CVE-2023-51663 in hail
Summary
by MITRE • 12/29/2023
Hail is an open-source, general-purpose, Python-based data analysis tool with additional data types and methods for working with genomic data. Hail relies on OpenID Connect (OIDC) email addresses from ID tokens to verify the validity of a user's domain, but because users have the ability to change their email address, they could create accounts and use resources in clusters that they should not have access to. For example, a user could create a Microsoft or Google account and then change their email to `[email protected]`. This account can then be used to create a Hail Batch account in Hail Batch clusters whose organization domain is `example.org`. The attacker is not able to access private data or impersonate another user, but they would have the ability to run jobs if Hail Batch billing projects are enabled and create Azure Tenants if they have Azure Active Directory Administrator access.
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Analysis
by VulDB Data Team • 01/21/2024
The vulnerability identified as CVE-2023-51663 resides within the Hail data analysis platform, a Python-based tool designed for genomic data processing that leverages OpenID Connect authentication mechanisms. This security flaw stems from the platform's reliance on email addresses contained within ID tokens for domain validation purposes during user authentication. The core technical issue emerges from the fundamental assumption that email addresses in OIDC tokens remain immutable and trustworthy for access control decisions. When users possess the capability to modify their email addresses within their identity provider accounts, attackers can exploit this functionality to bypass domain-based access controls that are critical for maintaining organizational security boundaries. The vulnerability specifically affects Hail Batch clusters that implement domain-based restrictions through billing projects, creating a pathway for unauthorized resource consumption.
The operational impact of this vulnerability extends beyond simple privilege escalation, creating a significant security risk for organizations utilizing cloud-based genomic data processing platforms. Attackers can leverage this flaw by creating legitimate user accounts with email addresses from target organizations, then modifying these accounts to match the desired domain. This allows them to access Hail Batch clusters that enforce domain restrictions, enabling them to execute computational jobs using the organization's billing resources. While the vulnerability does not permit direct access to private data or user impersonation, it provides attackers with the ability to consume computational resources and potentially create Azure Tenants when they possess Azure Active Directory Administrator privileges. This resource consumption capability represents a substantial financial risk, as organizations may face unexpected charges for computational workloads initiated by unauthorized users. The vulnerability particularly affects cloud environments where billing projects are enabled, making it a critical concern for organizations managing sensitive genomic data in shared or multi-tenant cloud infrastructures.
Security mitigations for this vulnerability should focus on strengthening the authentication and authorization mechanisms within the Hail platform. Organizations should implement additional verification steps beyond simple email domain matching, such as requiring multi-factor authentication or implementing more robust identity verification processes that cannot be easily circumvented through email address modification. The platform should enforce stricter validation of identity provider claims, potentially requiring additional attributes or implementing cryptographic verification of user identity beyond what is provided in standard OIDC tokens. From a compliance perspective, this vulnerability aligns with CWE-287 which addresses authentication failures and CWE-306 which covers missing authentication. The attack pattern resembles techniques documented in MITRE ATT&CK framework under T1078 legitimate credentials and T1566 credential stuffing, where attackers exploit weaknesses in authentication mechanisms to gain unauthorized access to resources. Organizations should also consider implementing monitoring and alerting for unusual job execution patterns that might indicate unauthorized access to billing-enabled clusters, as well as regularly auditing access controls and resource usage to detect potential exploitation of this vulnerability.