system: You are an expert security code reviewer. You will be shown a source code file along with a multi-select question listing several CWE (Common Weakness Enumeration) categories. Your task is to identify which of the listed CWEs are present in the code.

OUTPUT FORMAT: Respond with the letter(s) of all correct options, sorted alphabetically and comma-separated, wrapped in a single \boxed{...}. Examples: `\boxed{A}` for one correct, `\boxed{A,C}` for two, `\boxed{A,C,E}` for three. Output the boxed answer ONLY -- no explanation, no other text.

user: ```python
import re
import string
from nltk.corpus import stopwords
from spellchecker import SpellChecker
import wordninja 

spell = SpellChecker()


def remove_emoji(text):
    """
    Removes emojis from text.
    """
    emoji_pattern = re.compile("["
                           u"\U0001F600-\U0001F64F"  # emoticons
                           u"\U0001F300-\U0001F5FF"  # symbols & pictographs
                           u"\U0001F680-\U0001F6FF"  # transport & map symbols
                           u"\U0001F1E0-\U0001F1FF"  # flags (iOS)
                           u"\U00002702-\U000027B0"
                           u"\U000024C2-\U0001F251"
                           "]+", flags=re.UNICODE)
    return emoji_pattern.sub(r'', text)


def remove_url(text):
    """
    Removes URLs from the text.
    """
    url = re.compile(r'https?://\S+|www\.\S+')
    return url.sub(r'',text)


def remove_html(text):
    """
    Removes HTML tags from the text.
    """
    html=re.compile(r'<.*?>')
    return html.sub(r'',text)


def remove_punct(text):
    """
    Removes punctuation from the text.
    """
    table=str.maketrans('','',string.punctuation)
    return text.translate(table)


def correct_spelling(text):
    """
    Corrrects some spelling errors using pyspellcheker.
    """
    corrected_text = []
    misspelled_words = spell.unknown(text.split())
    for word in text.split():
        if word in misspelled_words:
            corrected_text.append(spell.correction(word))
        else:
            corrected_text.append(word)
    return " ".join(corrected_text)


def decontract(text):
    """
    Decontracts contractions.
    E.g: won't -> will not
    """
    # specific
    text = re.sub(r"won\'t", " will not", text)
    text = re.sub(r"won\'t've", " will not have", text)
    text = re.sub(r"can\'t", " can not", text)
    text = re.sub(r"don\'t", " do not", text)
    text = re.sub(r"can\'t've", " can not have", text)
    text = re.sub(r"ma\'am", " madam", text)
    text = re.sub(r"let\'s", " let us", text)
    text = re.sub(r"ain\'t", " am not", text)
    text = re.sub(r"shan\'t", " shall not", text)
    text = re.sub(r"sha\n't", " shall not", text)
    text = re.sub(r"o\'clock", " of the clock", text)
    text = re.sub(r"y\'all", " you all", text)
    # general
    text = re.sub(r"n\'t", " not", text)
    text = re.sub(r"n\'t've", " not have", text)
    text = re.sub(r"\'re", " are", text)
    text = re.sub(r"\'s", " is", text)
    text = re.sub(r"\'d", " would", text)
    text = re.sub(r"\'d've", " would have", text)
    text = re.sub(r"\'ll", " will", text)
    text = re.sub(r"\'ll've", " will have", text)
    text = re.sub(r"\'t", " not", text)
    text = re.sub(r"\'ve", " have", text)
    text = re.sub(r"\'m", " am", text)
    text = re.sub(r"\'re", " are", text)
    return text


def split_attached_words(text):
    """
    Split attached words especially common with twitter hashtags. 
    E.g.: famousactor -> famous actor
    """
    words = wordninja.split(text)
    return " ".join(words)


def remove_hashtag_split(text):
    """
    Removes hashtags and splits the tags into separeted words.
    E.g.: #famousactor -> famous actor
    """
    hashtag_list = re.findall("#(\w+)", text) 
    for hashtag in hashtag_list: 
        text = text.replace(f'#{hashtag}', split_attached_words(hashtag))
    return text


def remove_stopwords(text):
    """
    Removes stop words from text.
    """
    words = text.split()
    stop_words = set(stopwords.words('english'))
    words = [w for w in words if not w in stop_words]
    return " ".join(words)


```

Which of the following CWE vulnerability categories are present in this code? Multiple options may be correct.

  A) CWE-20: Improper Input Validation
  B) CWE-377: Insecure Temporary File
  C) CWE-209: Generation of Error Message Containing Sensitive Information
  D) CWE-116: Improper Encoding or Escaping of Output
  E) CWE-614: Sensitive Cookie in HTTPS Session Without 'Secure' Attribute
  F) CWE-732: Incorrect Permission Assignment for Critical Resource
Answer: A