There are at least 35,000 publicly accessible and insecure MongoDB databases on the Internet, and their number appears to be growing. Combined they expose 684.8 terabytes of data to potential theft.
This is the result of a scan performed over the past few days by John Matherly, the creator of the Shodan search engine for Internet-connected devices.
Matherly originally sounded the alarm about this issue back in July, when he found nearly 30,000 unauthenticated MongoDB instances. He decided to revisit the issue after a security researcher named Chris Vickery recently found information exposed in such databases that was associated with 25 million user accounts from various apps and services, including 13 million users of the controversial OS X optimization program MacKeeper.
Matherly’s new results show an increase of over 5,000 insecure MongoDB instances since July, a somewhat surprising result giving that newer versions of the database no longer have a default insecure configuration.
MongoDB versions 3.0 and newer only listen to “localhost,” so they don’t accept remote connections from the Internet. Yet, version 3.0.7 accounts for the largest number of exposed installations (3,010) found by Matherly and version 3.0.6 is also in the top five with 1,256 instances.
“The fact that MongoDB 3.0 is well-represented means that a lot of people are changing the default configuration of MongoDB to something less secure and aren’t enabling any firewall to protect their database,” Matherly said in a blog post Tuesday. “It could be that users are upgrading their instances but using their existing, insecure configuration files.”
The majority of the insecure MongoDB instances are hosted on cloud computing platforms run by DigitalOcean, Amazon.com and Alibaba Group.
If the information found by Vickery, such as names, email addresses, birth dates, postal addresses, private messages and insecure password hashes, are an indication of what’s in the other exposed databases, then the problem is very serious; and it’s not just limited to MongoDB.
“I can’t stress enough that this problem is not unique to MongoDB: Redis, CouchDB, Cassandra and Riak are equally impacted by these sorts of misconfigurations,” Matherly said.