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racfor_wiki:email:automated_spear_phishing_using_machine_learning [2020/01/07 22:58] divankovic |
racfor_wiki:email:automated_spear_phishing_using_machine_learning [2024/12/05 12:24] (trenutno) |
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| Redak 68: | Redak 68: | ||
| SNAP_R uses a recurrent neural network or a Markov model trained on spear phishing pen-testing data and tweets, which will be described in more detail in the model training section. | SNAP_R uses a recurrent neural network or a Markov model trained on spear phishing pen-testing data and tweets, which will be described in more detail in the model training section. | ||
| - | The profiling of the users is done by extracting topics from the target' | + | The profiling of the users is done by extracting topics from the target' |
| The most frequent words (excluding the stopwords - words like the, in, at, that, which, …) were the most effective way for seeding [6]. The phishing tweet is sent within the hour that the target is most active (schedule_tweet_and_sleep()) or immediately (post_tweet_and_sleep()). The hour that the target is the most active at is determined by simply counting the total number of tweets in each hour. | The most frequent words (excluding the stopwords - words like the, in, at, that, which, …) were the most effective way for seeding [6]. The phishing tweet is sent within the hour that the target is most active (schedule_tweet_and_sleep()) or immediately (post_tweet_and_sleep()). The hour that the target is the most active at is determined by simply counting the total number of tweets in each hour. | ||
| Redak 164: | Redak 164: | ||
| Copying and pasting turned out to be a problem, as Twitter stops users from posting the same message too frequently. | Copying and pasting turned out to be a problem, as Twitter stops users from posting the same message too frequently. | ||
| - | A single instance of SNAP_R tool was run during 2 hours. SNAP_R sent phishing tweets to 819 usera at 6.85 tweets/ | + | A single instance of SNAP_R tool was run during 2 hours. SNAP_R sent phishing tweets to 819 users at 6.85 tweets/ |
| The human managed to send 129 phishing tweets (with copying and pasting pre-made tweets) at 1.075 tweets/ | The human managed to send 129 phishing tweets (with copying and pasting pre-made tweets) at 1.075 tweets/ | ||