The Fine Print

from pydantic import BaseModel, Field
from langchain_openai import ChatOpenAI
class K8sAuditResult(BaseModel):
    is_secure: bool
    detected_risks: list[str]
    remediated_yaml: str
def audit_k8s_manifest(yaml_manifest: str) -> K8sAuditResult:
    llm = ChatOpenAI(model="gpt-4o", temperature=0)
    structured_llm = llm.with_structured_output(K8sAuditResult)
    prompt = f"Audit this Kubernetes manifest for security misconfigurations (e.g. privileged pods, hostPath mounts, cluster-admin bindings) and output corrected YAML:\n{yaml_manifest}"
    return structured_llm.invoke(prompt)
if __name__ == "__main__":
    bad_k8s = """
apiVersion: apps/v1
kind: Deployment
metadata:
  name: web-app
spec:
  template:
    spec:
      containers:
      - name: app
        image: nginx:latest
        securityContext:
          privileged: true
          runAsUser: 0
"""
    res = audit_k8s_manifest(bad_k8s)
    print(f"Is Secure: {res.is_secure}")
    print(f"Risks Identified: {res.detected_risks}")
    print("Remediated YAML:\n", res.remediated_yaml)