Update check_vulns

src/pe_reports/helpers/check_vulns.py

@@ -0,0 +1,158 @@
+ import sys
+# sys.path.append('Users/stewartc/Documents/GitHub/pe-reports/src/pe_reports/data')
+# sys.path.append('Users/stewartc/Documents/GitHub/pe-reports/src/pe_asm/helpers')
+# sys.path.append('Users/stewartc/Documents/GitHub/pe-reports/src/pe_reports')
+# sys.path.append('Users/stewartc/Documents/GitHub/pe-reports/src/pe_asm')
+# sys.path.append('Users/stewartc/Documents/GitHub/pe-reports/src')
+# Third-Party Libraries
+import numpy as np
+import pandas as pd
+import psycopg2
+from psycopg2 import OperationalError
+from psycopg2.extensions import AsIs
+import psycopg2.extras as extras
+from sshtunnel import SSHTunnelForwarder
+import logging
+from datetime import datetime
+import math
+
+# from .config import config, staging_config
+# cisagov Libraries
+
+# from pe_scorecard.data.db_query import (
+#     # connect,
+#     # close,
+#     # get_stakeholders
+#     # get_was_stakeholders,
+#     # get_hosts,
+#     # get_port_scans,
+#     # get_was_summary,
+#     # get_software
+# )
+
+from pe_reports.data.db_query import (
+    connect,
+    close
+)
+
+# from pe_scorecard.scores.score_helper_functions import (
+#     get_letter_grade,
+#     get_next_month,
+#     average_numbers
+# )
+
+LOGGER = logging.getLogger(__name__)
+
+def main():
+    start_date = datetime(2023, 4, 1, 0, 0, 0, 0)
+    end_date = datetime(2023, 6, 1, 0, 0, 0, 0)
+    orgs_df = get_stakeholders()
+    print(orgs_df)
+    # mean_fp = []
+    # for index, org in orgs_df.iterrows():
+    #     vuln_list = []
+    #     vuln_list.append([datetime(2022, 3, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2022, 3, 1, 0, 0, 0, 0), datetime(2022, 4, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     vuln_list.append([datetime(2022, 4, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2022, 4, 1, 0, 0, 0, 0), datetime(2022, 5, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     vuln_list.append([datetime(2022, 5, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2022, 5, 1, 0, 0, 0, 0), datetime(2022, 6, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     vuln_list.append([datetime(2022, 6, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2022, 6, 1, 0, 0, 0, 0), datetime(2022, 7, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     vuln_list.append([datetime(2022, 7, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2022, 7, 1, 0, 0, 0, 0), datetime(2022, 8, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     vuln_list.append([datetime(2022, 8, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2022, 8, 1, 0, 0, 0, 0), datetime(2022, 9, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     vuln_list.append([datetime(2022, 9, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2022, 9, 1, 0, 0, 0, 0), datetime(2022, 10, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     vuln_list.append([datetime(2022, 10, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2022, 10, 1, 0, 0, 0, 0), datetime(2022, 11, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     vuln_list.append([datetime(2022, 11, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2022, 11, 1, 0, 0, 0, 0), datetime(2022, 12, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     vuln_list.append([datetime(2022, 12, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2022, 12, 1, 0, 0, 0, 0), datetime(2023, 1, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     vuln_list.append([datetime(2023, 1, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2023, 1, 1, 0, 0, 0, 0), datetime(2023, 2, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     vuln_list.append([datetime(2023, 2, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2023, 2, 1, 0, 0, 0, 0), datetime(2023, 3, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     vuln_list.append([datetime(2023, 3, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2023, 3, 1, 0, 0, 0, 0), datetime(2023, 4, 1, 0, 0, 0, 0), org['organizations_uid'])])
+    #     # vuln_list.append([datetime(2023, 4, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2023, 4, 1, 0, 0, 0, 0), datetime(2023, 5, 1, 0, 0, 0, 0))])
+    #     # vuln_list.append([datetime(2023, 5, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2023, 5, 1, 0, 0, 0, 0), datetime(2023, 6, 1, 0, 0, 0, 0))])
+    #     # vuln_list.append([datetime(2023, 6, 1, 0, 0, 0, 0), calculate_fp_perc(datetime(2023, 6, 1, 0, 0, 0, 0), datetime(2023, 7, 1, 0, 0, 0, 0))])
+
+    #     df_vulns = pd.DataFrame(vuln_list, columns = ["Date", "FP_Percent"]) 
+    #     org_mean_fp = round((df_vulns['FP_Percent']).mean(), 2)
+    #     if org_mean_fp > 0.0:
+    #         mean_fp.append([org['organizations_uid'], org_mean_fp]) 
+
+    # df_mean_fp = pd.DataFrame(mean_fp, columns = ["organizations_uid", "org_mean_fp"])
+
+    # print(df_mean_fp)
+
+    vs_vulns = get_all_vs_vulns(start_date, end_date)
+    print(vs_vulns)
+
+
+def calculate_fp_perc(start_date, end_date, org_id):
+    vs_vulns = get_vs_vulns(start_date, end_date, org_id)
+    if vs_vulns is None or vs_vulns.empty:
+        return 0
+    else:
+        vuln_count = len(vs_vulns)
+        fp_df = vs_vulns.loc[vs_vulns['false_positive'] == True]
+        fp_count = len(fp_df)
+        return round(fp_count * 100.0 / vuln_count, 8)
+
+
+
+
+def get_pe_vulns():
+    conn = connect()
+    try:
+        sql = """select sv.organizations_uid, sv.cve, sv.ip,sv.is_verified, sv."timestamp"
+        from shodan_vulns sv 
+        where sv.cve notnull and sv.cve != 'NaN'
+        group by sv.organizations_uid , sv.cve, sv.ip, sv.is_verified, sv."timestamp" """
+        pe_vulns_df = pd.read_sql(sql, conn)
+        return pe_vulns_df
+    except (Exception, psycopg2.DatabaseError) as error:
+        LOGGER.error("There was a problem with your database query %s", error)
+    finally:
+        if conn is not None:
+            close(conn)
+
+def get_vs_vulns(start_date, end_date, org_ids):
+    conn = connect()
+    try:
+        #CHANGE TABLE BACL TO CYHY_TICKETS
+        sql = """select ct.organizations_uid, ct.cve, ct.cvss_base_score, ct.ip, ct.false_positive, ct.time_opened
+        from cyhy_tickets_temp ct
+        where ct.time_opened >= %(start_date)s and ct.time_opened < %(end_date)s and ct.organizations_uid::varchar = %(org_ids)s
+        group by ct.organizations_uid, ct.cve, ct.cvss_base_score, ct.false_positive, ct.time_opened"""
+        vs_vulns_df = pd.read_sql(sql, conn, params={"start_date": start_date, "end_date": end_date, "org_id": org_ids})
+        return vs_vulns_df
+    except (Exception, psycopg2.DatabaseError) as error:
+        LOGGER.error("There was a problem with your database query %s", error)
+    finally:
+        if conn is not None:
+            close(conn)
+
+def get_all_vs_vulns(start_date, end_date):
+    conn = connect()
+    try:
+        sql = """select ct.organizations_uid, ct.cve, ct.cvss_base_score, ct.ip, ct.false_positive, ct.time_opened
+        from cyhy_tickets ct
+        where ct.time_opened >= %(start_date)s and ct.time_opened < %(end_date)s
+        group by ct.organizations_uid, ct.cve, ct.cvss_base_score, ct.false_positive, ct.time_opened"""
+        vs_vulns_df = pd.read_sql(sql, conn, params={"start_date": start_date, "end_date": end_date})
+        return vs_vulns_df
+    except (Exception, psycopg2.DatabaseError) as error:
+        LOGGER.error("There was a problem with your database query %s", error)
+    finally:
+        if conn is not None:
+            close(conn)
+
+def get_stakeholders():
+    conn = connect()
+    try:
+        sql = """select organizations_uid, report_on from organizations where retired = False"""
+        pe_orgs_df = pd.read_sql(sql, conn)
+        return pe_orgs_df
+    except (Exception, psycopg2.DatabaseError) as error:
+        LOGGER.error("There was a problem with your database query %s", error)
+    finally:
+        if conn is not None:
+            close(conn)
+
+
+
+if __name__ == "__main__":
+    main()