path: root/src/sec_certs/dataset/cc.py

from __future__ import annotations

import itertools
import locale
import shutil
import tempfile
from collections.abc import Iterator
from dataclasses import dataclass
from datetime import datetime
from pathlib import Path
from typing import ClassVar, cast

import numpy as np
import pandas as pd
from bs4 import BeautifulSoup, Tag

import sec_certs.utils.sanitization
from sec_certs import constants
from sec_certs.configuration import config
from sec_certs.dataset.cc_scheme import CCSchemeDataset
from sec_certs.dataset.cpe import CPEDataset
from sec_certs.dataset.cve import CVEDataset
from sec_certs.dataset.dataset import AuxiliaryDatasets, Dataset, logger
from sec_certs.dataset.protection_profile import ProtectionProfileDataset
from sec_certs.model import (
    ReferenceFinder,
    SARTransformer,
    TransitiveVulnerabilityFinder,
)
from sec_certs.model.cc_matching import CCSchemeMatcher
from sec_certs.sample.cc import CCCertificate
from sec_certs.sample.cc_certificate_id import CertificateId
from sec_certs.sample.cc_maintenance_update import CCMaintenanceUpdate
from sec_certs.sample.cc_scheme import EntryType
from sec_certs.sample.protection_profile import ProtectionProfile
from sec_certs.serialization.json import ComplexSerializableType, serialize
from sec_certs.utils import helpers
from sec_certs.utils import parallel_processing as cert_processing
from sec_certs.utils.profiling import staged


@dataclass
class CCAuxiliaryDatasets(AuxiliaryDatasets):
    cpe_dset: CPEDataset | None = None
    cve_dset: CVEDataset | None = None
    pp_dset: ProtectionProfileDataset | None = None
    mu_dset: CCDatasetMaintenanceUpdates | None = None
    scheme_dset: CCSchemeDataset | None = None


class CCDataset(Dataset[CCCertificate, CCAuxiliaryDatasets], ComplexSerializableType):
    """
    Class that holds CCCertificate. Serializable into json, pandas, dictionary. Conveys basic certificate manipulations
    and dataset transformations. Many private methods that perform internal operations, feel free to exploit them.
    """

    def __init__(
        self,
        certs: dict[str, CCCertificate] = {},
        root_dir: str | Path = constants.DUMMY_NONEXISTING_PATH,
        name: str | None = None,
        description: str = "",
        state: Dataset.DatasetInternalState | None = None,
        auxiliary_datasets: CCAuxiliaryDatasets | None = None,
    ):
        self.certs = certs
        self.timestamp = datetime.now()
        self.sha256_digest = "not implemented"
        self.name = name if name else type(self).__name__ + " dataset"
        self.description = description if description else datetime.now().strftime("%d/%m/%Y %H:%M:%S")
        self.state = state if state else self.DatasetInternalState()

        self.auxiliary_datasets: CCAuxiliaryDatasets = (
            auxiliary_datasets if auxiliary_datasets else CCAuxiliaryDatasets()
        )

        self.root_dir = Path(root_dir)

    def to_pandas(self) -> pd.DataFrame:
        """
        Return self serialized into pandas DataFrame
        """
        df = pd.DataFrame([x.pandas_tuple for x in self.certs.values()], columns=CCCertificate.pandas_columns)
        df = df.set_index("dgst")

        df.not_valid_before = pd.to_datetime(df.not_valid_before, errors="coerce")
        df.not_valid_after = pd.to_datetime(df.not_valid_after, errors="coerce")
        df = df.astype(
            {"category": "category", "status": "category", "scheme": "category", "cert_lab": "category"}
        ).fillna(value=np.nan)
        df = df.loc[
            ~df.manufacturer.isnull()
        ]  # Manually delete one certificate with None manufacturer (seems to have many blank fields)

        # Categorize EAL
        df.eal = df.eal.fillna(value=np.nan)
        df.eal = pd.Categorical(df.eal, categories=sorted(df.eal.dropna().unique().tolist()), ordered=True)

        # Introduce year when cert got valid
        df["year_from"] = pd.DatetimeIndex(df.not_valid_before).year

        return df

    @property
    def reports_dir(self) -> Path:
        """
        Returns directory that holds files associated with certification reports
        """
        return self.certs_dir / "reports"

    @property
    def reports_pdf_dir(self) -> Path:
        """
        Returns directory that holds PDFs associated with certification reports
        """
        return self.reports_dir / "pdf"

    @property
    def reports_txt_dir(self) -> Path:
        """
        Returns directory that holds TXTs associated with certification reports
        """
        return self.reports_dir / "txt"

    @property
    def targets_dir(self) -> Path:
        """
        Returns directory that holds files associated with security targets
        """
        return self.certs_dir / "targets"

    @property
    def targets_pdf_dir(self) -> Path:
        """
        Returns directory that holds PDFs associated with security targets
        """
        return self.targets_dir / "pdf"

    @property
    def targets_txt_dir(self) -> Path:
        """
        Returns directory that holds TXTs associated with security targets
        """
        return self.targets_dir / "txt"

    @property
    def certificates_dir(self) -> Path:
        """
        Returns directory that holds files associated with the certificates
        """
        return self.certs_dir / "certificates"

    @property
    def certificates_pdf_dir(self) -> Path:
        """
        Returns directory that holds PDFs associated with certificates
        """
        return self.certificates_dir / "pdf"

    @property
    def certificates_txt_dir(self) -> Path:
        """
        Returns directory that holds TXTs associated with certificates
        """
        return self.certificates_dir / "txt"

    @property
    def pp_dataset_path(self) -> Path:
        """
        Returns a path to the dataset of Protection Profiles
        """
        return self.auxiliary_datasets_dir / "pp_dataset.json"

    @property
    def mu_dataset_dir(self) -> Path:
        """
        Returns directory that holds dataset of maintenance updates
        """
        return self.auxiliary_datasets_dir / "maintenances"

    @property
    def mu_dataset_path(self) -> Path:
        """
        Returns a path to the dataset of maintenance updates
        """
        return self.mu_dataset_dir / "maintenance_updates.json"

    @property
    def reference_annotator_dir(self) -> Path:
        return self.root_dir / "reference_annotator"

    @property
    def scheme_dataset_path(self) -> Path:
        """
        Returns a path to the scheme dataset
        """
        return self.auxiliary_datasets_dir / "scheme_dataset.json"

    BASE_URL: ClassVar[str] = "https://www.commoncriteriaportal.org"

    HTML_PRODUCTS_URL = {
        "cc_products_active.html": BASE_URL + "/products/index.cfm",
        "cc_products_archived.html": BASE_URL + "/products/index.cfm?archived=1",
    }
    HTML_LABS_URL = {"cc_labs.html": BASE_URL + "/labs"}
    CSV_PRODUCTS_URL = {
        "cc_products_active.csv": BASE_URL + "/products/certified_products.csv",
        "cc_products_archived.csv": BASE_URL + "/products/certified_products-archived.csv",
    }
    PP_URL = {
        "cc_pp_active.html": BASE_URL + "/pps/",
        "cc_pp_collaborative.html": BASE_URL + "/pps/collaborativePP.cfm?cpp=1",
        "cc_pp_archived.html": BASE_URL + "/pps/index.cfm?archived=1",
    }
    PP_CSV = {"cc_pp_active.csv": BASE_URL + "/pps/pps.csv", "cc_pp_archived.csv": BASE_URL + "/pps/pps-archived.csv"}

    @property
    def active_html_tuples(self) -> list[tuple[str, Path]]:
        """
        Returns List Tuple[str, Path] where first element is name of html file and second element is its Path.
        The files correspond to html files parsed from CC website that list all *active* certificates.
        """
        return [(x, self.web_dir / y) for y, x in self.HTML_PRODUCTS_URL.items() if "active" in y]

    @property
    def archived_html_tuples(self) -> list[tuple[str, Path]]:
        """
        Returns List Tuple[str, Path] where first element is name of html file and second element is its Path.
        The files correspond to html files parsed from CC website that list all *archived* certificates.
        """
        return [(x, self.web_dir / y) for y, x in self.HTML_PRODUCTS_URL.items() if "archived" in y]

    @property
    def active_csv_tuples(self) -> list[tuple[str, Path]]:
        """
        Returns List Tuple[str, Path] where first element is name of csv file and second element is its Path.
        The files correspond to csv files downloaded from CC website that list all *active* certificates.
        """
        return [(x, self.web_dir / y) for y, x in self.CSV_PRODUCTS_URL.items() if "active" in y]

    @property
    def archived_csv_tuples(self) -> list[tuple[str, Path]]:
        """
        Returns List Tuple[str, Path] where first element is name of csv file and second element is its Path.
        The files correspond to csv files downloaded from CC website that list all *archived* certificates.
        """
        return [(x, self.web_dir / y) for y, x in self.CSV_PRODUCTS_URL.items() if "archived" in y]

    @classmethod
    def from_web_latest(cls) -> CCDataset:
        """
        Fetches the fresh snapshot of CCDataset from seccerts.org
        """
        return cls.from_web(config.cc_latest_snapshot, "Downloading CC Dataset", "cc_latest_dataset.json")

    def _set_local_paths(self):
        super()._set_local_paths()

        if self.auxiliary_datasets.pp_dset:
            self.auxiliary_datasets.pp_dset.json_path = self.pp_dataset_path

        if self.auxiliary_datasets.mu_dset:
            self.auxiliary_datasets.mu_dset.root_dir = self.mu_dataset_dir

        for cert in self:
            cert.set_local_paths(
                self.reports_pdf_dir,
                self.targets_pdf_dir,
                self.certificates_pdf_dir,
                self.reports_txt_dir,
                self.targets_txt_dir,
                self.certificates_txt_dir,
            )
        # TODO: This forgets to set local paths for other auxiliary datasets

    def _merge_certs(self, certs: dict[str, CCCertificate], cert_source: str | None = None) -> None:
        """
        Merges dictionary of certificates into the dataset. Assuming they all are CommonCriteria certificates
        """
        new_certs = {x.dgst: x for x in certs.values() if x not in self}
        certs_to_merge = [x for x in certs.values() if x in self]
        self.certs.update(new_certs)

        for crt in certs_to_merge:
            self[crt.dgst].merge(crt, cert_source)

        logger.info(f"Added {len(new_certs)} new and merged further {len(certs_to_merge)} certificates to the dataset.")

    def _download_csv_html_resources(self, get_active: bool = True, get_archived: bool = True) -> None:
        self.web_dir.mkdir(parents=True, exist_ok=True)

        html_items = []
        csv_items = []
        if get_active is True:
            html_items.extend(self.active_html_tuples)
            csv_items.extend(self.active_csv_tuples)
        if get_archived is True:
            html_items.extend(self.archived_html_tuples)
            csv_items.extend(self.archived_csv_tuples)

        html_urls, html_paths = [x[0] for x in html_items], [x[1] for x in html_items]
        csv_urls, csv_paths = [x[0] for x in csv_items], [x[1] for x in csv_items]

        logger.info("Downloading required csv and html files.")
        helpers.download_parallel(html_urls, html_paths)
        helpers.download_parallel(csv_urls, csv_paths)

    @serialize
    @staged(logger, "Downloading and processing CSV and HTML files of certificates.")
    def get_certs_from_web(
        self, to_download: bool = True, keep_metadata: bool = True, get_active: bool = True, get_archived: bool = True
    ) -> None:
        """
        Downloads CSV and HTML files that hold lists of certificates from common criteria website. Parses these files
        and constructs CCCertificate objects, fills the dataset with those.

        :param bool to_download: If CSV and HTML files shall be downloaded (or existing files utilized), defaults to True
        :param bool keep_metadata: If CSV and HTML files shall be kept on disk after download, defaults to True
        :param bool get_active: If active certificates shall be parsed, defaults to True
        :param bool get_archived: If archived certificates shall be parsed, defaults to True
        """
        if to_download is True:
            self._download_csv_html_resources(get_active, get_archived)

        logger.info("Adding CSV certificates to CommonCriteria dataset.")
        csv_certs = self._get_all_certs_from_csv(get_active, get_archived)
        self._merge_certs(csv_certs, cert_source="csv")

        # Someway along the way, 3 certificates get lost.
        logger.info("Adding HTML certificates to CommonCriteria dataset.")
        html_certs = self._get_all_certs_from_html(get_active, get_archived)
        self._merge_certs(html_certs, cert_source="html")

        logger.info(f"The resulting dataset has {len(self)} certificates.")

        if not keep_metadata:
            shutil.rmtree(self.web_dir)

        self._set_local_paths()
        self.state.meta_sources_parsed = True

    def _get_all_certs_from_csv(self, get_active: bool, get_archived: bool) -> dict[str, CCCertificate]:
        """
        Creates dictionary of new certificates from csv sources.
        """
        csv_sources = list(self.CSV_PRODUCTS_URL.keys())
        csv_sources = [x for x in csv_sources if "active" not in x or get_active]
        csv_sources = [x for x in csv_sources if "archived" not in x or get_archived]

        new_certs = {}
        for file in csv_sources:
            partial_certs = self._parse_single_csv(self.web_dir / file)
            logger.info(f"Parsed {len(partial_certs)} certificates from: {file}")
            new_certs.update(partial_certs)
        return new_certs

    @staticmethod
    def _parse_single_csv(file: Path) -> dict[str, CCCertificate]:
        """
        Using pandas, this parses a single CSV file.
        """

        def map_ip_to_hostname(url: str) -> str:
            if not url:
                return url
            tokens = url.split("/")
            relative_path = "/" + "/".join(tokens[3:])
            return CCDataset.BASE_URL + relative_path

        def _get_primary_key_str(row: Tag):
            return row["category"] + row["cert_name"] + row["report_link"]

        cert_status = "active" if "active" in str(file) else "archived"

        csv_header = [
            "category",
            "cert_name",
            "manufacturer",
            "scheme",
            "security_level",
            "protection_profiles",
            "not_valid_before",
            "not_valid_after",
            "report_link",
            "st_link",
            "maintenance_date",
            "maintenance_title",
            "maintenance_report_link",
            "maintenance_st_link",
        ]

        # TODO: Now skipping bad lines, smarter heuristics to be built for dumb files
        try:
            df = pd.read_csv(file, engine="python", encoding="utf-8", on_bad_lines="skip")
        except UnicodeDecodeError:
            df = pd.read_csv(file, engine="python", encoding="windows-1252", on_bad_lines="skip")
        df = df.rename(columns=dict(zip(list(df.columns), csv_header)))

        df["is_maintenance"] = ~df.maintenance_title.isnull()
        df = df.fillna(value="")

        df[["not_valid_before", "not_valid_after", "maintenance_date"]] = df[
            ["not_valid_before", "not_valid_after", "maintenance_date"]
        ].apply(pd.to_datetime, errors="coerce")

        df["dgst"] = df.apply(lambda row: helpers.get_first_16_bytes_sha256(_get_primary_key_str(row)), axis=1)

        df_base = df.loc[~df.is_maintenance].copy()
        df_main = df.loc[df.is_maintenance].copy()

        df_base.report_link = df_base.report_link.map(map_ip_to_hostname)
        df_base.st_link = df_base.st_link.map(map_ip_to_hostname)

        df_main.maintenance_report_link = df_main.maintenance_report_link.map(map_ip_to_hostname)
        df_main.maintenance_st_link = df_main.maintenance_st_link.map(map_ip_to_hostname)

        n_all = len(df_base)
        n_deduplicated = len(df_base.drop_duplicates(subset=["dgst"]))
        if (n_dup := n_all - n_deduplicated) > 0:
            logger.warning(f"The CSV {file} contains {n_dup} duplicates by the primary key.")

        df_base = df_base.drop_duplicates(subset=["dgst"])
        df_main = df_main.drop_duplicates()

        profiles = {
            x.dgst: {
                ProtectionProfile(pp_name=y, pp_eal=None)
                for y in sec_certs.utils.sanitization.sanitize_protection_profiles(x.protection_profiles)
            }
            for x in df_base.itertuples()
        }
        updates: dict[str, set] = {x.dgst: set() for x in df_base.itertuples()}
        for x in df_main.itertuples():
            updates[x.dgst].add(
                CCCertificate.MaintenanceReport(
                    x.maintenance_date.date(), x.maintenance_title, x.maintenance_report_link, x.maintenance_st_link
                )
            )

        return {
            x.dgst: CCCertificate(
                cert_status,
                x.category,
                x.cert_name,
                x.manufacturer,
                x.scheme,
                x.security_level,
                x.not_valid_before,
                x.not_valid_after,
                x.report_link,
                x.st_link,
                None,
                None,
                profiles.get(x.dgst, None),
                updates.get(x.dgst, None),
                None,
                None,
                None,
            )
            for x in df_base.itertuples()
        }

    def _get_all_certs_from_html(self, get_active: bool, get_archived: bool) -> dict[str, CCCertificate]:
        """
        Prepares dictionary of certificates from all html files.
        """
        html_sources = list(self.HTML_PRODUCTS_URL.keys())
        if get_active is False:
            html_sources = [x for x in html_sources if "active" not in x]
        if get_archived is False:
            html_sources = [x for x in html_sources if "archived" not in x]

        new_certs = {}
        for file in html_sources:
            partial_certs = self._parse_single_html(self.web_dir / file)
            logger.info(f"Parsed {len(partial_certs)} certificates from: {file}")
            new_certs.update(partial_certs)
        return new_certs

    @staticmethod
    def _parse_single_html(file: Path) -> dict[str, CCCertificate]:
        """
        Prepares a dictionary of certificates from a single html file.
        """

        def _get_timestamp_from_footer(footer):
            locale.setlocale(locale.LC_ALL, "en_US")
            footer_text = list(footer.stripped_strings)[0]
            date_string = footer_text.split(",")[1:3]
            time_string = footer_text.split(",")[3].split(" at ")[1]
            formatted_datetime = date_string[0] + date_string[1] + " " + time_string
            return datetime.strptime(formatted_datetime, " %B %d %Y %I:%M %p")

        def _parse_table(
            soup: BeautifulSoup, cert_status: str, table_id: str, category_string: str
        ) -> dict[str, CCCertificate]:
            tables = soup.find_all("table", id=table_id)

            if not len(tables) <= 1:
                raise ValueError(
                    f'The "{file.name}" was expected to contain <1 <table> element. Instead, it contains: {len(tables)} <table> elements.'
                )

            if not tables:
                return {}

            table = tables[0]
            rows = list(table.find_all("tr"))
            # header, footer = rows[0], rows[1]
            body = rows[2:]

            # It's possible to obtain timestamp of the moment when the list was generated. It's identical for each table and should thus only be obtained once. Not necessarily in each table
            # timestamp = _get_timestamp_from_footer(footer)

            # The following unused snippet extracts expected number of certs from the table
            # caption_str = str(table.findAll('caption'))
            # n_expected_certs = int(caption_str.split(category_string + ' – ')[1].split(' Certified Products')[0])

            try:
                table_certs = {
                    x.dgst: x for x in [CCCertificate.from_html_row(row, cert_status, category_string) for row in body]
                }
            except ValueError as e:
                raise ValueError(f"Bad html file: {file.name} ({str(e)})") from e

            return table_certs

        cert_status = "active" if "active" in str(file) else "archived"

        cc_cat_abbreviations = ["AC", "BP", "DP", "DB", "DD", "IC", "KM", "MD", "MF", "NS", "OS", "OD", "DG", "TC"]
        cc_table_ids = ["tbl" + x for x in cc_cat_abbreviations]
        cc_categories = [
            "Access Control Devices and Systems",
            "Boundary Protection Devices and Systems",
            "Data Protection",
            "Databases",
            "Detection Devices and Systems",
            "ICs, Smart Cards and Smart Card-Related Devices and Systems",
            "Key Management Systems",
            "Mobility",
            "Multi-Function Devices",
            "Network and Network-Related Devices and Systems",
            "Operating Systems",
            "Other Devices and Systems",
            "Products for Digital Signatures",
            "Trusted Computing",
        ]
        cat_dict = dict(zip(cc_table_ids, cc_categories))

        with file.open("r") as handle:
            soup = BeautifulSoup(handle, "html5lib")

        certs = {}
        for key, val in cat_dict.items():
            certs.update(_parse_table(soup, cert_status, key, val))

        return certs

    def _download_all_artifacts_body(self, fresh: bool = True) -> None:
        self._download_reports(fresh)
        self._download_targets(fresh)
        self._download_certs(fresh)

    @staged(logger, "Downloading PDFs of CC certification reports.")
    def _download_reports(self, fresh: bool = True) -> None:
        self.reports_pdf_dir.mkdir(parents=True, exist_ok=True)
        certs_to_process = [x for x in self if x.state.report.is_ok_to_download(fresh) and x.report_link]

        if not fresh and certs_to_process:
            logger.info(
                f"Downloading {len(certs_to_process)} PDFs of CC certification reports for which previous download failed."
            )

        cert_processing.process_parallel(
            CCCertificate.download_pdf_report,
            certs_to_process,
            progress_bar_desc="Downloading PDFs of CC certification reports",
        )

    @staged(logger, "Downloading PDFs of CC security targets.")
    def _download_targets(self, fresh: bool = True) -> None:
        self.targets_pdf_dir.mkdir(parents=True, exist_ok=True)
        certs_to_process = [x for x in self if x.state.st.is_ok_to_download(fresh)]

        if not fresh and certs_to_process:
            logger.info(
                f"Downloading {len(certs_to_process)} PDFs of CC security targets for which previous download failed.."
            )

        cert_processing.process_parallel(
            CCCertificate.download_pdf_st,
            certs_to_process,
            progress_bar_desc="Downloading PDFs of CC security targets",
        )

    @staged(logger, "Downloading PDFs of CC certificates.")
    def _download_certs(self, fresh: bool = True) -> None:
        self.certificates_pdf_dir.mkdir(parents=True, exist_ok=True)
        certs_to_process = [x for x in self if x.state.cert.is_ok_to_download(fresh)]

        if not fresh and certs_to_process:
            logger.info(
                f"Downloading {len(certs_to_process)} PDFs of CC certificates for which previous download failed.."
            )

        cert_processing.process_parallel(
            CCCertificate.download_pdf_cert,
            certs_to_process,
            progress_bar_desc="Downloading PDFs of CC certificates",
        )

    @staged(logger, "Converting PDFs of certification reports to txt.")
    def _convert_reports_to_txt(self, fresh: bool = True) -> None:
        self.reports_txt_dir.mkdir(parents=True, exist_ok=True)
        certs_to_process = [x for x in self if x.state.report.is_ok_to_convert(fresh)]

        if not fresh and certs_to_process:
            logger.info(
                f"Converting {len(certs_to_process)} PDFs of certification reports to txt for which previous conversion failed."
            )

        cert_processing.process_parallel(
            CCCertificate.convert_report_pdf,
            certs_to_process,
            progress_bar_desc="Converting PDFs of certification reports to txt",
        )

    @staged(logger, "Converting PDFs of security targets to txt.")
    def _convert_targets_to_txt(self, fresh: bool = True) -> None:
        self.targets_txt_dir.mkdir(parents=True, exist_ok=True)
        certs_to_process = [x for x in self if x.state.st.is_ok_to_convert(fresh)]

        if fresh:
            logger.info("Converting PDFs of security targets to txt.")
        if not fresh and certs_to_process:
            logger.info(
                f"Converting {len(certs_to_process)} PDFs of security targets to txt for which previous conversion failed."
            )

        cert_processing.process_parallel(
            CCCertificate.convert_st_pdf,
            certs_to_process,
            progress_bar_desc="Converting PDFs of security targets to txt",
        )

    @staged(logger, "Converting PDFs of certificates to txt.")
    def _convert_certs_to_txt(self, fresh: bool = True) -> None:
        self.certificates_txt_dir.mkdir(parents=True, exist_ok=True)
        certs_to_process = [x for x in self if x.state.cert.is_ok_to_convert(fresh)]

        if fresh:
            logger.info("Converting PDFs of certificates to txt.")
        if not fresh and certs_to_process:
            logger.info(
                f"Converting {len(certs_to_process)} PDFs of certificates to txt for which previous conversion failed."
            )

        cert_processing.process_parallel(
            CCCertificate.convert_cert_pdf,
            certs_to_process,
            progress_bar_desc="Converting PDFs of certificates to txt",
        )

    def _convert_all_pdfs_body(self, fresh: bool = True) -> None:
        self._convert_reports_to_txt(fresh)
        self._convert_targets_to_txt(fresh)
        self._convert_certs_to_txt(fresh)

    @staged(logger, "Extracting report metadata")
    def _extract_report_metadata(self) -> None:
        certs_to_process = [x for x in self if x.state.report.is_ok_to_analyze()]
        processed_certs = cert_processing.process_parallel(
            CCCertificate.extract_report_pdf_metadata,
            certs_to_process,
            use_threading=False,
            progress_bar_desc="Extracting report metadata",
        )
        self.update_with_certs(processed_certs)

    @staged(logger, "Extracting target metadata")
    def _extract_target_metadata(self) -> None:
        certs_to_process = [x for x in self if x.state.st.is_ok_to_analyze()]
        processed_certs = cert_processing.process_parallel(
            CCCertificate.extract_st_pdf_metadata,
            certs_to_process,
            use_threading=False,
            progress_bar_desc="Extracting target metadata",
        )
        self.update_with_certs(processed_certs)

    @staged(logger, "Extracting cert metadata")
    def _extract_cert_metadata(self) -> None:
        certs_to_process = [x for x in self if x.state.cert.is_ok_to_analyze()]
        processed_certs = cert_processing.process_parallel(
            CCCertificate.extract_cert_pdf_metadata,
            certs_to_process,
            use_threading=False,
            progress_bar_desc="Extracting cert metadata",
        )
        self.update_with_certs(processed_certs)

    def _extract_pdf_metadata(self) -> None:
        self._extract_report_metadata()
        self._extract_target_metadata()
        self._extract_cert_metadata()

    @staged(logger, "Extracting report frontpages")
    def _extract_report_frontpage(self) -> None:
        certs_to_process = [x for x in self if x.state.report.is_ok_to_analyze()]
        processed_certs = cert_processing.process_parallel(
            CCCertificate.extract_report_pdf_frontpage,
            certs_to_process,
            use_threading=False,
            progress_bar_desc="Extracting report frontpages",
        )
        self.update_with_certs(processed_certs)

    def _extract_pdf_frontpage(self) -> None:
        self._extract_report_frontpage()
        # We have no frontpage extraction for targets or certificates themselves, only for the reports.

    @staged(logger, "Extracting report keywords")
    def _extract_report_keywords(self) -> None:
        certs_to_process = [x for x in self if x.state.report.is_ok_to_analyze()]
        processed_certs = cert_processing.process_parallel(
            CCCertificate.extract_report_pdf_keywords,
            certs_to_process,
            use_threading=False,
            progress_bar_desc="Extracting report keywords",
        )
        self.update_with_certs(processed_certs)

    @staged(logger, "Extracting target keywords")
    def _extract_target_keywords(self) -> None:
        certs_to_process = [x for x in self if x.state.st.is_ok_to_analyze()]
        processed_certs = cert_processing.process_parallel(
            CCCertificate.extract_st_pdf_keywords,
            certs_to_process,
            use_threading=False,
            progress_bar_desc="Extracting target keywords",
        )
        self.update_with_certs(processed_certs)

    @staged(logger, "Extracting cert keywords")
    def _extract_cert_keywords(self) -> None:
        certs_to_process = [x for x in self if x.state.cert.is_ok_to_analyze()]
        processed_certs = cert_processing.process_parallel(
            CCCertificate.extract_cert_pdf_keywords,
            certs_to_process,
            use_threading=False,
            progress_bar_desc="Extracting cert keywords",
        )
        self.update_with_certs(processed_certs)

    def _extract_pdf_keywords(self) -> None:
        self._extract_report_keywords()
        self._extract_target_keywords()
        self._extract_cert_keywords()

    def extract_data(self) -> None:
        logger.info("Extracting various data from certification artifacts")
        self._extract_pdf_metadata()
        self._extract_pdf_frontpage()
        self._extract_pdf_keywords()

    @staged(logger, "Computing heuristics: Deriving information about laboratories involved in certification.")
    def _compute_cert_labs(self) -> None:
        certs_to_process = [x for x in self if x.state.report.is_ok_to_analyze()]
        for cert in certs_to_process:
            cert.compute_heuristics_cert_lab()

    @staged(logger, "Computing heuristics: Deriving information about certificate ids from artifacts.")
    def _compute_normalized_cert_ids(self) -> None:
        for cert in self:
            cert.compute_heuristics_cert_id()

    @staged(logger, "Computing heuristics: Transitive vulnerabilities in referenc(ed/ing) certificates.")
    def _compute_transitive_vulnerabilities(self):
        transitive_cve_finder = TransitiveVulnerabilityFinder(lambda cert: cert.heuristics.cert_id)
        transitive_cve_finder.fit(self.certs, lambda cert: cert.heuristics.report_references)

        for dgst in self.certs:
            transitive_cve = transitive_cve_finder.predict_single_cert(dgst)

            self.certs[dgst].heuristics.direct_transitive_cves = transitive_cve.direct_transitive_cves
            self.certs[dgst].heuristics.indirect_transitive_cves = transitive_cve.indirect_transitive_cves

    @staged(logger, "Computing heuristics: Matching scheme data.")
    def _compute_scheme_data(self):
        if self.auxiliary_datasets.scheme_dset:
            for scheme in self.auxiliary_datasets.scheme_dset:
                if certified := scheme.lists.get(EntryType.Certified):
                    certs = [cert for cert in self if cert.status == "active"]
                    matches = CCSchemeMatcher.match_all(certified, scheme.country, certs)
                    for dgst, match in matches.items():
                        self[dgst].heuristics.scheme_data = match
                if archived := scheme.lists.get(EntryType.Archived):
                    certs = [cert for cert in self if cert.status == "archived"]
                    matches = CCSchemeMatcher.match_all(archived, scheme.country, certs)
                    for dgst, match in matches.items():
                        self[dgst].heuristics.scheme_data = match

    @staged(logger, "Computing heuristics: SARs")
    def _compute_sars(self) -> None:
        transformer = SARTransformer().fit(self.certs.values())
        for cert in self:
            cert.heuristics.extracted_sars = transformer.transform_single_cert(cert)

    def _compute_heuristics(self) -> None:
        self._compute_normalized_cert_ids()
        super()._compute_heuristics()
        self._compute_scheme_data()
        self._compute_cert_labs()
        self._compute_sars()

    @staged(logger, "Computing heuristics: references between certificates.")
    def _compute_references(self) -> None:
        def ref_lookup(kw_attr):
            def func(cert):
                kws = getattr(cert.pdf_data, kw_attr)
                if not kws:
                    return set()
                res = set()
                for scheme, matches in kws["cc_cert_id"].items():
                    for match in matches:
                        try:
                            canonical = CertificateId(scheme, match).canonical
                            res.add(canonical)
                        except Exception:
                            res.add(match)
                return res

            return func

        for ref_source in ("report", "st"):
            kw_source = f"{ref_source}_keywords"
            dep_attr = f"{ref_source}_references"

            finder = ReferenceFinder()
            finder.fit(self.certs, lambda cert: cert.heuristics.cert_id, ref_lookup(kw_source))  # type: ignore

            for dgst in self.certs:
                setattr(self.certs[dgst].heuristics, dep_attr, finder.predict_single_cert(dgst, keep_unknowns=False))

    @serialize
    def process_auxiliary_datasets(self, download_fresh: bool = False) -> None:
        """
        Processes all auxiliary datasets needed during computation. On top of base-class processing,
        CC handles protection profiles, maintenance updates and schemes.
        """
        super().process_auxiliary_datasets(download_fresh)
        self.auxiliary_datasets.pp_dset = self.process_protection_profiles(to_download=download_fresh)
        self.auxiliary_datasets.mu_dset = self.process_maintenance_updates(to_download=download_fresh)
        self.auxiliary_datasets.scheme_dset = self.process_schemes(
            to_download=download_fresh, only_schemes={cert.scheme for cert in self}
        )

    @staged(logger, "Processing protection profiles.")
    def process_protection_profiles(
        self, to_download: bool = True, keep_metadata: bool = True
    ) -> ProtectionProfileDataset:
        """
        Downloads new snapshot of dataset with processed protection profiles (if it doesn't exist) and links PPs
        with certificates within self. Assigns PPs to all certificates

        :param bool to_download: If dataset should be downloaded or fetched from json, defaults to True
        :param bool keep_metadata: If json related to the PP dataset should be kept on drive, defaults to True
        :raises RuntimeError: When building of PPDataset fails
        """

        self.auxiliary_datasets_dir.mkdir(parents=True, exist_ok=True)

        if to_download or not self.pp_dataset_path.exists():
            pp_dataset = ProtectionProfileDataset.from_web(self.pp_dataset_path)
        else:
            pp_dataset = ProtectionProfileDataset.from_json(self.pp_dataset_path)

        for cert in self:
            if cert.protection_profiles is None:
                raise RuntimeError("Building of the dataset probably failed - this should not be happening.")
            cert.protection_profiles = {pp_dataset.pps.get((x.pp_name, x.pp_link), x) for x in cert.protection_profiles}

        if not keep_metadata:
            self.pp_dataset_path.unlink()

        return pp_dataset

    @staged(logger, "Processing maintenace updates.")
    def process_maintenance_updates(self, to_download: bool = True) -> CCDatasetMaintenanceUpdates:
        """
        Downloads or loads from json a dataset of maintenance updates. Runs analysis on that dataset if it's not completed.
        :return CCDatasetMaintenanceUpdates: the resulting dataset of maintenance updates
        """
        self.mu_dataset_dir.mkdir(parents=True, exist_ok=True)

        if to_download or not self.mu_dataset_path.exists():
            maintained_certs: list[CCCertificate] = [x for x in self if x.maintenance_updates]
            updates = list(
                itertools.chain.from_iterable(CCMaintenanceUpdate.get_updates_from_cc_cert(x) for x in maintained_certs)
            )
            update_dset = CCDatasetMaintenanceUpdates(
                {x.dgst: x for x in updates}, root_dir=self.mu_dataset_dir, name="maintenance_updates"
            )
        else:
            update_dset = CCDatasetMaintenanceUpdates.from_json(self.mu_dataset_path)

        if not update_dset.state.artifacts_downloaded:
            update_dset.download_all_artifacts()
        if not update_dset.state.pdfs_converted:
            update_dset.convert_all_pdfs()
        if not update_dset.state.certs_analyzed:
            update_dset.extract_data()

        return update_dset

    @staged(logger, "Processing CC scheme dataset.")
    def process_schemes(self, to_download: bool = True, only_schemes: set[str] | None = None) -> CCSchemeDataset:
        """
        Downloads or loads from json a dataset of CC scheme data.
        """
        self.auxiliary_datasets_dir.mkdir(parents=True, exist_ok=True)

        if to_download or not self.scheme_dataset_path.exists():
            scheme_dset = CCSchemeDataset.from_web(only_schemes)
            scheme_dset.to_json(self.scheme_dataset_path)
        else:
            scheme_dset = CCSchemeDataset.from_json(self.scheme_dataset_path)

        return scheme_dset


class CCDatasetMaintenanceUpdates(CCDataset, ComplexSerializableType):
    """
    Dataset of maintenance updates related to certificates of CCDataset dataset.
    Should be used merely for actions related to Maintenance updates: download pdfs, convert pdfs, extract data from pdfs
    """

    # Quite difficult to achieve correct behaviour with MyPy here, opting for ignore
    def __init__(
        self,
        certs: dict[str, CCMaintenanceUpdate] = {},  # type: ignore
        root_dir: Path = constants.DUMMY_NONEXISTING_PATH,
        name: str = "dataset name",
        description: str = "dataset_description",
        state: CCDataset.DatasetInternalState | None = None,
    ):
        super().__init__(certs, root_dir, name, description, state)  # type: ignore
        self.state.meta_sources_parsed = True

    @property
    def certs_dir(self) -> Path:
        return self.root_dir

    def __iter__(self) -> Iterator[CCMaintenanceUpdate]:
        yield from self.certs.values()  # type: ignore

    def _compute_heuristics(self) -> None:
        raise NotImplementedError

    def compute_related_cves(self) -> None:
        raise NotImplementedError

    def process_auxiliary_datasets(self, download_fresh: bool = False) -> None:
        raise NotImplementedError

    def analyze_certificates(self) -> None:
        raise NotImplementedError

    def get_certs_from_web(
        self, to_download: bool = True, keep_metadata: bool = True, get_active: bool = True, get_archived: bool = True
    ) -> None:
        raise NotImplementedError

    @classmethod
    def from_json(cls, input_path: str | Path, is_compressed: bool = False) -> CCDatasetMaintenanceUpdates:
        dset = cast(CCDatasetMaintenanceUpdates, ComplexSerializableType.from_json(input_path, is_compressed))
        dset._root_dir = Path(input_path).parent.absolute()
        return dset

    def to_pandas(self) -> pd.DataFrame:
        df = pd.DataFrame([x.pandas_tuple for x in self.certs.values()], columns=CCMaintenanceUpdate.pandas_columns)
        df = df.set_index("dgst")
        df.index.name = "dgst"

        df.maintenance_date = pd.to_datetime(df.maintenance_date, errors="coerce")
        return df.fillna(value=np.nan)

    @classmethod
    def from_web_latest(cls) -> CCDatasetMaintenanceUpdates:
        with tempfile.TemporaryDirectory() as tmp_dir:
            dset_path = Path(tmp_dir) / "cc_maintenances_latest_dataset.json"
            helpers.download_file(config.cc_maintenances_latest_snapshot, dset_path)
            return cls.from_json(dset_path)

    def get_n_maintenances_df(self) -> pd.DataFrame:
        """
        Returns a DataFrame with CCCertificate digest as an index, and number of registered maintenances as a value
        """
        main_df = self.to_pandas()
        main_df.maintenance_date = main_df.maintenance_date.dt.date
        n_maintenances = (
            main_df.groupby("related_cert_digest").name.count().rename("n_maintenances").fillna(0).astype("int32")
        )

        n_maintenances.index.name = "dgst"
        return n_maintenances

    def get_maintenance_dates_df(self) -> pd.DataFrame:
        """
        Returns a DataFrame with CCCertificate digest as an index, and all the maintenance dates as a value.
        """
        main_dates = self.to_pandas()
        main_dates.maintenance_date = main_dates.maintenance_date.map(lambda x: [x])
        main_dates.index.name = "dgst"
        return main_dates.groupby("related_cert_digest").maintenance_date.agg("sum").rename("maintenance_dates")