#    Copyright (C) 2025 James Brotosky, Brandon Wickline
#
#    This program is free software: you can redistribute it and/or modify
#    it under the terms of the GNU Affero General Public License as published
#    by the Free Software Foundation, either version 3 of the License, or
#    (at your option) any later version.
#
#    This program is distributed in the hope that it will be useful,
#    but WITHOUT ANY WARRANTY; without even the implied warranty of
#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#    GNU Affero General Public License for more details.
#
#    You should have received a copy of the GNU Affero General Public License
#    along with this program.  If not, see <https://www.gnu.org/licenses/>.

import logging
import os
import os.path
import re
from typing import List

import dotenv
import pandas as pd

from models.execution import ExecutionHistoryRecord
from models.policy import Allowlist, Policy
from services.API import AirlockAPIWrapper
from utils.configmanager import get_system_list, get_system_value, load_env
from utils.selector import Selector
from utils.utils import (
    areYouSure,
    clear_screen,
    colorText,
    formatHTML,
    get_sanitized_input,
    locked,
    open_directory,
    print_x_wide,
    regulator,
)

logger = logging.getLogger(__name__)

dotenv.load_dotenv()


def selectPolicies(api: AirlockAPIWrapper, allow_multiple=True) -> List[Policy]:

    policies = [Policy(**row.to_dict()) for _, row in api.policy_find_all().iterrows()]
    logger.debug("Prompting for Policies")
    print(colorText("Please select policy/policies", "white"))
    selected = Selector.select_objects(policies, allow_multiple, prompt_each=True)

    if selected is None:
        return []

    # Normalize to always return a list
    logger.debug("Returning {selected.dict}")
    return selected if isinstance(selected, list) else [selected]


def selectAllowlists(
    api: AirlockAPIWrapper, policy=all, allow_multiple=True
) -> List[Allowlist]:
    if policy == "all":
        allowlists = [
            Allowlist(**row.to_dict()) for _, row in api.allowlist_find_all().iterrows()
        ]
    else:
        allowlists = [
            Allowlist(**row.to_dict())
            for _, row in api.policy_list_allowlists(policy[0].groupid).iterrows()
        ]
    logger.debug("Prompting for Allowlist(s)")
    print(colorText("Please select allowlist(s)", "white"))
    selected = Selector.select_objects(allowlists, allow_multiple, prompt_each=True)

    if selected is None:
        return []

    # Normalize to always return a list
    logger.debug(f"Returning {selected}")
    return selected if isinstance(selected, list) else [selected]


def sortHashes(
    api: AirlockAPIWrapper, selected_policies: List[Policy], type=[1, 2, 6, 7]
):
    working_dir = load_env("WORKING_DIR")
    history_days = Selector.select_value(
        prompt="Enter how many days of history to pull (1–150): ",
        value_type=int,
        valid_range=(1, 150),
    )

    logger.debug(f"{history_days} day selected for history")

    if history_days is None:
        logging.warning("No history range selected. Aborting.")
        return

    policy_executions = ExecutionHistoryRecord.from_policies(
        api, selected_policies, type_=type, history_days=history_days
    )

    logger.debug(f"Executions contains {policy_executions}")

    enriched_executions = ExecutionHistoryRecord.enrich_with_hashes(
        api, policy_executions
    )
    categorized_executions = (
        ExecutionHistoryRecord.categorize_executions_by_hash_decision(
            enriched_executions
        )
    )
    approved, unapproved, needs_review, unknown = (
        ExecutionHistoryRecord.sort_by_hash_decision(categorized_executions)
    )

    categories = {
        "needs_review": needs_review,
        "approved": approved,
        "unapproved": unapproved,
        "leftover": unknown,
    }

    for label, records in categories.items():
        if not records:
            continue  # Skip empty or falsy categories

        csv_path = f"{working_dir}\\Needs_Review\\Review_First\\{selected_policies[0].name}_{label}_executions.csv"
        html_path = f"{working_dir}\\Needs_Review\\HTML\\{selected_policies[0].name}_{label}.html"

        # Convert ExecutionHistoryRecord objects to dictionaries
        df = pd.DataFrame([r.__dict__ for r in records])

        # Optional: flatten hash_obj if needed
        if not df.empty and "hash_obj" in df.columns:
            hash_df = df["hash_obj"].apply(lambda h: h.to_dict() if h else {})
            df = pd.concat([df.drop(columns=["hash_obj"]), hash_df], axis=1)

        # Save to CSV
        df.to_csv(csv_path, index=False)
        logger.info(f"Saved {label} executions to {csv_path}")

        # Generate HTML
        formatHTML(df, html_path)
        logger.info(f"Generated HTML report at {html_path}")


def buildPathsandPublishers(selected_policies: List[Policy], split):
    working_dir = load_env("WORKING_DIR")
    df1 = pd.DataFrame()
    df2 = pd.DataFrame()
    all_approved_hashes = pd.DataFrame()
    path1 = (
        f"{working_dir}\\Approved\\{selected_policies[0].name}_approved_executions.csv"
    )
    path2 = f"{working_dir}\\Approved\\{selected_policies[0].name}_needs_review_executions.csv"
    path_exclusion_constant = get_system_value("PATH_EXCLUSION_CONST", cast_type=int)

    if os.path.exists(path1):
        df1 = pd.read_csv(path1)
    else:
        logger.warning(f"File not found: {path1}")

    if os.path.exists(path2):
        df2 = pd.read_csv(path2)
    else:
        logger.warning(f"File not found: {path2}")

    if df1.empty and df2.empty:
        logger.warning("Both DataFrames are empty. Skipping sort.")
        all_approved_hashes = pd.DataFrame()
        logger.debug(all_approved_hashes.head)
    else:
        all_approved_hashes = pd.concat([df1, df2], ignore_index=True)
        if "filename" in all_approved_hashes.columns:
            all_approved_hashes = all_approved_hashes.sort_values(by="filename")
        else:
            logger.warning(
                "Warning: 'filename' column not found in concatenated DataFrame."
            )

    if not all_approved_hashes.empty and path_exclusion_constant:

        primary_path_exclusions = calculatePath(
            all_approved_hashes,
            path_exclusion_constant,
            split,
        )
        remaining_hashes = all_approved_hashes[
            ~all_approved_hashes["sha256"].isin(primary_path_exclusions["sha256"])
        ]
        secondary_path_exclusions = calculatePath(
            remaining_hashes, (path_exclusion_constant - 1), split
        )
        remaining_hashes = remaining_hashes[
            ~remaining_hashes["sha256"].isin(secondary_path_exclusions["sha256"])
        ]
        dataframes = {
            "all_approved_hashes": all_approved_hashes,
            "primary_Paths": primary_path_exclusions,
            "secondary_Paths": secondary_path_exclusions,
            "hashes_not_approvable_by_path": remaining_hashes,
        }
        logger.debug("Preparing to sort dataframes")
        for name, df in dataframes.items():
            logger.debug(f" DataFrame headers: {list(df.columns)}")
            if "hashes" in name:
                df.sort_values(by="filename", inplace=True)
            else:
                df.sort_values(by="longestcfp", inplace=True)

            df.to_csv(
                f"{working_dir}\\Needs_Review\\Review_Second\\{selected_policies[0].name}_{name}.csv",
                index=False,
            )
            formatHTML(
                df,
                f"{working_dir}\\Needs_Review\\HTML\\{selected_policies[0].name}_{name}.html",
            )

        if not all_approved_hashes.empty:
            # Drop all not signed, only keep unique values
            publist = all_approved_hashes[
                all_approved_hashes["publisher"] != "Not Signed"
            ].drop_duplicates(subset=["publisher"])
            # Remove Bad publisher if somehow they made it this far
            pattern = regulator(get_system_list("BAD_PUBLISHERS"))
            publist = publist[~publist["publisher"].str.contains(pattern, na=False)]
            publist = publist[["publisher"]]
            publist.sort_values(by="publisher", inplace=True)
            publist.to_csv(
                f"{working_dir}\\Needs_Review\\Review_Second\\{selected_policies[0].name}_publishers.csv",
                index=False,
            )
    else:
        logger.debug("Approved Hashes list appears empty")


def buildPreflights(selected_policies: List[Policy]):
    working_dir = load_env("WORKING_DIR")

    df1 = pd.DataFrame()
    df2 = pd.DataFrame()
    approved_hashes = pd.DataFrame()
    approved_publishers = pd.DataFrame()

    hash = f"{working_dir}\\Needs_Review\\Review_Second\\{selected_policies[0].name}_all_approved_hashes.csv"
    path1 = f"{working_dir}\\Approved\\{selected_policies[0].name}_primary_Paths.csv"
    path2 = f"{working_dir}\\Approved\\{selected_policies[0].name}_secondary_Paths.csv"
    publishers = f"{working_dir}\\Approved\\{selected_policies[0].name}_publishers.csv"

    # Read in and combine the two path generations
    if os.path.exists(path1):
        df1 = pd.read_csv(path1)
    else:
        logger.warning(f"File not found: {path1}")

    if os.path.exists(path2):
        df2 = pd.read_csv(path2)
    else:
        logger.warning(f"File not found: {path2}")

    if df1.empty and df2.empty:
        logger.warning("Both DataFrames are empty. Skipping sort.")
        approved_paths = pd.DataFrame()
    else:
        approved_paths = pd.concat([df1, df2], ignore_index=True)

    approved_paths = approved_paths.drop_duplicates(subset="longestcfp", keep="first")

    # We create a list of hashes that are left over if we exclude the ones that are covered by the path exclusions.
    if os.path.exists(hash):
        hashes = pd.read_csv(hash)
        approved_hashes = hashes[~hashes["filename"].isin(approved_paths["longestcfp"])]

        approved_hashes = approved_hashes.drop_duplicates(subset="sha256", keep="first")

    else:
        logger.warning(f"File not found: {hash}")

    if os.path.exists(publishers):
        approved_publishers = pd.read_csv(publishers)

    else:
        logger.warning(f"File not found: {publishers}")

    dataframes = {
        "approved_paths": approved_paths,
        "approved_hashes": approved_hashes,
        "approved_publishers": approved_publishers,
    }

    for name, df in dataframes.items():
        logger.debug(f" DataFrame headers: {list(df.columns)}")
        if name == "approved_paths":
            df.sort_values(by="longestcfp", inplace=True)
        elif name == "approved_hashes":
            df.sort_values(by="filename", inplace=True)
        elif name == "approved_publishers":
            df.sort_values(by="publisher", inplace=True)

        df.to_csv(
            f"{working_dir}\\Preflight\\{selected_policies[0].name}_{name}.csv",
            index=False,
        )
        formatHTML(
            df,
            f"{working_dir}\\Preflight\\HTML\\{selected_policies[0].name}_{name}.html",
        )


def splitFilepathsGrouped(df, path_exclusion_constant, col="filename"):
    min_files_for_path = get_system_value("MIN_FILES_FOR_PATH", cast_type=int)

    def clean_split(path):
        if not isinstance(path, (str, bytes, os.PathLike)):
            return []
        parts = str(os.path.normpath(path)).split(os.sep)
        parts = [p for p in parts if p]  # Remove empty strings
        return parts

    # Diagnostic: log any non-string entries
    non_string_entries = df[
        ~df[col].apply(lambda x: isinstance(x, (str, bytes, os.PathLike)))
    ]
    if not non_string_entries.empty:
        print(f"[WARNING] Non-string entries found in column '{col}':")
        print(non_string_entries)

    df = df.copy()
    split_paths = df[col].apply(clean_split)

    if min_files_for_path is not None:
        df = df[
            split_paths.apply(lambda parts: len(parts) >= min_files_for_path)
        ].copy()
        split_paths = split_paths[df.index]

    df["group_key"] = split_paths.apply(
        lambda parts: os.sep.join(parts[:path_exclusion_constant])
    )
    grouped = df.groupby("group_key")
    new_rows = []

    for _, group_df in grouped:
        paths = group_df[col].tolist()
        split_parts = [clean_split(p) for p in paths]

        def longest_common_prefix(paths):
            if not paths:
                return []
            prefix = paths[0]
            for path in paths[1:]:
                prefix = [a for a, b in zip(prefix, path) if a == b]
                if not prefix:
                    break
            return prefix

        common_prefix = longest_common_prefix(split_parts)
        prefix_str = os.sep.join(common_prefix)

        for i, parts in enumerate(split_parts):
            filename = parts[-1]
            middle = (
                os.sep.join(parts[len(common_prefix) : -1])
                if len(parts) > len(common_prefix) + 1
                else ""
            )
            row = group_df.iloc[i].copy()
            row["longestcfp"] = prefix_str
            row["middle"] = middle
            row["filename_only"] = filename
            row["file_extension"] = os.path.splitext(filename)[1].lower()
            new_rows.append(row)

    return pd.DataFrame(new_rows).drop(columns=["group_key"])


def calculatePath(approved_hashes, path_exclusion_constant, split):
    if split:
        dfs_by_policy = [group for _, group in approved_hashes.groupby("policy")]
    else:
        dfs_by_policy = [approved_hashes]

    badpathparts = get_system_list("BAD_PATH_PARTS")
    min_files_for_path = get_system_value("MIN_FILES_FOR_PATH", cast_type=int)

    processed_dfs = []

    for df in dfs_by_policy:
        haslcp = splitFilepathsGrouped(df, path_exclusion_constant, "filename")
        haslcp = haslcp.drop_duplicates()

        forbidden = regulator(badpathparts, True)
        forbidden_lcfp = haslcp["longestcfp"].str.contains(forbidden, na=False)

        logger.debug("Removing forbidden filepaths for path exceptions")
        print(colorText("Removing forbidden filepaths for path exceptions", "green"))
        lcp_not_forbidden = haslcp[~forbidden_lcfp].copy()

        lcp_not_forbidden_review = lcp_not_forbidden[
            [
                "policyname",
                "longestcfp",
                "middle",
                "filename_only",
                "file_extension",
                "sha256",
            ]
        ]

        unique_sha_counts = (
            lcp_not_forbidden_review.groupby("longestcfp")["sha256"]
            .nunique()
            .reset_index()
        )
        unique_sha_counts.columns = ["longestcfp", "unique_sha256_count"]

        lcp_not_forbidden_review = lcp_not_forbidden_review.merge(
            unique_sha_counts, on="longestcfp", how="left"
        )
        lcp_not_forbidden_review = lcp_not_forbidden_review[
            lcp_not_forbidden_review["unique_sha256_count"] >= min_files_for_path
        ]
        processed_dfs.append(lcp_not_forbidden_review)

    pathExclusions = pd.concat(processed_dfs, ignore_index=True)

    return pathExclusions


def testChange(selected_policies, destination_policy, destination_allowlist):
    working_dir = load_env("WORKING_DIR")

    logger.info("These path exclusions would be added to:")
    logger.info(destination_policy)

    pathexclusions = pd.read_csv(
        f"{working_dir}\\Preflight\\{selected_policies[0].name}_approved_paths.csv"
    )
    hashes = pd.read_csv(
        f"{working_dir}\\Preflight\\{selected_policies[0].name}_approved_hashes.csv"
    )

    unique_combinations = pathexclusions[
        ["longestcfp", "file_extension"]
    ].drop_duplicates()

    drive_letter_pattern = re.compile(r"^[a-zA-Z]:\\")
    processed_paths = [
        (path if drive_letter_pattern.match(path) else f"\\\\{path}") + f"\\**{ext}"
        for path, ext in unique_combinations.itertuples(index=False, name=None)
    ]

    for path in processed_paths:
        logger.info(path)

    print(colorText("These publishers would added", "yellow"))
    processed_publishers = []
    if os.path.exists(
        f"{working_dir}\\Preflight\\{selected_policies[0].name}_approved_publishers.csv"
    ):
        publishers = pd.read_csv(
            f"{working_dir}\\Preflight\\{selected_policies[0].name}_approved_publishers.csv"
        )
        if publishers.empty:
            print(colorText("The publishers list is empty.", "red"))
        else:
            processed_publishers = (
                publishers[publishers["publisher"] != "Not Signed"]["publisher"]
                .drop_duplicates()
                .tolist()
            )
            for publisher in processed_publishers:
                print(publisher)

    print(colorText("These hashes would be added to:", "yellow"))
    print(destination_allowlist)

    processed_hashes = hashes["sha256"].unique().tolist()
    print_x_wide(processed_hashes, 3)

    return processed_paths, processed_hashes, processed_publishers


def menu_policy_enforce(
    api: AirlockAPIWrapper,
):  # TODO Need to clean up 6 and 7 into functions
    selected_policies = []
    destination_policy = []
    destination_allowlist = []
    processed_paths = []
    processed_hashes = []
    processed_publishers = []
    working_dir = load_env("WORKING_DIR")

    while True:
        printEnforceChecklist(
            selected_policies, destination_policy, destination_allowlist
        )
        choice = get_sanitized_input("\nEnter your choice: ")

        if choice == "1":
            clear_screen()
            selected_policies = selectPolicies(api, True)

        elif choice == "2":
            clear_screen()
            print(
                colorText(
                    "Please choose destination_name Policy for Path Exclusions", "white"
                )
            )

            destination_policy = selectPolicies(api, False)

            print(colorText("Please choose Allowlist for Hashes", "white"))

            destination_allowlist = selectAllowlists(api, destination_policy, False)

        elif choice == "3":
            clear_screen()
            sortHashes(
                api,
                selected_policies,
                type=[1, 2, 6, 7],
            )

        elif choice == "4":
            clear_screen()
            if os.path.exists(
                f"{working_dir}\\Needs_Review\\Review_First\\{selected_policies[0].name}_approved_executions.csv"
            ):
                buildPathsandPublishers(selected_policies, False)
            else:
                print(
                    "File not found. Please make sure it's saved correctly and try again."
                )

        elif choice == "5":
            clear_screen()
            if os.path.exists(
                f"{working_dir}\\Approved\\{selected_policies[0].name}_approved_executions.csv"
            ) and os.path.exists(
                f"{working_dir}\\Approved\\{selected_policies[0].name}_primary_Paths.csv"
            ):
                buildPreflights(selected_policies)
            else:
                print(
                    "File not found. Please make sure it's saved correctly and try again."
                )

        elif choice == "6":
            clear_screen()
            if (
                os.path.exists(
                    f"{working_dir}\\Preflight\\{selected_policies[0].name}_approved_paths.csv"
                )
                and os.path.exists(
                    f"{working_dir}\\Preflight\\{selected_policies[0].name}_approved_hashes.csv"
                )
                and destination_policy
                and destination_allowlist
            ):
                processed_paths, processed_hashes, processed_publishers = testChange(
                    selected_policies, destination_policy, destination_allowlist
                )
            else:
                # Log which condition(s) failed
                missing_items = []
                if not os.path.exists(
                    f"{working_dir}\\Preflight\\{selected_policies[0].name}_approved_paths.csv"
                ):
                    missing_items.append("approved_paths.csv not found")
                if not os.path.exists(
                    f"{working_dir}\\Preflight\\{selected_policies[0].name}_approved_hashes.csv"
                ):
                    missing_items.append("approved_hashes.csv not found")
                if not destination_policy:
                    missing_items.append("destination_policy is empty or None")
                if not destination_allowlist:
                    missing_items.append("destination_allowlist is empty or None")

                logger.error("Preflight check failed due to the following:")
                for item in missing_items:
                    logger.error(f" - {item}")

        elif choice == "7":
            clear_screen()
            areYouSure()
            confirmation = get_sanitized_input("Type 'I AGREE' to continue: ")
            if (
                processed_paths
                and processed_hashes
                and processed_publishers
                and destination_policy
                and destination_allowlist
                and confirmation.strip() == "I AGREE"
            ):
                print(colorText("Proceeding with the code...", "yellow"))
                api.hash_add_to_allowlist(
                    destination_allowlist[0].applicationid, processed_hashes
                )
                api.policy_add_path_exclusions(
                    destination_policy[0].groupid, processed_paths
                )
                if processed_publishers:
                    api.policy_add_publishers(
                        destination_policy[0].groupid, processed_publishers
                    )

                locked()

            else:
                logger.error("Confirmation block failed. Reasons:")
                if not processed_publishers or processed_hashes or processed_paths:
                    logger.error(" - Test not performed.")
                if not destination_policy:
                    logger.error(" - `destination_policy` is missing or invalid.")
                if not destination_allowlist:
                    logger.error(" - `destination_allowlist` is missing or invalid.")
                if confirmation.strip() != "I AGREE":
                    logger.error(
                        " - User did not confirm with 'I AGREE'. Received: '%s'",
                        confirmation.strip(),
                    )

        elif choice.upper() == "F":
            open_directory(working_dir)
        elif choice.upper() == "B":
            break

        else:
            print(colorText("Invalid choice. Please try again.", "red"))


def section_header(title):
    print(
        colorText(
            "\n --------------------------------------------------------------------",
            "cyan",
        )
    )
    print(colorText(f" ------------- {title} -------------", "cyan"))
    print(
        colorText(
            " --------------------------------------------------------------------",
            "cyan",
        )
    )


def printEnforceChecklist(selected_policies, destination_policy, destination_allowlist):
    working_dir = load_env("WORKING_DIR")
    section_header("🛠️ 🔒 Prepare to Enforce Policy 🛠️ 🔒")
    print(
        colorText(
            "\nSequentially follow these steps to prepare a policy for enforcement:",
            "white",
        )
    )

    # Step 1: Originating Policies
    print(
        colorText(
            "\n1. Choose which policy or policies to gather execution info from", "cyan"
        )
    )
    if not selected_policies:
        print(colorText("  [✗]  No policies have been chosen", "red"))
    else:
        print(colorText("The following policies have been chosen:", "green"))
        for policy in selected_policies:
            print(colorText(f"  [✓] {policy.name}", "green"))

    # Step 2: Destination Policy and Allowlist
    print(
        colorText("2. Choose the destination policy and associated allowlist", "cyan")
    )
    if destination_policy:
        print(
            colorText(
                f"  [✓] {destination_policy[0].name} has been selected as the destination policy",
                "green",
            )
        )
    else:
        print(colorText("  [✗]  No destination policy has been chosen", "red"))

    if destination_allowlist:
        print(
            colorText(
                f"  [✓] {destination_allowlist[0].name} has been selected as allowlist",
                "green",
            )
        )
    else:
        print(colorText("  [✗]  No allowlist has been chosen", "red"))

    # Step 3: Data Preparation
    print(
        colorText(
            f"3. Select to begin pulling execution history. The executions will be sorted and placed in {working_dir}\\data\\Needs_Review",
            "cyan",
        )
    )
    if selected_policies:
        policy_id = selected_policies[0].name
        review_path = f"{working_dir}\\Needs_Review\\Review_First\\{policy_id}_approved_executions.csv"
        print(
            colorText(
                (
                    "  [✓] Data has been fetched"
                    if os.path.exists(review_path)
                    else "  [✗] Data has not been fetched"
                ),
                "green" if os.path.exists(review_path) else "red",
            )
        )
    else:
        print(
            colorText(
                "  [✗]  No policies selected, cannot check data fetch status", "red"
            )
        )

    # Step 4: Manual Review
    print(colorText("4. Manually review the files:", "cyan"))
    print(
        colorText(
            "     Remove the rows containing hashes you do not approve of", "cyan"
        )
    )
    print(
        colorText(
            f"     When complete, save both csv files to {working_dir}\\data\\Approved and choose this option.",
            "cyan",
        )
    )
    print(
        colorText(
            "     This will start the process to generate possible filepath approvals",
            "cyan",
        )
    )

    if selected_policies:
        policy_id = selected_policies[0].name
        approved_path = f"{working_dir}\\Approved\\{policy_id}_approved_executions.csv"
        second_review_path = (
            f"{working_dir}\\Needs_Review\\Review_Second\\{policy_id}_primary_Paths.csv"
        )
        print(
            colorText(
                (
                    "  [✓]  Reviewed hashes have been loaded"
                    if os.path.exists(approved_path)
                    else "  [✗]  Reviewed hashes have not been loaded"
                ),
                "green" if os.path.exists(approved_path) else "red",
            )
        )
        print(
            colorText(
                (
                    "  [✓]  Path review list created"
                    if os.path.exists(second_review_path)
                    else "  [✗]  Path review list has not been created"
                ),
                "green" if os.path.exists(second_review_path) else "red",
            )
        )
    else:
        print(
            colorText(
                "  [✗]  No policies selected, cannot check reviewed hashes or path list",
                "red",
            )
        )

    # Step 5: Path Review
    print(
        colorText(
            f"5. Manually review the files in {working_dir}\\Needs_Review\\Review_Second\\",
            "cyan",
        )
    )
    print(
        colorText(
            "     Remove the rows containing path exclusions or publishers you do not approve of.",
            "cyan",
        )
    )
    print(
        colorText(
            f"     When complete, save the files to {working_dir}\\data\\Approved",
            "cyan",
        )
    )
    print(
        colorText("     Choose this option when done to build your preflights", "cyan")
    )

    if selected_policies:
        policy_id = selected_policies[0].name
        reviewed_path = f"{working_dir}\\Approved\\{policy_id}_primary_Paths.csv"
        preflight_paths = f"{working_dir}\\Preflight\\{policy_id}_approved_paths.csv"
        preflight_hashes = f"{working_dir}\\Preflight\\{policy_id}_approved_hashes.csv"
        print(
            colorText(
                (
                    "  [✓]  Reviewed path list detected"
                    if os.path.exists(reviewed_path)
                    else "  [✗]  Path review list has not been detected"
                ),
                "green" if os.path.exists(reviewed_path) else "red",
            )
        )
        preflight_ready = os.path.exists(preflight_paths) and os.path.exists(
            preflight_hashes
        )
        print(
            colorText(
                (
                    "  [✓]  Preflight Path Exclusion List has been generated"
                    if preflight_ready
                    else "  [✗]  Preflight Path Exclusion List has not been generated"
                ),
                "green" if preflight_ready else "red",
            )
        )
    else:
        print(
            colorText(
                "  [✗]  No policies selected, cannot check preflight status", "red"
            )
        )

    # Final Steps
    print(
        colorText(
            "6. Test ------------------------------------------------------", "cyan"
        )
    )
    print(
        colorText(
            "     Prints to console the changes that would be made, must be done to proceed. ",
            "cyan",
        )
    )

    print(
        colorText(
            "7. Liftoff ------------------------------------------------------", "cyan"
        )
    )
    print(
        colorText(
            "     Apply path exclusions and approved publishers to selected policy",
            "cyan",
        )
    )
    print(colorText("     Apply approved hashes to allowlist", "cyan"))

    # Utility Options
    print(colorText("F. 📂  - Open Working Directory", "cyan"))
    print(colorText("B. 🔚  - Back", "cyan"))