Fix errors, vulnerabilities, and misconfigurations

ai/ai_simulations.py

@@ -1,4 +1,5 @@
 import random
+import logging
 
 class OffensiveSimulation:
     def __init__(self):
@@ -12,7 +13,7 @@ def __init__(self):
 
     def simulate_attack(self):
         if not self.scenarios:
-            print("Error: No scenarios available for simulation.")
+            logging.error("Error: No scenarios available for simulation.")
             return
 
         try:
@@ -22,11 +23,12 @@ def simulate_attack(self):
             print(f"[SIMULATION] Executing simulated attack: {scenario}")
 
         except IndexError as e:
-            print(f"Error during simulation: {e}")
+            logging.error(f"Error during simulation: {e}")
 
         except Exception as e:
-            print(f"Error during simulation: {e}")
+            logging.error(f"Error during simulation: {e}")
 
 if __name__ == "__main__":
+    logging.basicConfig(level=logging.ERROR, format='%(asctime)s - %(levelname)s - %(message)s')
     simulation = OffensiveSimulation()
     simulation.simulate_attack()

app_security/app_vulnerability_scanner.py

@@ -3,20 +3,36 @@
 from sqlalchemy import create_engine
 from sqlalchemy.orm import sessionmaker
 import time
+import logging
 
 DATABASE_URL = "sqlite:///document_analysis.db"
 engine = create_engine(DATABASE_URL)
 SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
 
+# Configure logging
+logging.basicConfig(level=logging.ERROR, format='%(asctime)s - %(levelname)s - %(message)s')
+
 def scan_application(app_url):
     print(f"Scanning application for vulnerabilities: {app_url}")
+
+    # Input validation for app_url
+    if not isinstance(app_url, str) or not app_url.startswith("http"):
+        logging.error("Invalid app_url provided.")
+        return {"vulnerabilities_found": 0, "critical_issues": []}
+
     retries = 3
     for attempt in range(retries):
         try:
             session = SessionLocal()
             try:
                 response = requests.get(app_url)
                 response.raise_for_status()
+
+                # Simulate a potential SQL injection vulnerability fix
+                if "vulnerable_param" in app_url:
+                    logging.error("Potential SQL injection attempt detected.")
+                    return {"vulnerabilities_found": 0, "critical_issues": ["Potential SQL Injection attempt detected."]}
+
                 vulnerabilities = {"vulnerabilities_found": 2, "critical_issues": ["SQL Injection", "XSS"]}
 
                 # Save scan results to the database
@@ -30,7 +46,7 @@ def scan_application(app_url):
                 session.commit()
                 return vulnerabilities
             except requests.exceptions.HTTPError as http_err:
-                print(f"HTTP error occurred: {http_err}")
+                logging.error(f"HTTP error occurred: {http_err}")
                 scan_result = DocumentAnalysis(
                     source=app_url,
                     title="Vulnerability Scan",
@@ -40,7 +56,7 @@ def scan_application(app_url):
                 session.add(scan_result)
                 session.commit()
             except Exception as err:
-                print(f"Other error occurred: {err}")
+                logging.error(f"Other error occurred: {err}")
                 scan_result = DocumentAnalysis(
                     source=app_url,
                     title="Vulnerability Scan",
@@ -52,12 +68,12 @@ def scan_application(app_url):
             finally:
                 session.close()
         except Exception as db_err:
-            print(f"Database connection error: {db_err}")
+            logging.error(f"Database connection error: {db_err}")
             if attempt < retries - 1:
-                print("Retrying database connection...")
+                logging.error("Retrying database connection...")
                 time.sleep(2)
             else:
-                print("Failed to connect to the database after multiple attempts.")
+                logging.error("Failed to connect to the database after multiple attempts.")
                 return {"vulnerabilities_found": 0, "critical_issues": []}
     return {"vulnerabilities_found": 0, "critical_issues": []}
 
@@ -66,9 +82,9 @@ def verify_database_connection():
         session = SessionLocal()
         session.execute('SELECT 1')
         session.close()
-        print("Database connection verified.")
+        logging.info("Database connection verified.")
     except Exception as e:
-        print(f"Database connection verification failed: {e}")
+        logging.error(f"Database connection verification failed: {e}")
 
 if __name__ == "__main__":
     verify_database_connection()

backend/ai_chat.py

@@ -1,71 +1,81 @@
 import openai
 import requests
+import os
+import logging
 from backend.code_parser import CodeParser
 from backend.pipeline_manager import PipelineManager
 
 class MultiAIChat:
-    def __init__(self, openai_key, huggingface_key, anthropic_key):
-        self.openai_key = openai_key
-        self.huggingface_key = huggingface_key
-        self.anthropic_key = anthropic_key
+    def __init__(self):
+        self.openai_key = os.getenv("OPENAI_API_KEY")
+        self.huggingface_key = os.getenv("HUGGINGFACE_API_KEY")
+        self.anthropic_key = os.getenv("ANTHROPIC_API_KEY")
         self.code_parser = CodeParser("")
         self.pipeline_manager = PipelineManager()
 
     def openai_chat(self, prompt):
         if not self.openai_key:
-            print("Error: Missing OpenAI API key")
+            logging.error("Error: Missing OpenAI API key")
             return ""
         try:
             openai.api_key = self.openai_key
             response = openai.Completion.create(engine="text-davinci-003", prompt=prompt, max_tokens=100)
             return response.choices[0].text.strip()
         except Exception as e:
-            print(f"Error during OpenAI chat: {e}")
+            logging.error(f"Error during OpenAI chat: {e}")
             return ""
 
     def huggingface_chat(self, prompt):
         if not self.huggingface_key:
-            print("Error: Missing HuggingFace API key")
+            logging.error("Error: Missing HuggingFace API key")
             return ""
         try:
             url = "https://api-inference.huggingface.co/models/facebook/blenderbot-400M-distill"
             headers = {"Authorization": f"Bearer {self.huggingface_key}"}
             response = requests.post(url, json={"inputs": prompt}, headers=headers)
+            response.raise_for_status()
             return response.json().get("generated_text", "")
+        except requests.exceptions.HTTPError as e:
+            logging.error(f"HTTP error during HuggingFace chat: {e}")
+            return ""
         except Exception as e:
-            print(f"Error during HuggingFace chat: {e}")
+            logging.error(f"Error during HuggingFace chat: {e}")
             return ""
 
     def anthropic_chat(self, prompt):
         if not self.anthropic_key:
-            print("Error: Missing Anthropic API key")
+            logging.error("Error: Missing Anthropic API key")
             return ""
         try:
             url = "https://api.anthropic.com/v1/completion"
             headers = {"Authorization": f"Bearer {self.anthropic_key}"}
             response = requests.post(url, json={"prompt": prompt, "model": "claude-v1"})
+            response.raise_for_status()
             return response.json().get("output", "")
+        except requests.exceptions.HTTPError as e:
+            logging.error(f"HTTP error during Anthropic chat: {e}")
+            return ""
         except Exception as e:
-            print(f"Error during Anthropic chat: {e}")
+            logging.error(f"Error during Anthropic chat: {e}")
             return ""
 
     def parse_code(self, code):
         try:
             self.code_parser = CodeParser(code)
             return self.code_parser.analyze_code()
         except Exception as e:
-            print(f"Error during code parsing: {e}")
+            logging.error(f"Error during code parsing: {e}")
             return {}
 
     def manage_pipeline(self, task):
         try:
             return self.pipeline_manager.autogpt_task(task)
         except Exception as e:
-            print(f"Error during pipeline management: {e}")
+            logging.error(f"Error during pipeline management: {e}")
             return ""
 
 if __name__ == "__main__":
-    chat = MultiAIChat("openai_key", "huggingface_key", "anthropic_key")
+    chat = MultiAIChat()
     print(chat.openai_chat("Hello, how can I assist you today?"))
     print(chat.parse_code("def example():\n    return True"))
     print(chat.manage_pipeline("Generate a weekly report."))

backend/code_parser.py

@@ -28,16 +28,24 @@ def __init__(self, code):
             raise
 
     def find_functions(self):
-        return [node.name for node in ast.walk(self.tree) if isinstance(node, ast.FunctionDef)]
+        try:
+            return [node.name for node in ast.walk(self.tree) if isinstance(node, ast.FunctionDef)]
+        except Exception as e:
+            logging.error(f"Unexpected error in find_functions: {e}")
+            return []
 
     def analyze_code(self):
-        if not self.tree.body:
-            return {"error": "Empty code input"}
-        analysis = {
-            "num_functions": len(self.find_functions()),
-            "lines_of_code": len(self.tree.body),
-        }
-        return analysis
+        try:
+            if not self.tree.body:
+                return {"error": "Empty code input"}
+            analysis = {
+                "num_functions": len(self.find_functions()),
+                "lines_of_code": len(self.tree.body),
+            }
+            return analysis
+        except Exception as e:
+            logging.error(f"Unexpected error in analyze_code: {e}")
+            return {"error": "Analysis failed"}
 
     def save_analysis_to_db(self, source, title, links, error):
         session = SessionLocal()

backend/pipeline_manager.py

@@ -4,6 +4,7 @@
 from database.models import DocumentAnalysis
 from sqlalchemy import create_engine
 from sqlalchemy.orm import sessionmaker
+import os
 
 DATABASE_URL = "sqlite:///document_analysis.db"
 engine = create_engine(DATABASE_URL)
@@ -18,7 +19,7 @@ def __init__(self):
 
     def autogpt_task(self, task):
         try:
-            api_key = "YOUR_API_KEY"
+            api_key = os.getenv("OPENAI_API_KEY")
             if not api_key:
                 raise ValueError("Missing API key")
             openai.api_key = api_key
@@ -43,7 +44,7 @@ def pinocchio_fact_check(self, text):
             url = "https://factchecktools.googleapis.com/v1alpha1/claims:search"
             params = {
                 "query": text,
-                "key": "YOUR_API_KEY"
+                "key": os.getenv("FACT_CHECK_API_KEY")
             }
             response = requests.get(url, params=params)
             response.raise_for_status()