Module: HEITT::Analyzer

Defined in:
lib/heitt/analyzer.rb

Class Method Summary collapse

Class Method Details

.algorithm_scores(keyword_counts, profiles: HEITT::PROFILES) ⇒ Object

database: HEITT::DATABASE)



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# File 'lib/heitt/analyzer.rb', line 94

def self.algorithm_scores(keyword_counts, profiles: HEITT::PROFILES)#database: HEITT::DATABASE)
  scores = {}
  return scores if keyword_counts.nil?

  profiles.each do |name, profile| #database.each do |entry|
    context = profile[:context] || []
    next if context.empty?
    #modes = get_modes(entry)
    #next unless modes
    #modes.each do |mode|
    #  contexts = mode[:context] || []
    #  next if contexts.empty?
    total = context.sum {|kw| keyword_counts[kw.downcase] || 0}
    scores[name] = total if total > 0
  #  end
  end
  scores
end

.analyze(text, profiles: HEITT::PROFILES) ⇒ Object

database: HEITT::DATABASE)



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# File 'lib/heitt/analyzer.rb', line 5

def self.analyze(text, profiles: HEITT::PROFILES)#database: HEITT::DATABASE)
  keyword_counts = keyword_counts(text.downcase, profiles: profiles)
  algorithm_scores(keyword_counts, profiles: profiles)
end

.assign_confidence(scores_hash, prefix_matched_mode = nil) ⇒ Object 



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# File 'lib/heitt/analyzer.rb', line 125

def self.assign_confidence(scores_hash,  prefix_matched_mode=nil)
  all_scores = scores_hash.values

  return {} if all_scores.empty?

  avg_score = all_scores.sum.to_f / all_scores.size
 
  scores_hash.transform_values do |score|
    if score == 0
      "regex-match"
    else
      mode_name = scores_hash.key(score)
      is_prefix_mode = (prefix_matched_mode == mode_name)
      deviation = (score - avg_score) / avg_score

      case deviation
      when 2.0..Float::INFINITY
        "high"
      when 0.5..2.0
        is_prefix_mode ? "high" : "medium-high"
      else
        is_prefix_mode ? "medium-high" : "medium-low"
      end
    end 
  end
end

.entropy(text) ⇒ Object

this code is an inspiration of "https://github.com/chrisjchandler/entropy/blob/main/entropy.go"



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# File 'lib/heitt/analyzer.rb', line 61

def self.entropy(text)
  frequency = Hash.new(0)
  text.each_char { |ch| frequency[ch] += 1 }

  #calculate the total number of characters
  total = text.length.to_f
  #caluclate entropy
  entropy = 0.0
  frequency.each_value do |count|
    probability = count.to_f / total
    entropy += probability * Math.log2(probability)
  end
  #negate the sum as entropy is positive
  -entropy
end

.extract_prefix(text, offset) ⇒ Object 



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# File 'lib/heitt/analyzer.rb', line 10

def self.extract_prefix(text, offset)
  line_start = text.rindex("\n", offset) || 0
  text[line_start...offset]
end

.high_entropy?(text, min_ent) ⇒ Boolean

Returns:

  • (Boolean) 


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# File 'lib/heitt/analyzer.rb', line 15

def self.high_entropy?(text, min_ent)
  entropy(text) >= min_ent
end

.keyword_counts(content_lower, profiles: HEITT::PROFILES) ⇒ Object

HEITT::DATABASE)



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# File 'lib/heitt/analyzer.rb', line 77

def self.keyword_counts(content_lower, profiles: HEITT::PROFILES) #HEITT::DATABASE)
  keywords = profiles.values.flat_map { |p| p[:context] || [] }.uniq.map(&:downcase)
  #database.flat_map do |entry|
    #modes = get_modes(entry)
    #next [] unless modes
    #modes.flat_map {|mode| HEITT::PROFILES[mode[:name]][:context] || []}
  #end#.uniq.map(&:downcase)

  counts = {}
  keywords.each do |kw|
    count = content_lower.scan(/\b#{Regexp.escape(kw)}\b/).size
    counts[kw] = count if count > 0
  end
  counts
end

.prefix_match?(profile, delim_prefix) ⇒ Boolean

Returns:

  • (Boolean) 


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# File 'lib/heitt/analyzer.rb', line 114

def self.prefix_match?(profile, delim_prefix)
  #prefixes = mode[:prefixes] || []
  prefixes = profile[:prefixes] || []
  return false if prefixes.empty?

  delimiters =  "= : "
  raw_prefix = delim_prefix.strip.split(/[#{Regexp.escape(delimiters)}]/).last&.strip&.downcase
  prefixes.map(&:downcase).include?(raw_prefix)
end

.score_candidates(modes, delim_prefix, context_scores, profiles: HEITT::PROFILES) ⇒ Object 



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# File 'lib/heitt/analyzer.rb', line 20

def self.score_candidates(modes, delim_prefix, context_scores, profiles: HEITT::PROFILES)
  prefix_matched_mode = nil
  #context based scoring
  matches = modes.map do |mode|
    profile = profiles[mode[:name]] || {}
    score = context_scores[mode[:name]] || 0
    #score = score_data || 0

    if prefix_match?(profile, delim_prefix)
      #boost score as confidence is high if prefix matched
      prefix_matched_mode = mode[:name]
      score += 20
    end
    {
      name: mode[:name],
      hashcat: mode[:hashcat],
      john: mode[:john],
      extended: mode[:extended],
      description: profile[:description],
      notes: profile[:notes],
      score: score
    }
  end 
  return [] if matches.empty?

  #calculate confidence
  scores_hash = matches.map {|m| [m[:name], m[:score]]}.to_h 
  
  confidences = assign_confidence(scores_hash, prefix_matched_mode)
  scored_candidates = matches.map{|m| m.merge(confidence: confidences[m[:name]])}.sort_by {|m| -m[:score]}
  scored_candidates
end