A high-severity vulnerability, CVE-2026-25243, has been patched in Redis, a widely used open-source, in-memory data store. The flaw is a heap-based buffer overflow (CWE-122) in the RESTORE command. It stems from improper validation of user-supplied serialized data. An authenticated attacker who has permissions to execute the RESTORE command can exploit this vulnerability by sending a specially crafted payload. This can cause the Redis server to crash (denial-of-service) or, in a more severe scenario, could be leveraged for remote code execution (RCE). The vulnerability has a CVSS 4.0 score of 7.7 (High) and affects all Redis versions up to 8.6.3. Administrators are urged to upgrade to the patched version or apply the recommended ACL-based workaround.
The vulnerability exists specifically within the logic of the Redis RESTORE command. This command is used to create a key in the database using a serialized value, typically one obtained via the DUMP command. The flaw lies in the fact that the RESTORE command does not sufficiently validate the structure of the serialized data it receives.
An authenticated attacker can craft a malformed serialized value and pass it to the RESTORE command. When the Redis server attempts to process this invalid data, it leads to a heap-based buffer overflow. This memory corruption can cause the redis-server process to terminate unexpectedly, resulting in a denial-of-service.
More critically, as with many buffer overflow vulnerabilities, there is a potential for attackers to gain control over the instruction pointer and achieve remote code execution. This would allow them to run arbitrary commands on the server with the permissions of the redis-server process.
redis-server)There is no public information about active exploitation of this vulnerability in the wild. However, the public disclosure of the flaw and its details increases the risk of exploitation by threat actors. The attack requires an attacker to be authenticated and have the necessary permissions to execute the RESTORE command. This makes it less likely to be exploited by unauthenticated external attackers, but it poses a significant risk in scenarios where an attacker has gained a low-privileged foothold within the network or if a Redis instance is improperly configured to allow broad command access.
The following patterns may help identify vulnerable systems or exploitation attempts:
Redis log fileRESTORE command.RESTORERESTORE commands, especially from untrusted clients.redis-serverredis-server instances. Any version prior to 8.6.3 is vulnerable.redis-server --version
redis-cli INFO server | grep redis_version
redis-server process following RESTORE command activity could indicate an exploitation attempt.RESTORE command. Scrutinize any user with this permission who is not a trusted administrator.Upgrade Redis: The primary solution is to upgrade all Redis instances to version 8.6.3 or newer. This version contains the necessary patch to correctly validate data passed to the RESTORE command.
Workaround (ACL Restriction): If an immediate upgrade is not feasible, the risk can be mitigated by restricting access to the vulnerable command. Use Redis ACLs to prevent untrusted or application-level users from executing the RESTORE command. For example, you can configure a user to have access to most commands but explicitly deny RESTORE:
ACL SETUSER myappuser on >mypassword allkeys +@all -RESTORE
This ensures that only highly privileged administrative users can call the vulnerable function, significantly reducing the attack surface.
The most effective mitigation is to upgrade all Redis instances to version 8.6.3 or later.
Mapped D3FEND Techniques:
Use Redis ACLs to restrict permissions, specifically denying access to the `RESTORE` command for all but the most trusted administrative users.
Mapped D3FEND Techniques:
Follow the principle of least privilege. Application service accounts connecting to Redis should only have access to the commands and keys they absolutely need.
Mapped D3FEND Techniques:
Redis discloses CVE-2026-25243 and releases patched version 8.6.3.

Cybersecurity professional with over 10 years of specialized experience in security operations, threat intelligence, incident response, and security automation. Expertise spans SOAR/XSOAR orchestration, threat intelligence platforms, SIEM/UEBA analytics, and building cyber fusion centers. Background includes technical enablement, solution architecture for enterprise and government clients, and implementing security automation workflows across IR, TIP, and SOC use cases.
Help others stay informed about cybersecurity threats
Every tactic, technique, and sub-technique used in this threat has been identified and mapped to the MITRE ATT&CK framework for consistent, actionable threat language.
Observables and indicators of compromise (IOCs) have been extracted and cataloged. Risk has been assessed and correlated with known threat actors and historical campaigns.
Detection rules, incident response steps, and D3FEND-aligned mitigation strategies are included so your team can act on this intelligence immediately.
Structured threat data is packaged as a STIX 2.1 bundle and can be visualized as an interactive graph — relationships between actors, malware, techniques, and indicators.
Sigma detection rules are derived from the threat techniques in this article and can be converted for deployment across any major SIEM or EDR platform.