Early Detection of the Weibo Data Breach: A Case Study
Last month at the end of March, Sina Weibo publicly announced that it had suffered a data breach. As one of the largest Chinese social media platforms with more than 600 million registered users, the breach was a huge hit to their brand and reputation. A hacker seems to have obtained a part of the company’s user database, affecting 538 million Weibo users and their personal details which include real names, site usernames, gender, location, and phone numbers. But early detection of the data breach through advanced web monitoring could have mitigated the financial and reputational damage inflicted on the organization.
This is not the first major social network that has suffered a serious data breach in 2019. Facebook announced three major data breaches last year; Instagram reported a data breach in May that included bio, profile photo, location, verification status, email address and phone numbers of 49 million high-profile accounts; and Flipboard, a social news app, suffered two major data breaches.
Seizing the Window of Opportunity
Unfortunately, even with the best risk mitigation plan in place, social media networks will continue to be hacked or breached in the future. But by leveraging early detection of data breaches with advanced dark web monitoring technology, organizations can greatly mitigate the damage to their users and brand.
As we’ve explained in earlier posts, the time before a data breach is detected and notified to the public is the most essential, since it can prevent the most damage to the organization. This is especially true when the name of the organization is explicitly mentioned. Hackers know that when they mention the name of an organization they don’t have much more time to profit from the breach. Those few days between the time the breach is detected and the time it is officially announced in the media makes a huge difference.
Webz’s Cyber API was able to successfully detect one of the first posts selling the data about the Weibo breach in a Chinese Dark Web marketplace – posted before the first official publication in the media.
In addition, the Cyber API was able to detect the same actor in multiple forums offering this database for sale.
We also found mentions of a sale of the Weibo breach in English in a Telegram chat.
Detecting Data Breach Mentions in Multiple Languages
Dark web cybercriminals exist all over the world and do business in many different languages. Although the majority of posts relating to social media breaches have been in English in the Webz.io Cyber API , there were also significant numbers of posts in Chinese and Russian.
Source: Webz.io Cyber API
Here is an example of two separate reports about the Weibo breach found in the Cyber API. The first is from a hacker site’s news section in Russian. The next two, one in Russian and another in Italian, are from different Telegram channels.
Reducing the Negative Impact from Data Breaches
The average loss for a data breach is close to $3 million for each organization. But the damage goes far beyond financial loss. Research has demonstrated that up to a third of customers in the health, finance and retail industries will stop doing business with a brand that has suffered a data breach. New customers after a breach can also become far more expensive to acquire. But early detection can vastly reduce both the monetary damage and reputational impact of a data breach through advanced web monitoring and data breach detection in multiple languages, marketplaces and forums. It’s all about identifying and leveraging that window of opportunity.