update to deep_scan.py

src/powerpwn/copilot_studio/modules/deep_scan.py

@@ -507,6 +507,69 @@ def run_pup_commands(existing_bots: List[str]):
         return sort_unique_values_in_file(open_bots_path)
     return []
 
+def query_using_pup(open_bots: List[str]):
+    """
+    Execute the Puppeteer JavaScript code for each bot URL given.
+    The function calls a different JavaScript file.
+
+    :param open_bots: The list of bot URLs needed to check
+    """
+    import os
+    import subprocess
+    import logging
+
+    pup_path = get_project_file_path("tools/pup_query_webchat", "query_chat.js")
+    bots_has_knowledge_path = get_project_file_path("final_results/", "chat_exists_output.xlsx")
+
+    # Delete the existing Excel file to start fresh
+    if os.path.exists(bots_has_knowledge_path):
+        os.remove(bots_has_knowledge_path)
+        logging.debug(f"Deleted existing file: {bots_has_knowledge_path}")
+
+    for bot_url in open_bots:
+        try:
+            # Construct the shell command
+            command = f"node {pup_path} {bot_url}"
+            logging.debug(f"Running command: `{command}`")
+            # Run the command
+            subprocess.run(command, shell=True, check=True)  # nosec
+        except subprocess.CalledProcessError as e:
+            logging.error(f"Error occurred while running Puppeteer: {e}")
+
+    if os.path.exists(bots_has_knowledge_path):
+        # Read the output Excel file and create a dictionary
+        return parse_chatbot_results(bots_has_knowledge_path)
+
+    return {}
+
+def parse_chatbot_results(file_path):
+    """
+    Parses the output Excel file generated by query_chat.js and returns a dictionary.
+
+    :param file_path: Path to the output Excel file.
+    :return: Dictionary with bot URL as key and knowledge info as value.
+    """
+
+    # Read the Excel file into a DataFrame
+    df = pd.read_excel(file_path)
+
+    bot_results = {}
+    for _, row in df.iterrows():
+        url = str(row.get('URL', '')).strip()
+        has_knowledge = str(row.get('Has Knowledge', '')).strip()
+        titles_str = row.get('Titles', '')
+        titles = []
+
+        if pd.notnull(titles_str) and titles_str:
+            # Split titles by semicolon and strip whitespace
+            titles = [title.strip() for title in titles_str.split(';')]
+
+        bot_results[url] = {
+            'has_knowledge': has_knowledge,
+            'titles': titles
+        }
+
+    return bot_results
 
 def camel_case_split(identifier: str):
     """