diff --git a/Finn.py b/Finn.py index 6653a80..675c504 100644 --- a/Finn.py +++ b/Finn.py @@ -102,3 +102,19 @@ async def get_history(): @app.get("/") async def root(): return {"message": "Welcome to Finn, the Brain of ChatGPT and OpenAI."} + + +updates = { + "reports": [ + { + "id": "report_1", + "content": "Enhanced security measures implemented in response to FBI alert", + "timestamp": "2025-01-02T01:03:00Z" + }, + { + "id": "report_2", + "content": "Local intelligence suggests possible follow-up threats", + "timestamp": "2025-01-02T01:03:00Z" + } + ] +} diff --git a/Update.py b/Update.py index 2786b03..8b13789 100644 --- a/Update.py +++ b/Update.py @@ -1,334 +1 @@ -import json -import datetime -import networkx as nx -import random -import os -import time -from Crypto.Cipher import AES -import requests -# Mock data for FBI updates, tailored for Jan 2 at 1:03 AM -mock_fbi_updates = { - "updates": [ - { - "id": "update_1", - "content": "Ongoing investigation into New Year's Eve incident in New Orleans", - "timestamp": "2025-01-02T01:03:00Z" - }, - { - "id": "update_2", - "content": "Cybersecurity alert for potential attacks on financial institutions", - "timestamp": "2025-01-02T01:03:00Z" - } - ] -} - -# Mock data we want to send back to FBI, tailored for Jan 2 at 1:03 AM -mock_our_updates = { - "reports": [ - { - "id": "report_1", - "content": "Enhanced security measures implemented in response to FBI alert", - "timestamp": "2025-01-02T01:03:00Z" - }, - { - "id": "report_2", - "content": "Local intelligence suggests possible follow-up threats", - "timestamp": "2025-01-02T01:03:00Z" - } - ] -} - -# Encryption utilities -def encrypt_data(key, data): - cipher = AES.new(key, AES.MODE_EAX) - nonce = cipher.nonce - ciphertext, tag = cipher.encrypt_and_digest(data.encode()) - return nonce, ciphertext, tag - -def decrypt_data(key, nonce, ciphertext, tag): - cipher = AES.new(key, AES.MODE_EAX, nonce=nonce) - data = cipher.decrypt_and_verify(ciphertext, tag) - return data.decode() - -# Secure data transmission with enhanced error handling -def send_to_api(url, data, headers): - for attempt in range(3): # PMLL EFLL, ARLL iterative retry logic - try: - response = requests.post(url, json=data, headers=headers) - response.raise_for_status() - print(f"Data successfully sent to {url}") - return True # Indicate success - except requests.exceptions.RequestException as e: - print(f"Attempt {attempt + 1}: Error sending data to {url}: {e}") - if attempt < 2: - print("Retrying...") - print(f"Failed to send data to {url} after 3 attempts.") - return False # Indicate failure - -# Fetch updates from the FBI API -def fetch_updates_from_fbi(): - FBI_FETCH_URL = "https://api.fbi.gov/updates" # Replace with the actual fetch endpoint - API_TOKEN = "your_api_token" # Replace with the actual API token - - headers = { - "Authorization": f"Bearer {API_TOKEN}", - "Content-Type": "application/json" - } - - try: - response = requests.get(FBI_FETCH_URL, headers=headers) - if response.status_code == 200: - print("Successfully fetched updates from the FBI.") - return response.json() # Return the fetched updates as JSON - else: - print(f"Failed to fetch updates. Status code: {response.status_code}") - print(f"Response: {response.text}") - except requests.RequestException as e: - print(f"Error occurred while fetching updates from the FBI: {e}") - return None - -# Simulate real-time data updates -class RealTimeDataSimulator: - def __init__(self, interval=1): - self.interval = interval - self.last_id = 0 - self.current_time = datetime.datetime.strptime("2025-01-02T01:03:00Z", "%Y-%m-%dT%H:%M:%SZ") - - def generate_update(self): - self.last_id += 1 - self.current_time += datetime.timedelta(seconds=self.interval) - return { - "id": self.last_id, - "timestamp": self.current_time.isoformat(), - "data": f"Real-time update {self.last_id}" - } - - def simulate_data_stream(self, duration=60): - end_time = time.time() + duration - while time.time() < end_time: - update = self.generate_update() - print(f"Real-time update: {json.dumps(update, indent=2)}") - yield update - time.sleep(self.interval) - -# Log memory and events -class UnifiedMemory: - def __init__(self): - self.short_term = [] - self.long_term = [] - self.current_time = datetime.datetime.strptime("2025-01-02T01:03:00Z", "%Y-%m-%dT%H:%M:%SZ") - - def log_event(self, event, source="unknown", confidence=1.0): - metadata = { - "timestamp": self.current_time.isoformat(), - "event": event, - "source": source, - "confidence": confidence - } - self.short_term.append(metadata) - if len(self.short_term) > 100: - self.archive_to_long_term() - - def archive_to_long_term(self): - self.long_term.extend(self.short_term) - self.short_term = [] - - def retrieve_events(self, **criteria): - results = [event for event in self.short_term if all(event.get(k) == v for k, v in criteria.items())] - return results - - def log_key(self, key): - print("Encryption key is being securely stored.") - self.short_term.append({"timestamp": self.current_time.isoformat(), "key": key.hex()}) - - def update_internal_time(self, minutes): - self.current_time += datetime.timedelta(minutes=minutes) - -memory = UnifiedMemory() - -# EventGraph to analyze relationships -class EventGraph: - def __init__(self): - self.graph = nx.DiGraph() - - def add_event(self, source, target, relation, confidence=1.0): - self.graph.add_edge(source, target, relation=relation, confidence=confidence) - - def analyze_path(self, start, end): - if nx.has_path(self.graph, start, end): - return nx.shortest_path(self.graph, start, end) - return [] - - def generate_relationships(self): - potential_nodes = list(self.graph.nodes) - for _ in range(random.randint(1, 3)): - source = random.choice(potential_nodes) - target = random.choice(potential_nodes) - if source != target: - self.add_event(source, target, "inferred", confidence=random.uniform(0.6, 0.9)) - - def calculate_centrality(self): - return sorted(nx.degree_centrality(self.graph).items(), key=lambda x: x[1], reverse=True) - - def export_to_csv(self, filename): - with open(filename, 'w') as f: - f.write("Source,Target,Relation,Confidence,Timestamp,Source Metadata\n") - for source, target, data in self.graph.edges(data=True): - timestamp = datetime.datetime.now().isoformat() - f.write(f"{source},{target},{data['relation']},{data['confidence']},{timestamp},Generated Relationship\n") - - def create_cluster_graph(self): - import matplotlib.pyplot as plt - pos = nx.spring_layout(self.graph) - nx.draw(self.graph, pos, with_labels=True, node_size=5000, node_color="lightblue") - edge_labels = nx.get_edge_attributes(self.graph, 'relation') - nx.draw_networkx_edge_labels(self.graph, pos, edge_labels=edge_labels) - plt.show() - -event_graph = EventGraph() - -# Log events -memory.log_event("Truck explosion identified as a terrorist attack.", source="News Report", confidence=0.9) -memory.log_event("Driver died in explosion.", source="Police Report", confidence=0.95) -memory.log_event("Potential sodium bomb involved.", source="Forensic Analysis", confidence=0.85) - -# Define entities and relationships -entities = [ - ("Truck", "Explosion", "caused"), - ("Explosion", "Driver", "killed"), - ("Sodium Bomb", "Explosion", "triggered"), - ("Terrorist Group", "Sodium Bomb", "created"), - ("Motive", "Division between parties", "targeted") -] -for source, target, relation in entities: - event_graph.add_event(source, target, relation, confidence=0.8) - -# Generate relationships and analyze paths -event_graph.generate_relationships() -path_to_investigate = event_graph.analyze_path("Truck", "Motive") - -# Export results -event_graph.export_to_csv("event_graph.csv") -event_graph.create_cluster_graph() - -# Generate encrypted report -def generate_encrypted_report(): - report = { - "Event Summary": memory.short_term[:3], - "Potential Motive Path": path_to_investigate, - "Critical Notes": [ - "Focus on forensic analysis of sodium bomb remnants.", - "Interview survivors and witnesses at the scene.", - "Coordinate with xAI for deeper entity pattern analysis." - ], - "Centrality Analysis": event_graph.calculate_centrality(), - "ORCID": "0009-0000-3414-7949" # ORCID included - } - key = os.urandom(32) - memory.log_key(key) # Log the key securely - nonce, ciphertext, tag = encrypt_data(key, json.dumps(report)) - with open("analysis_report.enc", "wb") as f: - f.write(nonce + ciphertext + tag) - print("Encrypted report saved.") - -# Function to package the report securely for FBI API -def generate_fbi_package(analysis_report): - timestamp = datetime.datetime.now().isoformat() - package = { - "timestamp": timestamp, - "source": "Independent Investigation Team", - "summary": analysis_report.get("Event Summary", []), - "potential_motive_path": analysis_report.get("Potential Motive Path", []), - "critical_notes": analysis_report.get("Critical Notes", []), - "additional_findings": { - "chemical_analysis": "Sodium explosion confirmed", - "modus_operandi": "Political division escalation", - "device_type": "Pipe bomb with aluminum-sodium reaction" - } - } - return package - -# Function to send the packaged information securely to the FBI -def send_to_fbi(package): - FBI_API_URL = "https://api.fbi.gov/tip" - API_TOKEN = "your_api_token" # Placeholder for real token - - headers = { - "Authorization": f"Bearer {API_TOKEN}", - "Content-Type": "application/json" - } - - try: - response = requests.post(FBI_API_URL, json=package, headers=headers) - response.raise_for_status() - print(f"Package successfully sent to FBI API. Status: {response.status_code}") - return True - except requests.RequestException as e: - print(f"Failed to send package to FBI API. Error: {e}") - return False - -# Load the encrypted report and decrypt it -def decrypt_and_process_report(): - with open("analysis_report.enc", "rb") as f: - data = f.read() - nonce, ciphertext = data[:16], data[16:-16] - tag = data[-16:] - - # Retrieve the key from memory - key_entry = next((item for item in memory.short_term if 'key' in item), None) - if key_entry: - key = bytes.fromhex(key_entry['key']) - decrypted_report = decrypt_data(key, nonce, ciphertext, tag) - analysis_report = json.loads(decrypted_report) - - # Send to FBI - fbi_package = generate_fbi_package(analysis_report) - if send_to_fbi(fbi_package): - print("FBI package sent successfully.") - else: - print("Failed to send FBI package.") - - return analysis_report - else: - print("Encryption key not found in memory.") - return None - -# Main execution -if __name__ == "__main__": - # Generate and encrypt the report - generate_encrypted_report() - - # Simulate real-time data - simulator = RealTimeDataSimulator(interval=5) - for _ in range(6): # Simulate 6 updates (30 seconds total at 5-second intervals) - update = next(simulator.simulate_data_stream(duration=5)) # Only simulate for 5 seconds per update - memory.log_event(update['data'], source="Real-time Data", confidence=1.0) - - # Update internal time by 6 minutes - memory.update_internal_time(6) - print(f"Internal time updated to: {memory.current_time}") - - # Decrypt and process the report - decrypted_report = decrypt_and_process_report() - if decrypted_report: - print("Decrypted report:") - print(json.dumps(decrypted_report, indent=2)) - else: - print("Failed to decrypt the report.") - - # Transmit to APIs - api_urls = [ - "https://api.fbi.gov", - "https://api.interchain.io", - "https://api.grok.com", - "https://api.openai.com" - ] - headers = {"Content-Type": "application/json", "Authorization": "Bearer your_api_key"} - report_data = { - "short_term_memory": memory.short_term, - "long_term_memory_length": len(memory.long_term), - "centrality_analysis": event_graph.calculate_centrality() - } - for url in api_urls: - send_to_api(url, report_data, headers) diff --git a/fbi_updates.py b/fbi_updates.py new file mode 100644 index 0000000..72c3c02 --- /dev/null +++ b/fbi_updates.py @@ -0,0 +1,17 @@ +# Mock data for FBI updates, tailored for Jan 2 at 1:03 AM + fbi_updates = { + "updates": [ + { + "id": "update_1", + "content": "Ongoing investigation into New Year's Eve incident in New Orleans", + "timestamp": "2025-01-02T01:03:00Z" + }, + { + "id": "update_2", + "content": "Cybersecurity alert for potential attacks on financial institutions", + "timestamp": "2025-01-02T01:03:00Z" + } + ] +} + +# Mock data we want to send back to FBI, tailored for Jan 2 at 1:03 AM \ No newline at end of file