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With more than 500 million daily tweets from over 330 million active users,Twitter constantly attracts malicious users aiming to carry out phishing andmalware-related attacks against its user base. It therefore becomes ofparamount importance to assess the effectiveness of Twitter's use of blacklistsin protecting its users from such threats. We collected more than 182 millionpublic tweets containing URLs from Twitter's Stream API over a 2-month periodand compared these URLs against 3 popular phishing, social engineering, andmalware blacklists, including Google Safe Browsing (GSB). We focus on the delayperiod between an attack URL first being tweeted to appearing on a blacklist,as this is the timeframe in which blacklists do not warn users, leaving themvulnerable. Experiments show that, whilst GSB is effective at blocking a numberof social engineering and malicious URLs within 6 hours of being tweeted, asignificant number of URLs go undetected for at least 20 days. For instance,during one month, we discovered 4,930 tweets containing URLs leading to socialengineering websites that had been tweeted to over 131 million Twitter users.We also discovered 1,126 tweets containing 376 blacklisted Bitly URLs that hada combined total of 991,012 clicks, posing serious security and privacythreats. In addition, an equally large number of URLs contained within publictweets remain in GSB for at least 150 days, raising questions about potentialfalse positives in the blacklist. We also provide evidence to suggest thatTwitter may no longer be using GSB to protect its users.

Catch Me (On Time) If You Can: Understanding the Effectiveness of Twitter URL Blacklists