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 users 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 test@example.org. 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.
Weakness
The product performs authentication based on the name of a resource being accessed, or the name of the actor performing the access, but it does not properly check all possible names for that resource or actor.
Affected Software
| Name |
Vendor |
Start Version |
End Version |
| Hail |
Hail |
* |
0.2.127 (excluding) |
Potential Mitigations
- Assume all input is malicious. Use an “accept known good” input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
- When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, “boat” may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as “red” or “blue.”
- Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code’s environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
References