chatgpt_all_cvss_scores.py

# ChatGPT prompt:
# i would like to create a code that would generate all possible combinations of CVSS scores and 
# output the configuration + calculated score in CVS format to STDOUT.
#  could you help me generate that code in python?

# Output:
import csv
import sys
from itertools import product
from cvss import CVSS3

# Define the possible values for each CVSS metric
attack_vector = ['N', 'A', 'L', 'P']
attack_complexity = ['L', 'H']
privileges_required = ['N', 'L', 'H']
user_interaction = ['N', 'R']
scope = ['U', 'C']
confidentiality_impact = ['N', 'L', 'H']
integrity_impact = ['N', 'L', 'H']
availability_impact = ['N', 'L', 'H']

# Create a CSV writer that writes to STDOUT
writer = csv.writer(sys.stdout)
writer.writerow(['Attack Vector', 'Attack Complexity', 'Privileges Required', 'User Interaction', 'Scope', 'Confidentiality Impact', 'Integrity Impact', 'Availability Impact', 'CVSS Score'])

# Generate all combinations of CVSS metrics
for av, ac, pr, ui, s, ci, ii, ai in product(attack_vector, attack_complexity, privileges_required, user_interaction, scope, confidentiality_impact, integrity_impact, availability_impact):
    # Calculate the CVSS score for the current combination of metrics
    vector = f'CVSS:3.1/AV:{av}/AC:{ac}/PR:{pr}/UI:{ui}/S:{s}/C:{ci}/I:{ii}/A:{ai}'
    score = CVSS3(vector).scores()[0]

    # Write the combination of metrics and the calculated score to STDOUT
    writer.writerow([av, ac, pr, ui, s, ci, ii, ai, score])

find_cvss_combinations.py

# ChatGPT prompt:
# Could we make another one: you run the python script and give it a 
# CVSS score as a command-line argument and it gives you all of the 
# possible combinations that produces that score

# Output
import csv
import sys
from itertools import product
from cvss import CVSS3

# Check if a CVSS score was provided as a command-line argument
if len(sys.argv) != 2:
    print(f'Usage: {sys.argv[0]} <cvss_score>')
    sys.exit(1)

# Parse the CVSS score
try:
    target_score = float(sys.argv[1])
except ValueError:
    print(f'Error: Invalid CVSS score "{sys.argv[1]}"')
    sys.exit(1)

# Define the possible values for each CVSS metric
attack_vector = ['N', 'A', 'L', 'P']
attack_complexity = ['L', 'H']
privileges_required = ['N', 'L', 'H']
user_interaction = ['N', 'R']
scope = ['U', 'C']
confidentiality_impact = ['N', 'L', 'H']
integrity_impact = ['N', 'L', 'H']
availability_impact = ['N', 'L', 'H']

# Create a CSV writer that writes to STDOUT
writer = csv.writer(sys.stdout)
writer.writerow(['Attack Vector', 'Attack Complexity', 'Privileges Required', 'User Interaction', 'Scope', 'Confidentiality Impact', 'Integrity Impact', 'Availability Impact', 'CVSS Score'])

# Generate all combinations of CVSS metrics
for av, ac, pr, ui, s, ci, ii, ai in product(attack_vector, attack_complexity, privileges_required, user_interaction, scope, confidentiality_impact, integrity_impact, availability_impact):
    # Calculate the CVSS score for the current combination of metrics
    vector = f'CVSS:3.1/AV:{av}/AC:{ac}/PR:{pr}/UI:{ui}/S:{s}/C:{ci}/I:{ii}/A:{ai}'
    score = CVSS3(vector).scores()[0]

    # If the calculated score matches the target score, write the combination of metrics to STDOUT
    if score == target_score:
        writer.writerow([av, ac, pr, ui, s, ci, ii, ai, score])

result_all_cvss_distribution.sh

cut -f9 -d, cvss.csv| grep -v CVSS | sort -n | uniq -c
  96 0.0
   6 1.6
   6 1.7
  18 1.8
  12 1.9
  18 2.0
  12 2.1
  15 2.2
  12 2.3
  15 2.4
  12 2.5
  21 2.6
  12 2.7
  15 2.8
  24 2.9
  15 3.0
  24 3.1
  21 3.2
  18 3.3
  30 3.4
  22 3.5
  20 3.6
  23 3.7
  22 3.8
  23 3.9
  34 4.0
  25 4.1
  29 4.2
  32 4.3
  38 4.4
  29 4.5
  55 4.6
  34 4.7
  63 4.8
  42 4.9
  38 5.0
  40 5.1
  38 5.2
  51 5.3
  68 5.4
  51 5.5
  53 5.6
  71 5.7
  44 5.8
  79 5.9
  32 6.0
  72 6.1
  53 6.2
  69 6.3
  53 6.4
  64 6.5
  32 6.6
  56 6.7
  69 6.8
  50 6.9
  26 7.0
  75 7.1
  25 7.2
  52 7.3
  31 7.4
  47 7.5
  46 7.6
  32 7.7
  12 7.8
  26 7.9
  18 8.0
  32 8.1
  41 8.2
  21 8.3
  10 8.4
  16 8.5
   7 8.6
  18 8.7
  11 8.8
   9 8.9
   9 9.0
   7 9.1
   3 9.2
  13 9.3
   3 9.4
  11 9.6
   1 9.8
   7 9.9
   7 10.0

summarize_cvss_combinations.py

# ChatGPT prompt:
# long discussion about how to get it to correctly summarize and format blocks and options as list ...

# Output after 7+ iterations
import sys
from itertools import product
from cvss import CVSS3

# Check if a CVSS score was provided as a command-line argument
if len(sys.argv) != 2:
    print(f'Usage: {sys.argv[0]} <cvss_score>')
    sys.exit(1)

# Parse the CVSS score
try:
    target_score = float(sys.argv[1])
except ValueError:
    print(f'Error: Invalid CVSS score "{sys.argv[1]}"')
    sys.exit(1)

# Define the possible values for each CVSS metric
metric_values = {
    'Attack Vector': ['N', 'A', 'L', 'P'],
    'Attack Complexity': ['L', 'H'],
    'Privileges Required': ['N', 'L', 'H'],
    'User Interaction': ['N', 'R'],
    'Scope': ['U', 'C'],
    'Confidentiality Impact': ['N', 'L', 'H'],
    'Integrity Impact': ['N', 'L', 'H'],
    'Availability Impact': ['N', 'L', 'H'],
}

# Generate all combinations of CVSS metrics
combinations = []
for av, ac, pr, ui, s, ci, ii, ai in product(*metric_values.values()):
    # Calculate the CVSS score for the current combination of metrics
    vector = f'CVSS:3.1/AV:{av}/AC:{ac}/PR:{pr}/UI:{ui}/S:{s}/C:{ci}/I:{ii}/A:{ai}'
    score = CVSS3(vector).scores()[0]

    # If the calculated score matches the target score, add the combination of metrics to the list
    if score == target_score:
        combinations.append((av, ac, pr, ui, s, ci, ii, ai))

# Group the combinations by their common metrics
results = {metric: set() for metric in metric_values.keys()}

for combination in combinations:
    for metric, value in zip(metric_values.keys(), combination):
        results[metric].add(value)

# Print the results
for metric, values in results.items():
    if values == set(metric_values[metric]):
        print(f'{metric} = *')
    else:
        print(f'{metric} = {" or ".join(sorted(values))}')

x_result_all_cvss_score_combos.csv