What you need to know
- The source code for Twitch's streaming service has been leaked online by an anonymous hacker.
- The leak includes creator payout reports, the entirety of twitch.tv, and an unreleased Steam rival.
- It is believed that the data may have been obtained earlier this week.
An anonymous hacker has leaked the entirety of Twitch in a 125GB torrent uploaded to 4chan, according to Video Games Chronicle. The report suggests the data may have been obtained as recently as Monday.
Twitch has confirmed the breach with Android Central and promised to share additional details after it completes its investigation.
In addition to Twitch's entire source code, the leak is said to contain creator payout reports from 2019, proprietary SDKs and internal AWS services, internal "red teaming tools," as well as an unreleased Steam challenger codenamed Vapor from Amazon Game Studios.
The torrent file has been named "Twitch leaks part one" by the hacker, which seems to suggest more data could be leaked online soon. It remains unclear if the hacker was able to obtain personal information of Twitch users, such as their account password or address.
If you are a Twitch user, it is highly recommended that you change your password and enable two-factor authentication for your account. To enable two-factor authentication, log in to your Twitch account and click on your avatar. Next, click on Settings and head over to the Security and Privacy page to begin setting up two-factor authentication. It is worth noting, however, that the email tied to your Twitch account must be verified for 2FA to be enabled.
Twitch has recently been under fire for its inaction over hate and harassment on its platform. Last month, some Twitch streamers boycotted the company for a day to put pressure on it to do something about hate raids.
Back in August, Twitch rolled out an update to fix a "vulnerability" in its proactive filters to "better detect hate speech" in chat. It also plans to improve its account verification process and launch channel-level ban detection to address harassment.
