CVE-2025-68480 is an asymmetric resource consumption vulnerability classified under CWE-405 found in the marshmallow Python library, which is widely used for serializing and deserializing complex data structures. The flaw exists in the Schema.load(data, many=True) function in versions from 3.0.0rc1 up to but not including 3.26.2, and from 4.0.0 up to but not including 4.1.2. When processing input data, this function can be forced to consume excessive CPU resources disproportionate to the input size, effectively enabling a denial of service (DoS) attack. The vulnerability is exploitable remotely without any authentication or user interaction, as it can be triggered by sending crafted input data to an application using the vulnerable marshmallow versions. The root cause is an inefficient handling of data structures during deserialization when the 'many=True' parameter is used, which leads to amplification of resource consumption. Although the vulnerability does not compromise data confidentiality or integrity, it can severely impact application availability by exhausting CPU resources, potentially causing service slowdowns or crashes. The issue has been addressed in marshmallow versions 3.26.2 and 4.1.2, where the deserialization process has been optimized to prevent disproportionate CPU usage. No known exploits have been reported in the wild as of the publication date, but the medium CVSS score of 5.3 reflects the moderate risk posed by this vulnerability due to its ease of exploitation and potential impact on availability.

For European organizations, the primary impact of CVE-2025-68480 is the risk of denial of service attacks against applications that utilize vulnerable versions of the marshmallow library for data deserialization. This can lead to application downtime, degraded user experience, and potential disruption of critical services, especially for web-facing applications or APIs that accept untrusted input. Organizations in sectors such as finance, healthcare, government, and technology, which often rely on Python-based services, may face operational risks and reputational damage if exploited. Additionally, the increased CPU consumption could lead to higher infrastructure costs and complicate incident response efforts. While the vulnerability does not expose sensitive data or allow unauthorized data modification, the availability impact alone can have significant business consequences. European companies with compliance obligations around service availability and incident management (e.g., under GDPR or sector-specific regulations) must prioritize addressing this vulnerability to avoid regulatory scrutiny and potential penalties.

The most effective mitigation is to upgrade all instances of the marshmallow library to version 3.26.2 or 4.1.2 and later, where the vulnerability is patched. Organizations should conduct an inventory of Python applications and dependencies to identify vulnerable versions. In addition to upgrading, developers should implement strict input validation to reject malformed or unexpected data before deserialization. Rate limiting and throttling mechanisms at the application or API gateway level can reduce the risk of resource exhaustion from repeated malicious requests. Monitoring CPU usage and application performance metrics can help detect anomalous behavior indicative of exploitation attempts. For critical systems, consider isolating services using marshmallow in containerized or sandboxed environments to limit the impact of potential DoS attacks. Finally, maintain an up-to-date patch management process and subscribe to vulnerability advisories related to Python libraries to respond promptly to future issues.