From c8d3d41575ffbacb57fb6e8845e7b7018bee0bbe Mon Sep 17 00:00:00 2001 From: Google AI Agent Date: Mon, 30 Mar 2026 23:09:57 +0000 Subject: [PATCH] feat: implement Phase 12 - Tirith Hardener --- agent/evolution/tirith_hardener.py | 53 ++++++++++++++++++++++++++++++ 1 file changed, 53 insertions(+) create mode 100644 agent/evolution/tirith_hardener.py diff --git a/agent/evolution/tirith_hardener.py b/agent/evolution/tirith_hardener.py new file mode 100644 index 000000000..7442606b5 --- /dev/null +++ b/agent/evolution/tirith_hardener.py @@ -0,0 +1,53 @@ +"""Phase 12: Automated Threat Modeling & Tirith Hardening. + +Continuous, autonomous security auditing and hardening of the infrastructure. +""" + +import logging +import json +from typing import List, Dict, Any +from agent.gemini_adapter import GeminiAdapter + +logger = logging.getLogger(__name__) + +class TirithHardener: + def __init__(self): + self.adapter = GeminiAdapter() + + def run_security_audit(self, infra_config: Dict[str, Any]) -> Dict[str, Any]: + """Performs a deep security audit of the infrastructure configuration.""" + logger.info("Performing Tirith security audit and threat modeling.") + + prompt = f""" +Infrastructure Configuration: +{json.dumps(infra_config, indent=2)} + +Please perform a 'Deep Scan' of this infrastructure configuration. +Simulate sophisticated cyber-attacks against 'The Nexus' and 'The Door'. +Identify vulnerabilities and generate 'Tirith Security Patches' to mitigate them. + +Format the output as JSON: +{{ + "threat_model": "...", + "vulnerabilities": [...], + "attack_simulations": [...], + "security_patches": [ + {{ + "component": "...", + "vulnerability": "...", + "patch_description": "...", + "implementation_steps": "..." + }} + ] +}} +""" + result = self.adapter.generate( + model="gemini-3.1-pro-preview", + prompt=prompt, + system_instruction="You are Timmy's Tirith Hardener. Your goal is to make the sovereign infrastructure impenetrable.", + thinking=True, + response_mime_type="application/json" + ) + + audit_data = json.loads(result["text"]) + return audit_data