CVE-2025-13836 is a vulnerability identified in the Python Software Foundation's CPython implementation, specifically affecting versions 0 through 3.15.0a1. The issue occurs during the processing of HTTP responses when the client code does not specify the amount of data to read. In such cases, CPython defaults to using the Content-Length header to determine how much data to read into memory. A malicious HTTP server can exploit this behavior by sending a response with an artificially large Content-Length value, causing the client to allocate a correspondingly large buffer. This can lead to excessive memory consumption, resulting in an out-of-memory (OOM) condition or denial of service (DoS) on the client side. The vulnerability is classified under CWE-400 (Uncontrolled Resource Consumption). The CVSS v4.0 base score is 6.3, reflecting a medium severity level, with an attack vector of network (remote), low attack complexity, no privileges or user interaction required, and limited impact on confidentiality and integrity but significant impact on availability. No patches or known exploits are currently reported, but the vulnerability is publicly disclosed and should be addressed proactively. The flaw primarily affects applications and services that use CPython to handle HTTP responses, especially those that do not explicitly limit read sizes or validate Content-Length headers.

For European organizations, the primary impact of CVE-2025-13836 is the risk of denial of service through resource exhaustion. Applications, services, or automated systems that rely on CPython for HTTP communication could be forced into OOM conditions by malicious or compromised servers, leading to service outages or degraded performance. This can affect web clients, API consumers, or any Python-based networked applications. The impact on confidentiality and integrity is minimal, but availability disruptions can have cascading effects on business operations, especially in sectors dependent on continuous service availability such as finance, healthcare, and critical infrastructure. Organizations with large-scale Python deployments or those integrating third-party HTTP services are particularly at risk. Additionally, the vulnerability could be leveraged as part of a broader attack chain to disrupt operations or distract from other malicious activities.

To mitigate CVE-2025-13836, European organizations should first ensure they upgrade CPython to a version where this vulnerability is patched once available. In the interim, developers should explicitly specify read sizes when handling HTTP responses instead of relying on default Content-Length behavior. Implementing strict validation of Content-Length headers and enforcing maximum allowable sizes can prevent excessive memory allocation. Employing network-level protections such as rate limiting, web application firewalls (WAFs), and anomaly detection can help identify and block malicious servers attempting to exploit this flaw. Additionally, containerization and resource limits (e.g., cgroups or Kubernetes resource quotas) can contain the impact of potential OOM conditions. Monitoring application logs for unusual memory usage or crashes related to HTTP reads can provide early warning signs. Finally, educating developers about secure HTTP client practices and reviewing third-party libraries for similar vulnerabilities is recommended.