BagelHole/DevOps-Security-Agent-Skills - Seite 3

dns-management

Configure DNS zones and records. Manage Route53, Cloud DNS, and self-hosted DNS. Use when setting up DNS infrastructure.

Quellsprache: Englisch

load-balancing

Configure load balancers and traffic distribution. Implement health checks and SSL termination. Use when distributing traffic across servers.

Quellsprache: Englisch

reverse-proxy

Configure nginx and Traefik as reverse proxies. Implement SSL termination and routing. Use when setting up application gateways.

Quellsprache: Englisch

service-mesh

Implement Istio and Linkerd service meshes. Configure mTLS, traffic management, and observability. Use when managing microservices communication.

Quellsprache: Englisch

convex-backend

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.

Quellsprache: Englisch

firebase-app-platform

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.

Quellsprache: Englisch

vercel-deployments

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.

Quellsprache: Englisch

linux-administration

System administration for Linux servers. Manage packages, services, and system configuration. Use when administering Linux systems.

Quellsprache: Englisch

performance-tuning

Optimize Linux system performance. Configure kernel parameters, analyze bottlenecks, and tune resources. Use when improving system performance.

Quellsprache: Englisch

ssh-configuration

Configure SSH servers and clients securely. Manage keys, tunnels, and config files. Use when setting up secure remote access.

Quellsprache: Englisch

systemd-services

Create and manage systemd services and timers. Configure service dependencies and resource limits. Use when managing system services.

Quellsprache: Englisch

user-management

Manage users, groups, and permissions on Linux systems. Configure sudo and access controls. Use when managing system access.

Quellsprache: Englisch

windows-server

Administer Windows Server systems. Manage IIS, Active Directory, and PowerShell automation. Use when administering Windows infrastructure.

Quellsprache: Englisch

backup-recovery

Implement backup and recovery strategies. Configure rsync, Restic, and cloud backups. Use when designing data protection solutions.

Quellsprache: Englisch

block-storage

Manage block storage volumes and LVM. Configure cloud block storage and local disks. Use when managing disk storage.

Quellsprache: Englisch

nfs-storage

Configure NFS servers and clients. Implement network file sharing for Linux systems. Use when setting up shared storage.

Quellsprache: Englisch

object-storage

Configure object storage with S3, GCS, and MinIO. Implement lifecycle policies and access controls. Use when managing object storage.

Quellsprache: Englisch

ai-agent-security

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.

Quellsprache: Englisch

ai-coding-agent-guardrails

Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.

Quellsprache: Englisch

ai-red-teaming

Run structured AI red team exercises for jailbreak resistance, data exfiltration risk, harmful output controls, and agent tool abuse resilience.

Quellsprache: Englisch

llm-app-security

Secure LLM-powered applications with input validation, output controls, tenant isolation, and abuse prevention.

Quellsprache: Englisch

mcp-server-security

Secure Model Context Protocol (MCP) servers with transport encryption, tool authorization, input validation, and audit logging for safe AI agent integrations.

Quellsprache: Englisch

model-supply-chain-security

Secure the AI model supply chain with artifact signing, provenance attestation, SBOM workflows, dependency controls, and trusted model promotion.

Quellsprache: Englisch

prompt-injection-defense

Defend AI systems against prompt injection and indirect prompt attacks using input controls, tool permissions, output validation, and isolation boundaries.

Quellsprache: Englisch

windows-hardening

Harden Windows servers per security baselines and CIS benchmarks. Configure Group Policy, Windows Defender, and security features. Use when securing Windows Server environments.

Quellsprache: Englisch

firewall-config

Configure iptables, nftables, and cloud firewalls. Implement network segmentation and traffic filtering. Use when securing network perimeters or implementing security zones.

Quellsprache: Englisch

ssl-tls-management

Manage SSL/TLS certificates with Let's Encrypt and internal PKI. Configure secure HTTPS, certificate renewal, and cipher suites. Use when implementing secure communications.

Quellsprache: Englisch

vpn-setup

Configure WireGuard, OpenVPN, and cloud VPNs. Implement secure remote access and site-to-site connectivity. Use when setting up secure network tunnels.

Quellsprache: Englisch

waf-setup

Deploy and tune Web Application Firewalls. Configure rules for OWASP Top 10 protection. Use when protecting web applications from common attacks.

Quellsprache: Englisch

zero-trust

Implement zero-trust network architecture. Configure identity-based access, micro-segmentation, and continuous verification. Use when implementing modern security architectures.

Quellsprache: Englisch

incident-response

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.

Quellsprache: Englisch

threat-modeling

Conduct threat modeling using STRIDE methodology. Identify threats, assess risks, and design security controls. Use when designing secure systems or assessing application security.

Quellsprache: Englisch

sbom-supply-chain

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.

Quellsprache: Englisch

supply-chain-attack-response

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.

Quellsprache: Englisch

aws-secrets-manager

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.

Quellsprache: Englisch

azure-keyvault

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.

Quellsprache: Englisch

gcp-secret-manager

Secure secrets in Google Cloud Secret Manager. Configure IAM policies, integrate with GKE, and manage secret versions. Use when managing secrets in GCP environments.

Quellsprache: Englisch

openclaw-deployment-hardening

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.

Quellsprache: Englisch

llm-fine-tuning

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.

Quellsprache: Englisch

llm-inference-scaling

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.

Quellsprache: Englisch