In May, a video of a woman flouting a national Covid-19 mask mandate went viral on social media in Singapore. In the clip, the bare-faced woman argues with passersby outside of a grocery store, defending herself as “a sovereign” and therefore exempt from the law. 

Following her arrest later that day, internet detectives took matters into their own hands to ensure that justice was served. They soon identified the woman as the CEO of a digital security firm. Within hours, social media users had posted her personal information and the names and photographs of her employees. 

The only problem was, they got the wrong person. Internet sleuths mistook the woman for business executive Tuhina Singh, but two days after the incident, she was identified at a court appearance as Paramjeet Kaur, a physiotherapist. The damage had already been done: false accusations against Singh had prompted a torrent of racist and xenophobic comments online.

The easy availability of information on the internet has made open source intelligence — OSINT — a valuable tool for researchers and ordinary web users. Collaborative group research, and the subsequent shaming of individuals, uses publicly available data gathered across social media platforms, including facial recognition, IP addresses, satellite imagery, news media and online public records. Around the world, OSINT, which dates back to World War II but gained momentum after the 9/11 attacks in 2001, has been used to spot burned villages in Myanmar, reveal Russian bombings of hospitals in Syria, profile surveillance hubs operated by U.S. law enforcement and even to locate internationally wanted animal abusers.