CVE Vulnerabilities

CVE-2025-30152

External Control of Assumed-Immutable Web Parameter

Published: Mar 19, 2025 | Modified: Mar 19, 2025
CVSS 3.x
N/A
Source:
NVD
CVSS 2.x
RedHat/V2
RedHat/V3
Ubuntu

The Syliud PayPal Plugin is the Sylius Core Team’s plugin for the PayPal Commerce Platform. Prior to 1.6.2, 1.7.2, and 2.0.2, a discovered vulnerability allows users to modify their shopping cart after completing the PayPal Checkout process and payment authorization. If a user initiates a PayPal transaction from a product page or the cart page and then returns to the order summary page, they can still manipulate the cart contents before finalizing the order. As a result, the order amount in Sylius may be higher than the amount actually captured by PayPal, leading to a scenario where merchants deliver products or services without full payment. The issue is fixed in versions: 1.6.2, 1.7.2, 2.0.2 and above.

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.

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.

References