Keystone is a content management system for Node.js. Prior to version 6.5.0, {field}.isFilterable access control can be bypassed in update and delete mutations by adding additional unique filters. These filters can be used as an oracle to probe the existence or value of otherwise unreadable fields. Specifically, when a mutation includes a where clause with multiple unique filters (e.g. id and email), Keystone will attempt to match records even if filtering by the latter fields would normally be rejected by field.isFilterable or list.defaultIsFilterable. This can allow malicious actors to infer the presence of a particular field value when a filter is successful in returning a result. This affects any project relying on the default or dynamic isFilterable behavior (at the list or field level) to prevent external users from using the filtering of fields as a discovery mechanism. While this access control is respected during findMany operations, it was not completely enforced during update and delete mutations when accepting more than one unique where values in filters. This has no impact on projects using isFilterable: false or defaultIsFilterable: false for sensitive fields, or for those who have otherwise omitted filtering by these fields from their GraphQL schema. This issue has been patched in @keystone-6/core version 6.5.0. To mitigate this issue in older versions where patching is not a viable pathway, set isFilterable: false statically for relevant fields to prevent filtering by them earlier in the access control pipeline (that is, dont use functions); set {field}.graphql.omit.read: true for relevant fields, which implicitly removes filtering by these fields from the GraphQL schema; and/or deny update and delete operations for the relevant lists completely.
The product exposes sensitive information to an actor that is not explicitly authorized to have access to that information.
There are many different kinds of mistakes that introduce information exposures. The severity of the error can range widely, depending on the context in which the product operates, the type of sensitive information that is revealed, and the benefits it may provide to an attacker. Some kinds of sensitive information include:
Information might be sensitive to different parties, each of which may have their own expectations for whether the information should be protected. These parties include:
Information exposures can occur in different ways:
It is common practice to describe any loss of confidentiality as an “information exposure,” but this can lead to overuse of CWE-200 in CWE mapping. From the CWE perspective, loss of confidentiality is a technical impact that can arise from dozens of different weaknesses, such as insecure file permissions or out-of-bounds read. CWE-200 and its lower-level descendants are intended to cover the mistakes that occur in behaviors that explicitly manage, store, transfer, or cleanse sensitive information.