Redis HyperLogLog Data Structure SETRANGE Command Stack-Buffer Overflow Vulnerability [CVE-2019-10193]

CVE Number – CVE-2019-10193

A vulnerability in the Redis HyperLogLog data structure could allow an authenticated, remote attacker to execute arbitrary code or cause a denial of service (DoS) condition on a targeted system.

The vulnerability is due to a stack-buffer overflow condition that exists in the affected software. An attacker could exploit this vulnerability by executing the SETRANGE command to corrupt a HyperLogLog structure on a targeted system. A successful exploit could cause the affected software to perform controlled increments of up to 12 bytes past the end of a stack-allocated buffer, which the attacker could use to execute arbitrary code or cause a DoS condition. Redis has confirmed the vulnerability and released software updates.


  • To exploit this vulnerability, the attacker must have administrative-level access to the targeted system. This access requirement could reduce the likelihood of a successful exploit.


  • Administrators are advised to apply the appropriate updates.

    Administrators are advised to allow only trusted users to have network access.

    Administrators are advised to run both firewall and antivirus applications to minimize the potential of inbound and outbound threats.

    Administrators may consider using IP-based access control lists (ACLs) to allow only trusted systems to access the affected systems.

    Administrators can help protect affected systems from external attacks by using a solid firewall strategy.

    Administrators are advised to monitor affected systems.

Vendor Announcements

  • Redis has released an issue report at the following link: Issue #6215

Fixed Software

Duncan Newell

Duncan is a technology professional with over 20 years experience of working in various IT roles. He has a interest in cyber security, and has a wide range of other skills in radio, electronics and telecommunications.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

%d bloggers like this: