'security-hardening' 검색 결과

Apply Odylith security-hardening guidance to bounded product changes.

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AI 에이전트가 외부 정보를 읽고 도구나 파일을 조작할 때의 보안 대책을 정리합니다. 권한, 저장 경로, 접속 대상, 인증 정보 처리를 검토하고 실제 동작으로 검증합니다.

• 에이전트의 보안 대책 검토
• 사용자와 작업 영역 간 데이터 격리 확인
• 인증 정보 정리와 출력 제한 검증

Plan security controls for LLM applications and AI agents, covering malicious instructions, data leakage, model tampering, and API access. Includes guidance and code examples for filtering outputs, enforcing permissions, isolating networks, and recording audit events.

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• Reviewing defenses against prompt injection in AI agents
• Filtering personal information from LLM responses
• Designing authentication and rate limits for LLM APIs

Strengthen LDAP and Active Directory services by reviewing encrypted connections, signing, channel binding, access controls, and audit logging. Use the guidance to organize security settings, validate them in a test environment, and document implementation evidence.

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• Reviewing LDAP or Active Directory security settings
• Organizing encrypted connections and authentication protections
• Checking audit logging and monitoring arrangements

Audit AWS, Azure, and GCP configurations against CIS Benchmarks, security configuration guidelines. Use automated scan results to identify failed checks, prioritize fixes, report compliance by area, and establish ongoing monitoring for configuration changes.

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• Running an initial cloud security configuration audit
• Preparing CIS-related evidence for SOC 2 or ISO 27001 audits
• Prioritizing fixes for failed security checks

Develop security design improvements from vulnerability reports, incident documents, source code, or scan results. Compare architectural options with before-and-after diagrams, engineering tradeoffs, and migration plans to support a concrete design decision.

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• Find structural causes shared by several vulnerabilities
• Compare security architecture options and costs
• Explain proposed changes with before-and-after diagrams

Develop security design improvements from vulnerability reports, incident documents, source code, or scan results. Compare architectural options with before-and-after diagrams, engineering tradeoffs, and migration plans to support a concrete design decision.

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• Find structural causes shared by several vulnerabilities
• Compare security architecture options and costs
• Explain proposed changes with before-and-after diagrams

Application security covering input validation, auth, headers, secrets management, and dependency auditing

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AIDefence security layer with prompt injection blocking, input validation, sandboxed execution, output sanitization, and STRIDE threat modeling.

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Coordinate multi-layer security scanning and hardening across application, infrastructure, and compliance controls.

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Harden OpenClaw self-hosted environments with baseline host controls, auth tightening, secret handling, network segmentation, and safe update/rollback workflows. Use when deploying OpenClaw in home labs, startups, or production-like local AI infrastructure.

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Harden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks. Covers input validation, output filtering, access control, model API security, and compliance controls for production AI systems.

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VPS 安全加固自动化 Skill。通过 SSH 登录 VPS 并执行完整的安全策略配置。 触发场景： - "加固VPS安全"、"VPS安全配置"、"新VPS初始化" - "配置SSH安全"、"修改SSH端口"、"禁用root密码登录" - "VPS安全加固"、"服务器安全设置"、"hardening" 功能（7招安全加固）： 1. 创建 sudo 用户，禁用 root 密码登录 2. 修改 SSH 端口（支持 Ubuntu 不同版本） 3. Fail2ban 自动安装配置 4. SSH 密钥登录支持 5. SSH 登录通知（可选） 6. UFW 防火墙配置 7. Docker 安全提醒 Author: github.com/wlzh Version: 1.0.0

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Reduces attack surface across OS, container, cloud, network, and database layers using CIS Benchmarks and zero-trust principles. Use when hardening production infrastructure, meeting compliance requirements, or implementing defense-in-depth security.

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Harden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks.

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REST API security hardening with authentication, rate limiting, input validation, security headers. Use for production APIs, security audits, defense-in-depth, or encountering vulnerabilities, injection attacks, CORS issues.

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Ultimate guide for designing, building, and security-hardening modern AI Tools/Bots via Model Context Protocol (MCP v1.x) in TypeScript and Python / Panduan utama merancang, membangun, dan mengamankan AI Tools/Bots modern melalui Model Context Protocol (MCP) dalam TypeScript dan Python.

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Develop evidence-backed structural and architectural security hardening proposals from vulnerability disclosures, supplied findings, incident or assessment documents, source code, or a completed Codex Security scan. Use when a user asks for systemic improvements, alternatives beyond per-finding patches, before-and-after security architecture views, engineering tradeoff analysis, or an implementation-ready plan for a selected hardening option. Also use automatically after a Codex Security scan with reportable findings when the top-level scan workflow requests final-report hardening guidance.

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Use when bounded Odylith product changes touch security posture, trust, provenance, or hardening guidance.

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Audit and harden VPS security — fail2ban, SSH hardening, firewall setup

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Harden LDAP directory services against common attacks including credential harvesting, LDAP injection, anonymous binding, and channel binding bypass. Covers LDAPS enforcement, channel binding, LDAP si

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This skill details how to conduct cloud security audits using Center for Internet Security benchmarks for AWS, Azure, and GCP. It covers interpreting CIS Foundations Benchmark controls, running automated assessments with tools like Prowler and ScoutSuite, remediating failed controls, and maintaining continuous compliance monitoring against CIS v5 for AWS, v4 for Azure, and v4 for GCP.

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Harden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks.

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Coordinate multi-layer security scanning and hardening across application, infrastructure, and compliance controls.

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