Security-focused review of AI-generated or AI-assisted code. Use when reviewing code produced by AI coding assistants, auditing AI-generated patches, verifying AI-assisted contributions before merge, or when a review needs to account for failure modes specific to AI code generation.
Configure Kubernetes network security including host access restrictions, network policies, port management, and connectivity requirements. Use when writing, reviewing, or auditing pod specs, Services, NetworkPolicies, or NetworkAttachmentDefinitions.
Secure AI-powered products and infrastructure. Use when integrating LLM APIs, deploying model-serving infrastructure, building agent workflows, connecting MCP servers, or reviewing AI system architecture for security gaps.
Enforce standard authentication for external data source connections. Use when integrating, configuring, or reviewing connections from AI systems to external databases, APIs, or data services.
Harden container images and runtime configuration. Use when building, reviewing, or auditing Containerfiles, Dockerfiles, container compose files, or Kubernetes pod security settings.
Supply chain security audit using CLI vulnerability scanners, license compliance checks, and supply chain risk assessment. Use when auditing project dependencies for known CVEs, license concerns, and supply chain health.
Apply when reviewing or writing code that processes untrusted input, constructs queries or commands, or handles user-supplied data. Covers SQL, LDAP, OS command injection, prototype pollution, and general validation strategy.
Enforce logging of access to sensitive external data sources in AI systems. Use when designing, building, or reviewing audit and logging capabilities for AI systems accessing external databases or data services.