Configure DNS zones and records. Manage Route53, Cloud DNS, and self-hosted DNS. Use when setting up DNS infrastructure.
Skills in this repository
BagelHole/DevOps-Security-Agent-Skills - Page 3
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Configure load balancers and traffic distribution. Implement health checks and SSL termination. Use when distributing traffic across servers.
Configure nginx and Traefik as reverse proxies. Implement SSL termination and routing. Use when setting up application gateways.
Implement Istio and Linkerd service meshes. Configure mTLS, traffic management, and observability. Use when managing microservices communication.
Build reactive backends with Convex functions, schema validation, auth integration, and deployment workflows. Use when building real-time apps with type-safe server functions and automatic caching.
Build and operate apps on Firebase using Auth, Firestore, Cloud Functions, and Hosting. Use when building mobile/web backends with managed services, real-time data sync, or serverless APIs.
Deploy frontend and full-stack apps on Vercel with previews, edge functions, environment promotion, and production guardrails. Use when shipping Next.js, SvelteKit, or static sites with zero-config CI/CD.
System administration for Linux servers. Manage packages, services, and system configuration. Use when administering Linux systems.
Optimize Linux system performance. Configure kernel parameters, analyze bottlenecks, and tune resources. Use when improving system performance.
Configure SSH servers and clients securely. Manage keys, tunnels, and config files. Use when setting up secure remote access.
Create and manage systemd services and timers. Configure service dependencies and resource limits. Use when managing system services.
Manage users, groups, and permissions on Linux systems. Configure sudo and access controls. Use when managing system access.
Administer Windows Server systems. Manage IIS, Active Directory, and PowerShell automation. Use when administering Windows infrastructure.
Implement backup and recovery strategies. Configure rsync, Restic, and cloud backups. Use when designing data protection solutions.
Manage block storage volumes and LVM. Configure cloud block storage and local disks. Use when managing disk storage.
Configure NFS servers and clients. Implement network file sharing for Linux systems. Use when setting up shared storage.
Configure object storage with S3, GCS, and MinIO. Implement lifecycle policies and access controls. Use when managing object storage.
Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.
Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.
Run structured AI red team exercises for jailbreak resistance, data exfiltration risk, harmful output controls, and agent tool abuse resilience.
Secure LLM-powered applications with input validation, output controls, tenant isolation, and abuse prevention.
Secure Model Context Protocol (MCP) servers with transport encryption, tool authorization, input validation, and audit logging for safe AI agent integrations.
Secure the AI model supply chain with artifact signing, provenance attestation, SBOM workflows, dependency controls, and trusted model promotion.
Defend AI systems against prompt injection and indirect prompt attacks using input controls, tool permissions, output validation, and isolation boundaries.
Harden Windows servers per security baselines and CIS benchmarks. Configure Group Policy, Windows Defender, and security features. Use when securing Windows Server environments.
Configure iptables, nftables, and cloud firewalls. Implement network segmentation and traffic filtering. Use when securing network perimeters or implementing security zones.
Manage SSL/TLS certificates with Let's Encrypt and internal PKI. Configure secure HTTPS, certificate renewal, and cipher suites. Use when implementing secure communications.
Configure WireGuard, OpenVPN, and cloud VPNs. Implement secure remote access and site-to-site connectivity. Use when setting up secure network tunnels.
Deploy and tune Web Application Firewalls. Configure rules for OWASP Top 10 protection. Use when protecting web applications from common attacks.
Implement zero-trust network architecture. Configure identity-based access, micro-segmentation, and continuous verification. Use when implementing modern security architectures.
Handle security incidents with IR playbooks and procedures. Implement detection, containment, eradication, and recovery processes. Use when responding to security events or building incident response capabilities.
Conduct threat modeling using STRIDE methodology. Identify threats, assess risks, and design security controls. Use when designing secure systems or assessing application security.
Generate, sign, and verify SBOMs and provenance attestations to secure the software supply chain. Use when implementing SLSA controls, artifact trust policies, or compliance evidence for releases.
Detect, respond to, and prevent software supply chain attacks on package registries, container images, and CI/CD pipelines with lockfile auditing, provenance verification, and emergency response playbooks.
Store and rotate secrets in AWS Secrets Manager. Configure automatic rotation, access policies, and application integration. Use when managing secrets in AWS environments or requiring automatic credential rotation.
Manage secrets and certificates in Azure Key Vault. Configure access policies, integrate with Azure services, and implement secure secret management. Use when managing secrets in Azure environments.
Secure secrets in Google Cloud Secret Manager. Configure IAM policies, integrate with GKE, and manage secret versions. Use when managing secrets in GCP environments.
Secure OpenClaw deployments with preflight hardening checks, CI/CD guardrails, container runtime restrictions, and post-deploy verification. Use when shipping OpenClaw with Docker, Kubernetes, or automated release pipelines.
Set up infrastructure for fine-tuning LLMs with QLoRA, LoRA, and full fine-tuning using Hugging Face TRL, Axolotl, and distributed training with DeepSpeed or FSDP. Covers dataset prep, training runs, and model export.
Auto-scale LLM inference clusters on Kubernetes using KEDA, custom GPU metrics, and horizontal pod autoscaling. Handle traffic spikes, implement queue-based scaling, and optimize cost with spot instances for AI workloads.