management workflows.

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Analyzes Windows Security, System, and Sysmon event logs in Splunk to detect authentication attacks, privilege escalation, persistence mechanisms, and lateral movement using SPL queries mapped to MITRE ATT&CK techniques. Use when SOC analysts need to investigate Windows-based threats, build detection queries, or perform forensic timeline analysis of Windows endpoints and domain controllers.

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Analyzes encryption algorithms, key management, and file encryption routines used by ransomware families to assess decryption feasibility, identify implementation weaknesses, and support recovery efforts. Covers AES, RSA, ChaCha20, and hybrid encryption schemes. Activates for requests involving ransomware cryptanalysis, encryption analysis, key recovery assessment, or ransomware decryption feasibility.

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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.

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Examine Linux system artifacts (auth logs, cron/systemd persistence, shell history, SSH keys, and system configuration) to uncover evidence of compromise, detect rootkits or backdoors, and reconstruct user/attacker activity. Use when investigating a compromised Linux server or workstation, hunting for persistence mechanisms, or scoping a Linux-based breach during incident response.

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Use Sysinternals Autoruns to systematically enumerate and analyze malware persistence mechanisms across Windows registry run keys, scheduled tasks, services, drivers, and startup locations. Use when hunting for persistence during Windows incident response, triaging a compromised endpoint, or validating that malware autostart entries have been fully identified and removed.

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Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense models), implementing sparse architectures like Mixtral 8x7B or DeepSeek-V3, or scaling model capacity without proportional compute increase. Covers MoE architectures, routing mechanisms, load balancing, expert parallelism, and inference optimization.

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Give chosen NanoClaw agents a real phone number as a container tool — the `dial` CLI baked into the agent image plus OneCLI credential injection for api.getdial.ai, scoped per agent, so the agents you pick can send SMS, place AI voice calls, and receive verification codes from inside the sandbox. Independent of the Dial channel; idempotent; re-run to change which agents may use it. Use when the user wants agents to text, call, or run `dial …` from a chat, without wiring Dial as a messaging channel.

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Add another phone number to an existing Dial channel — a second (or third) public line for the agent, so one NanoClaw install answers SMS and AI voice calls on multiple numbers. Use when Dial is already installed and the operator wants an additional number (e.g. a personal line plus a support line). Requires the Dial channel to already be installed (see /add-dial).

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Add Dial channel integration — a real phone number for SMS and AI voice calls via the Dial platform (getdial.ai). Native adapter — no Chat SDK bridge.

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Generic framework for converting external events (SMS, meetings, social mentions) into brain-ingestible signals. Define a transform function, register a webhook URL, and incoming events get processed through the brain pipeline.

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Router/index for the 15 regulatory & quality-management skills bundled in this plugin (ISO 13485 QMS, EU MDR 2017/745, FDA submissions under QMSR, ISO 14971 risk, CAPA, document control, ISO 27001/ISMS, ISO 42001 AIMS, EU AI Act, GDPR/DSGVO, SOC 2, auditing). Use when a compliance request doesn't obviously match one skill and you need to pick the right one (e.g., 'prepare us for an ISO 13485 audit', 'is my AI system high-risk under the AI Act').

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ISO/IEC 42001:2023 AI Management System (AIMS) specialist for compliance teams running internal audits. Three decisions: (1) Where are the gaps against Clauses 4-10 and what do we close first? (2) What goes in the AI risk register and which Annex A controls treat each risk? (3) What's the 12-month internal audit plan that satisfies Clause 9.2? Use when preparing for certification, scoping internal audit cycles, or onboarding AI systems into an existing ISMS (27001) / QMS (13485) program. NOT an executive AI strategy skill (see chief-ai-officer-advisor). NOT EU AI Act compliance (see compliance-team-eu-ai-act).

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/cs:iso27001-audit-prep <scope> — ISO 27001 ISMS audit readiness 6-question forcing interrogation. Use before annual Clause 9.2 internal audit, surveillance audit prep, or stage 1 certification readiness.

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Identify growth loops (flywheels) for sustainable traction. Evaluates 5 loop types: Viral, Usage, Collaboration, User-Generated, and Referral. Use when designing growth mechanisms, building product-led traction, or understanding how growth loops work.

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Detects AI-generated writing four ways — a heuristic audit against a catalog of known AI patterns, deterministic statistical signals (n-gram entropy, burstiness, repetition, stylometry — features never verdicts), an empirical Pangram score calibrated against known-human baselines, and a keyless scan for watermark and steganography signatures (invisible characters, homoglyphs, bidi, odd whitespace) in the bytes. USE WHEN detect AI writing, is this AI, AI detection, AI detector, did an AI write this, does this sound like AI, AI writing score, pangram, scan for AI tells, flag AI patterns, AI-isms, statistical AI signals, burstiness, text entropy, is this watermarked, detect watermark, steganography, zero-width chars, hidden characters, invisible unicode, compare drafts for AI-ness. NOT FOR rewriting prose to strip AI patterns (use a voice/authoring skill), plagiarism detection, detecting AI-generated images/video/code, or judging whether writing is any good.

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Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense models), implementing sparse architectures like Mixtral 8x7B or DeepSeek-V3, or scaling model capacity without proportional compute increase. Covers MoE architectures, routing mechanisms, load balancing, expert parallelism, and inference optimization.

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Create and manage Claude Code skills following Anthropic best practices. Use when creating new skills, modifying skill-rules.json, understanding trigger patterns, working with hooks, debugging skill activation, or implementing progressive disclosure. Covers skill structure, YAML frontmatter, trigger types (keywords, intent patterns, file paths, content patterns), enforcement levels (block, suggest, warn), hook mechanisms (UserPromptSubmit, PreToolUse), session tracking, and the 500-line rule.

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Comprehensive persistence tradecraft for authorized red team engagements covering Windows and Linux mechanisms. Windows techniques include registry Run/RunOnce keys, scheduled tasks, WMI event subscriptions, DLL search order hijacking, COM object hijacking, Startup folder drops, service creation, Security Support Provider (SSP) DLL injection, and Active Directory persistence (AdminSDHolder abuse, DCShadow, Golden Ticket, Silver Ticket, Skeleton Key, SID History injection). Linux techniques include cron and at jobs, systemd timers and services, SSH authorized_keys injection, shell profile backdoors (.bashrc/.bash_profile), PAM module backdoors, LD_PRELOAD hijacking, kernel module rootkits, web shells, and Git hook abuse. Provides operator-ready command sequences for SharPersist, Impacket ticketer, schtasks, sc.exe, crontab, and systemctl with OPSEC considerations for each method. Maps to MITRE ATT&CK T1547 (Boot or Logon Autostart), T1053 (Scheduled Task/Job), T1546 (Event Triggered Execution), T1556 (Modify Authentication Process), and sub-techniques. Includes detection indicators and a rapid engagement cheatsheet.

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Social engineering attack techniques beyond email phishing for authorized red team and physical penetration testing engagements. Covers pretexting methodology (persona creation, authority and urgency psychological triggers, rapport building), vishing (voice phishing via caller ID spoofing, IVR system exploitation, VoIP infrastructure setup with Twilio/Asterisk), smishing (SMS-based phishing, carrier gateway abuse, short code impersonation), physical social engineering (tailgating and piggybacking, RFID badge cloning with Proxmark3, lock picking and bypass, dumpster diving for sensitive documents), USB drop attacks (Rubber Ducky keystroke injection, Bash Bunny multi-vector payloads, O.MG cable covert implants, BadUSB firmware attacks), watering hole attack planning and execution, and OSINT-driven targeting (LinkedIn harvesting, organizational chart reconstruction, employee pattern analysis). Integrates with the Social Engineering Toolkit for attack automation, Proxmark3 for RFID/NFC cloning, USB Rubber Ducky and Bash Bunny for physical payload delivery, and BeEF for browser exploitation. Maps to MITRE ATT&CK T1598 (Phishing for Information), T1566 (Phishing), T1091 (Replication Through Removable Media), and T1189 (Drive-by Compromise). All techniques require explicit written authorization and defined rules of engagement.

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Submit compact ProteomeXchange PROXI requests for datasets, libraries, peptidoforms, proteins, PSMs, spectra, and USI examples. Use when a user wants concise PROXI summaries

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This skill should be used when the user asks to "remove AI writing patterns", "humanize this text", "make this sound more natural", "remove AI-generated traces", "fix robotic writing", or needs to eliminate AI writing patterns from prose. Supports both English and Chinese text. Based on Wikipedia's "Signs of AI writing" guide, detects and fixes inflated symbolism, promotional language, superficial -ing analyses, vague attributions, AI vocabulary, negative parallelisms, and excessive conjunctive phrases.

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Okta-as-IdP red-team attack chain — tenant discovery, user enumeration (multiple vectors), authentication flow analysis (factors enumeration, push-notification fatigue, SMS bypass), password spray with lockout discipline, Okta-specific phishing primitives (kits, FastPass abuse, OIDC redirect_uri tampering), MFA enumeration, post-compromise admin API surface. Many enterprise orgs use Okta instead of (or alongside) Entra ID. Distinct endpoints, distinct rate-limiting, distinct factor flows. Use when recon shows `<tenant>.okta.com`, `<tenant>.okta-emea.com`, `<tenant>.oktapreview.com`, or autodiscover-style records pointing at Okta IdP.

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Hunt MFA / 2FA bypass — 7 distinct patterns. (1) MFA not enforced on sensitive endpoints (password change, email change accept without MFA challenge), (2) MFA-step skip via direct navigation to post-login URL, (3) MFA-token replay (same code accepted twice), (4) brute-force the 6-digit OTP without rate limit (10^6 attempts at server speed), (5) race condition on OTP validation, (6) recovery-code dump via /api/me, (7) backup factor downgrade (SMS factor with no rate limit). Plus the chain: cookie theft + password oracle + no step-up = ATO without MFA challenge. Detection: trace auth flow in Burp, find every state transition, check if MFA is middleware-gated vs per-endpoint, check OTP entropy and rate limit on OTP-validate. Validate: attacker session reaching post-MFA state. Use when hunting auth bypass, MFA flows, chaining primitives toward ATO.

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