mirror of
http://git.nowherejezfoltodf4jiyl6r56jnzintap5vyjlia7fkirfsnfizflqd.onion/nihilist/darknet-lantern.git
synced 2025-07-02 03:06:41 +00:00
FINished adding the trusted and the refactoring of 6
This commit is contained in:
doctor_dev
parent
8b0ba4833f
commit
14231fff92
5 changed files with 631 additions and 321 deletions
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@ -7,11 +7,15 @@ def download_participant_data(participant):
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"""
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Downloads the participants csv files and banner
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Parameters:
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participant (str): The url of the webring participant.
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Parameters
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----------
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participant : str
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The url of the webring participant.
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Returns:
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Boolean: True if all files downloaded, False if any of them failed
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Returns
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-------
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Boolean
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True if all files downloaded, False if any of them failed
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"""
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try:
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@ -44,28 +48,34 @@ def download_participant_data(participant):
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utils.print_colors(f"[+] Downloaded webring {participant} csv files and banner")
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except Exception as err:
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print_colors("[-] Downloading webring participant's files failed.", is_error=True)
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utils.print_colors("[-] Downloading webring participant's files failed.", is_error=True)
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def clean_csv(df, blacklist):
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"""
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Cleans duplications and blacklisted rows
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Parameters:
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df (dataframe): The dataframe we want to clean.
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blacklist (list): The blacklisted words.
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Parameters
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----------
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df pd.DataFrame
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The dataframe we want to clean.
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blacklist : list
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The blacklisted words.
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Returns:
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Dataframe: Cleaned dataframe.
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Returns
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-------
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pd.DataFrame
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Cleaned dataframe.
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"""
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try:
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if not df.empty:
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df = utils.remove_duplications(df)
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df = df[~df.apply(lambda row: any(word in str(value) for word in blacklist for value in row), axis=1)]
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if not df.empty:
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df = df[df.apply(utils.is_row_valid, axis=1)]
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except Exception as err:
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print_colors("[-] cleaning dataframe failed", is_error=True)
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@ -75,12 +85,17 @@ def mark_sensitive(df, sensitive_list):
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"""
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Marks rows as sensitive
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Parameters:
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df (dataframe): The dataframe we want to mark.
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sensitive (list): The sensitive words.
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Parameters
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----------
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df : pd.DataFrame
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The dataframe we want to mark.
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sensitive : list
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The sensitive words.
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Returns:
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Dataframe: Marked dataframe.
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Returns
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-------
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pd.DataFrame
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Marked dataframe.
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"""
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try:
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@ -91,6 +106,72 @@ def mark_sensitive(df, sensitive_list):
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df.loc[~sensitive_rows, 'Sensitive'] = 'NO'
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except Exception as err:
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print_colors("[-] MArking sensitive words failed.", is_error=True)
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print_colors("[-] Marking sensitive words failed.", is_error=True)
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return df
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return df
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def mark_webring_participant_trusted(webring_df, participant_id, trustworthy):
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"""
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Marks a webring to be trusted or not
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Parameters
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----------
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webring_df : pd.DataFrame
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dataframe of all the webring participants
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participant_id : int
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the index of the participant
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trustworthy : bool
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is the participant trustworthy or not
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Returns
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-------
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pd.DataFrame
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Marked webring dataframe with trust/untrust.
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"""
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try:
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webring_df.iloc[participant_id, webring_df.columns.get_loc('Trusted')] = "YES" if trustworthy else "NO"
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except Exception as err:
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utils.print_colors("[-] Trusting or untrusting a webring participant failed", is_error = True)
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return webring_df
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def mark_webring_participant_blacklist(webring_df, participant_instance, participant_id, blacklisted):
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"""
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Marks a webring to be blacklisted or not
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Parameters
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----------
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webring_df : pd.DataFrame
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dataframe of all the webring participants
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participant_id :int
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the index of the participant
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blacklisted : bool
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is the participant set to be blacklisted or not
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Returns
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-------
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pd.DataFrame
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Marked webring dataframe with blacklist/unblacklist.
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"""
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try:
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if blacklisted:
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webring_df.iloc[participant_id, webring_df.columns.get_loc('Blacklisted')] = "YES"
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utils.print_colors(f'[+] Adding new word to blacklist')
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local_blacklist_df = utils.add_word_to_blacklist(participant_instance)
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else:
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webring_df.iloc[participant_id, webring_df.columns.get_loc('Blacklisted')] = "NO"
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utils.print_colors(f'[+] Removing word from blacklist')
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local_blacklist_df = utils.remove_word_from_blacklist(participant_instance)
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except Exception as err:
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utils.print_colors("[-] Blacklisting or unblacklisting a webring participlant failed", is_error = True)
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raise err
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return webring_df
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213
scripts/logic/options.py
Normal file
213
scripts/logic/options.py
Normal file
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@ -0,0 +1,213 @@
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import utils
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import conf
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import lantern_logic as lantern
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def run_option_4():
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try:
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utils.print_colors("4) Synchronize new links from new or existing webring participants, into your local csv files")
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utils.print_colors('[+] Syncing official webrings to local webrings')
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webring_df = utils.get_local_webring_participants()
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current_instance = utils.get_current_instance()
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utils.print_colors('[+] Reading local blacklist and sensitive words')
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local_blacklist_df = utils.get_local_blacklist()
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local_sensitive_df = utils.get_local_sensitive()
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utils.print_colors('[+] Reading local verified and unverified')
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local_verified_df, local_unverified_df = utils.get_local_verified_and_unverified()
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#Remove all rows
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local_unverified_df = local_unverified_df[0:0]
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local_verified_df = local_verified_df[0:0]
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for participant in webring_df.itertuples(index=False, name='columns'):
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# Check if the participant is my instance
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if current_instance in participant:
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continue
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if participant.Blacklisted == 'YES':
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continue
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if not utils.is_participant_reachable(participant.URL):
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utils.print_colors("[-] Webring {participant.URL} isn't reachable, skipping", is_error=True)
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continue
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utils.print_colors('[+] Downloading participant\'s files to store locally')
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lantern.download_participant_data(participant.URL)
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participant_url = utils.generate_local_participant_dir(participant.URL)
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utils.print_colors('[+] Reading webrring participant\'s verified and unverified')
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participant_verified_df, participant_unverified_df = utils.get_participant_local_verified_and_unverified(participant_url)
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utils.print_colors('[+] Removing unvalidated and blacklisted rows')
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participant_verified_df = lantern.clean_csv(participant_verified_df, local_blacklist_df['blacklisted-words'].tolist())
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participant_unverified_df = lantern.clean_csv(participant_unverified_df, local_blacklist_df['blacklisted-words'].tolist())
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utils.print_colors('[+] Marking sensitive rows')
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participant_verified_df = lantern.mark_sensitive(participant_verified_df, local_sensitive_df['sensitive-words'].tolist())
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participant_unverified_df = lantern.mark_sensitive(participant_unverified_df, local_sensitive_df['sensitive-words'].tolist())
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if participant.Trusted == 'YES':
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utils.print_colors('[+] This participant is trusted, copying participant\'s verified to local verified')
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local_verified_df = utils.merge_verification_df(local_verified_df, participant_verified_df)
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else:
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utils.print_colors('[+] This participant is not trusted, copying participant\'s verified to local unverified')
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local_unverified_df = utils.merge_verification_df(local_unverified_df, participant_verified_df)
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utils.print_colors('[+] Copying participant\'s unverified to local unverified')
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local_unverified_df = utils.merge_verification_df(local_unverified_df, participant_unverified_df)
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utils.print_colors('[+] Saving local verified and unverified')
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utils.save_local_verified_and_unverified(local_verified_df, local_unverified_df)
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except Exception as err:
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utils.print_colors("[-] Option 4 failed suddently, please try again", is_error=True)
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def run_option_6():
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while True:
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utils.print_colors("[+] Trust/UnTrust/Blacklist a webring participant (Potentially dangerous)")
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webring_df = utils.get_local_webring_participants()
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webring_path = conf.LOCAL_DIR + conf.WEBRING_CSV_FILE
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utils.print_colors(f'{webring_df[["URL","Trusted", "Blacklisted"]]}')
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try:
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index = int(input('What is the index of the webring participant that you want to edit? -1 to exit ').strip())
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if index == -1:
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break
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if index in webring_df.index:
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choice = input('Do you want to 1) Trust, 2) UnTrust, or 3) Blacklist the webring participant?').strip()
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utils.print_colors('[+] Reading local verified and unverified')
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local_verified_df, local_unverified_df = utils.get_local_verified_and_unverified()
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participant_instance = webring_df.iloc[index, webring_df.columns.get_loc("URL")]
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match choice:
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case '1':
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# trust the webring participant
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approve=input('You\'re about to trust another peer, this means that you\'re going to automatically trust all of the links they have in their verified.csv file! If this is a malicious peer, this action might be potentially risky! Do you want to continue ? (y/n)')
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# to lower case incase someone enters Y instead of y
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if approve.lower() == 'y':
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try:
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utils.print_colors(f'[+] Trusting webring participant {participant_instance}')
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webring_df = lantern.mark_webring_participant_trusted(webring_df, index, True)
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webring_df = lantern.mark_webring_participant_blacklist(webring_df, participant_instance, index, False)
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except Exception as err:
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utils.print_colors('[-] Trusting webring participant failed', is_error=True)
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else:
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utils.print_colors('[-] not trusting webring participant', is_error=True)
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case '2':
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try:
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utils.print_colors(f'[+] Untrusting webring participant {participant_instance}')
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webring_df = lantern.mark_webring_participant_trusted(webring_df, index, False)
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webring_df = lantern.mark_webring_participant_blacklist(webring_df, participant_instance, index, False)
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except Exception as err:
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utils.print_colors('[-] Untrusting webring participant failed', is_error=True)
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case '3':
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try:
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utils.print_colors(f'[+] Blacklisting webring participant {participant_instance}')
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webring_df = lantern.mark_webring_participant_trusted(webring_df, index, False)
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webring_df = lantern.mark_webring_participant_blacklist(webring_df, participant_instance, index, True)
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local_blacklist_df = utils.get_local_blacklist()
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utils.print_colors('[+] Removing unvalidated and blacklisted rows')
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local_verified_df = lantern.clean_csv(local_verified_df, local_blacklist_df['blacklisted-words'].tolist())
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local_unverified_df = lantern.clean_csv(local_verified_df, local_blacklist_df['blacklisted-words'].tolist())
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participant_dir = f'{conf.PARTICIPANT_DIR}{participant_instance}'
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utils.print_colors(f"[+] removing the participant's directory at {participant_dir}")
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shutil.rmtree(participant_dir)
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except FileNotFoundError as err:
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utils.print_colors('[-] File already blacklisted', is_error=True)
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except Exception as err:
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utils.print_colors('[-] Blacklisting webring participant failed', is_error=True)
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utils.save_dataframe(webring_df, webring_path)
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utils.print_colors('[+] Saving local verified and unverified')
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utils.save_local_verified_and_unverified(local_verified_df, local_unverified_df)
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except Exception as err:
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utils.print_colors("[-] Option 6 failed suddently, please try again", is_error=True)
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def run_option_9():
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utils.print_colors("[+] 9) Cleaning up all duplicates in your own unverified + verified.csv (based on the url)")
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try:
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utils.print_colors('[+] Reading local verified and unverified')
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verified_df, unverified_df = utils.get_local_verified_and_unverified()
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utils.print_colors('[+] Removing cross dataframe replications')
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verified_df, unverified_df = utils.remove_cross_dataframe_replications(verified_df, unverified_df)
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utils.print_colors('[+] Saving local verified and unverified')
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utils.save_local_verified_and_unverified(verified_df, unverified_df)
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except Exception as err:
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utils.print_colors("[-] Option 9 failed suddenly, please try again", is_error=True)
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def run_option_10():
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utils.print_colors("[+] 10) perform sanity checks on all csv files (to mark them as sensitive / or remove the ones that are blacklisted)")
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try:
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utils.print_colors('[+] Reading local blacklist and sensitive words')
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local_blacklist_df = utils.get_local_blacklist()
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local_sensitive_df = utils.get_local_sensitive()
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for participant in os.listdir(conf.PARTICIPANT_DIR):
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participant_local_dir = conf.PARTICIPANT_DIR + participant + '/'
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utils.print_colors('[+] Reading webrring participant\'s verified and unverified')
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participant_verified_df, participant_unverified_df = utils.get_participant_local_verified_and_unverified(participant_local_dir)
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utils.print_colors('[+] Removing unverified and blacklisted rows')
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participant_verified_df = lantern.clean_csv(participant_verified_df, local_blacklist_df['blacklisted-words'].tolist())
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participant_unverified_df = lantern.clean_csv(participant_unverified_df, local_blacklist_df['blacklisted-words'].tolist())
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utils.print_colors('[+] Marking sensitive rows')
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participant_verified_df = lantern.mark_sensitive(participant_verified_df, local_sensitive_df['sensitive-words'].tolist())
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participant_unverified_df = lantern.mark_sensitive(participant_unverified_df, local_sensitive_df['sensitive-words'].tolist())
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utils.print_colors('[+] Saving local participant verified and unverified')
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utils.save_local_participant_verified_and_unverified(participant_verified_df, participant_unverified_df, participant_local_dir)
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except Exception as err:
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utils.print_colors("[-] Option 10 failed suddently, please try again", is_error=True)
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