The Fine Print

from pydantic import BaseModel, Field
from langchain_openai import ChatOpenAI
class IaCScanResult(BaseModel):
    has_violations: bool = Field(description="True if security violations exist")
    violations: list[str] = Field(description="List of detected policy violations")
    remediated_code: str = Field(description="Corrected Terraform code with fixes applied")
def analyze_and_remediate_terraform(tf_code: str) -> IaCScanResult:
    llm = ChatOpenAI(model="gpt-4o", temperature=0)
    structured_llm = llm.with_structured_output(IaCScanResult)
    prompt = f"""
You are a Cloud Security Engineering Agent. Analyze the following Terraform code for CIS AWS Benchmark violations.
If violations are found, fix them while maintaining original resource functionality.
TERRAFORM CODE:
{tf_code}
"""
    return structured_llm.invoke(prompt)
if __name__ == "__main__":
    bad_tf = """
resource "aws_db_instance" "default" {
allocated_storage   =10
engine        = "mysql"
engine_version    = "5.7"
instance_class    = "db.t3.micro"
name         = "mydb"
username= "admin"
password       = "Password123!"
publicly_accessible  = true
storage_encrypted   = false
}
"""
    result = analyze_and_remediate_terraform(bad_tf)
    print(f"Violations Found: {result.violations}\n")
    print("Remediated Terraform Code:\n")
    print(result.remediated_code)