Microsoft has warned users about a new password-spraying attack by a hacking group Storm-1977 that targets cloud users. The Microsoft Threat Intelligence team reported a new warning after discovering threat actors are abusing unsecured workload identities to access restricted resources.
According to Microsoft, “Container technology has become essential for modern application development and deployment. It's a critical component for over 90% of cloud-native organizations, facilitating swift, reliable, and flexible processes that drive digital transformation.”
Research says 51% of such workload identities have been inactive for one year, which is why attackers are exploiting this attack surface. The report highlights the “adoption of containers-as-a-service among organizations rises.” According to Microsoft, it continues to look out for unique security dangers that affect “containerized environments.”
The password-spraying attack targeted a command line interface tool “AzureChecker” to download AES-encrypted data which revealed the list of password-spray targets after it was decoded. To make things worse, the “threat actor then used the information from both files and posted the credentials to the target tenants for validation.”
The attack allowed the Storm-1977 hackers to leverage a guest account to make a compromised subscription resource group and over 200 containers that were used for crypto mining.
The solution to the problem of password spraying attacks is eliminating passwords. It can be done by moving towards passkeys, a lot of people are already doing that.
Modify the Kubernetes role-based access controls for every user and service account to only retain permissions that are required.
According to Microsoft, “Recent updates to Microsoft Defender for Cloud enhance its container security capabilities from development to runtime. Defender for Cloud now offers enhanced discovery, providing agentless visibility into Kubernetes environments, tracking containers, pods, and applications.” These updates upgrade security via continuous granular scanning.