Pre-cleanup snapshot - all current files

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Co-Authored-By: Claude <noreply@anthropic.com>

modules/shhh/core/llm_analyzer.py

@@ -0,0 +1,44 @@
+import requests
+import json
+
+class LLMAnalyzer:
+    """Analyzes text for secrets using a local LLM via Ollama."""
+
+    def __init__(self, endpoint: str, model: str, system_prompt: str):
+        self.endpoint = endpoint
+        self.model = model
+        self.system_prompt = system_prompt
+
+    def analyze(self, text: str) -> dict:
+        """
+        Sends text to the Ollama API for analysis and returns a structured JSON response.
+
+        Returns:
+            A dictionary like:
+            {
+                "secret_found": bool,
+                "secret_type": str,
+                "confidence_score": float,
+                "severity": str
+            }
+            Returns a default "not found" response on error.
+        """
+        prompt = f"Log entry: \"{text}\"\n\nAnalyze this for secrets and respond with only the required JSON."
+        payload = {
+            "model": self.model,
+            "system": self.system_prompt,
+            "prompt": prompt,
+            "format": "json",
+            "stream": False
+        }
+        try:
+            response = requests.post(self.endpoint, json=payload, timeout=15)
+            response.raise_for_status()
+            # The response from Ollama is a JSON string, which needs to be parsed.
+            analysis = json.loads(response.json().get("response", "{}"))
+            return analysis
+        except (requests.exceptions.RequestException, json.JSONDecodeError) as e:
+            print(f"[ERROR] LLMAnalyzer failed: {e}")
+            # Fallback: If LLM fails, assume no secret was found to avoid blocking the pipeline.
+            return {"secret_found": False}
+