PLEASE DO NOT SPAM THE QUESTION I WILL AUTOMATICALLY DISLIKE IT (THANKS)

Build a script (Python) that reads the saved csv called RiskResults.csv.This requires using a matrix-like data structure (using a dictionary) to store the various data in a permeant file.

code:

# Define a mapping of severity and probability to threat value

threat_map = {

"Emergency": {"Frequent": 16, "Probable": 14, "Unlikely": 11, "Rare": 8},

"Major": {"Frequent": 14, "Probable": 11, "Unlikely": 8, "Rare": 5},

"Moderate": {"Frequent": 11, "Probable": 8, "Unlikely": 5, "Rare": 2},

"Minor": {"Frequent": 5, "Probable": 2, "Unlikely": 1, "Rare": 0}

}

# Initialize a list to store the threats information

threats = []

# Open the CSV file and read the data into a list of dictionaries

with open("RiskResults.csv") as file:

# Skip the header line

next(file)

for line in file:

parts = line.strip().split(",")

# Unpack the data into separate variables

ID, start_time, end_time, description, severity, probability = parts

# Calculate the threat value based on the mapping

threat_value = threat_map[severity][probability]

# Create a dictionary to store the threat information

threat = {

"ID": ID,

"start_time": start_time,

"end_time": end_time,

"description": description,

"severity": severity,

"probability": probability,

"threat_value": threat_value

}

# Add the threat information to the list

threats.append(threat)

# Iterate over the list of threats and output a recommendation for each threat

for threat in threats:

threat_value = threat["threat_value"]

if threat_value

# Threat value should not be less than or equal to 0

print("Logging Error - check the data provided as this threat value is invalid.")

elif threat_value

print("Minor issue likely, increasing security is not recommended due to costs involved")

elif threat_value

print("Issue will require increase in security and access controls. Adding to Backlog for further planning.")

else:

print("Major bug or issue - sending email to sysadmin, infosec chief, and IT manager.")

RiskResults.csv

ID Start time Completion time Provide a "Description of the Risk" Select its severity Select its Probability Category 1 1/7/2023 12:03 1/7/2023 12:11 Internal employee sabotaging or leaking confidential data Major Unlikely People 2 1/12/2023 9:51 1/12/2023 9:54 Sensitive data over home network (potentially unsecured) Major Frequent Network 3 1/12/2023 10:16 1/12/2023 10:16 There is no security system protecting the house. Moderate Unlikely Physical 4 1/12/2023 10:13 1/12/2023 10:16 Natural disaster in florida Emergency Frequent Disaster 5 1/12/2023 10:16 1/12/2023 10:16 Hurricane Emergency Likely Disaster 6 1/12/2023 10:16 1/12/2023 10:16 Natural disaster Moderate Unlikely Disaster 7 1/12/2023 10:16 1/12/2023 10:16 Hurricane Emergency Unlikely Disaster 8 1/12/2023 10:16 1/12/2023 10:16 Baseball smashing through a window Minor Unlikely Physical 9 1/12/2023 10:16 1/12/2023 10:26 Building Maintenance Major Unlikely Maintenance 10 1/12/2023 10:12 1/12/2023 10:29 Flooding Emergency Probable Disaster

- Create Severity and Probability Dictionaries - Read CSV file into list of dictionaries - Using DictReader with csv library - Loop through above (for) and check values for severity and probability - display message for row based on total from values - Calculates a value based on the impact and probability - Emergency, Frequent = 16 to - Minor, Unlikely =1 - Recommend a dictionary here but can use if/elif/else or function calls (dictionary might look like:) Probability ={ "Frequent" : 16, "Probable": 14} Severity ={ "Emergency" } - Check that value by category with - the severity - the probability - Can use dictionary here (category: value) or scalar variables (or no variables if just evaluating the condition) - Displays a recommendation of action based on the value of the new threats added - Generic Recommendations (values don't matter - use what you think would be an emergency): - 0 or less: "Logging Error - check the data provided as this threat value is invalid." - between 0 and 4: "Minor issue likely, increasing security is not recommended due to costs involved" - between 5 and 15: "Issue will require increase in security and access controls. Adding to Backlog for further planning." - 16+: "Maior bug or issue - sending email to sysadmin, infosec chief. and IT manager." - Create Severity and Probability Dictionaries - Read CSV file into list of dictionaries - Using DictReader with csv library - Loop through above (for) and check values for severity and probability - display message for row based on total from values - Calculates a value based on the impact and probability - Emergency, Frequent = 16 to - Minor, Unlikely =1 - Recommend a dictionary here but can use if/elif/else or function calls (dictionary might look like:) Probability ={ "Frequent" : 16, "Probable": 14} Severity ={ "Emergency" } - Check that value by category with - the severity - the probability - Can use dictionary here (category: value) or scalar variables (or no variables if just evaluating the condition) - Displays a recommendation of action based on the value of the new threats added - Generic Recommendations (values don't matter - use what you think would be an emergency): - 0 or less: "Logging Error - check the data provided as this threat value is invalid." - between 0 and 4: "Minor issue likely, increasing security is not recommended due to costs involved" - between 5 and 15: "Issue will require increase in security and access controls. Adding to Backlog for further planning." - 16+: "Maior bug or issue - sending email to sysadmin, infosec chief. and IT manager