A flaw was found in Keycloak. A low-privilege user, with knowledge of user credentials and client ID, can bypass a security control intended to disable the implicit flow in OpenID Connect (OIDC) clients. By manipulating client data during a session restart, an attacker can obtain an access token that should not be available. This vulnerability can also lead to the exposure of these access tokens in server logs, proxy logs, and HTTP Referrer headers, resulting in sensitive information disclosure.
Weakness
The web application does not sufficiently verify inputs that are assumed to be immutable but are actually externally controllable, such as hidden form fields.
Affected Software
| Name | Vendor | Start Version | End Version |
|---|---|---|---|
| Build_of_keycloak | Redhat | 26.4 (including) | 26.4.12 (excluding) |
| Red Hat build of Keycloak 26.4 | RedHat | rhbk/keycloak-operator-bundle:26.4.12-1 | * |
| Red Hat build of Keycloak 26.4 | RedHat | rhbk/keycloak-rhel9:26.4-17 | * |
| Red Hat build of Keycloak 26.4 | RedHat | rhbk/keycloak-rhel9-operator:26.4-17 | * |
| Red Hat build of Keycloak 26.4.12 | RedHat | rhbk/keycloak-rhel9-operator | * |
Extended Description
If a web product does not properly protect assumed-immutable values from modification in hidden form fields, parameters, cookies, or URLs, this can lead to modification of critical data. Web applications often mistakenly make the assumption that data passed to the client in hidden fields or cookies is not susceptible to tampering. Improper validation of data that are user-controllable can lead to the application processing incorrect, and often malicious, input. For example, custom cookies commonly store session data or persistent data across sessions. This kind of session data is normally involved in security related decisions on the server side, such as user authentication and access control. Thus, the cookies might contain sensitive data such as user credentials and privileges. This is a dangerous practice, as it can often lead to improper reliance on the value of the client-provided cookie by the server side application.
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.
Related Attack Patterns
- https://cwe.mitre.org/data/definitions/146.html
- https://cwe.mitre.org/data/definitions/226.html
- https://cwe.mitre.org/data/definitions/31.html
- https://cwe.mitre.org/data/definitions/39.html