CVE-2025-69229 is a resource exhaustion vulnerability classified under CWE-770, affecting aiohttp, a popular asynchronous HTTP framework used in Python applications. Versions 3.13.2 and earlier improperly handle chunked HTTP messages, specifically when the request.read() method is used to process incoming data. When an attacker sends a large number of chunked messages, the server spends excessive blocking CPU time processing these chunks, approximately one second per request, which is significant in asynchronous environments designed to handle many concurrent connections efficiently. This blocking behavior can degrade server responsiveness, leading to denial-of-service conditions as the server becomes unable to process other incoming requests during the CPU blocking period. The vulnerability does not require any authentication or user interaction and can be triggered remotely by sending crafted HTTP requests. The CVSS 4.0 base score is 6.6, reflecting medium severity due to network attack vector, low attack complexity, no privileges or user interaction needed, but with a moderate impact on availability. The flaw was addressed in aiohttp version 3.13.3, which implements proper throttling or limits on resource allocation when handling chunked messages. No public exploits are known at this time, but the vulnerability poses a risk to any Python-based asynchronous web service using vulnerable aiohttp versions, especially those exposed to untrusted networks.

For European organizations, the primary impact of CVE-2025-69229 is the potential for denial-of-service attacks against web services built on aiohttp versions prior to 3.13.3. Such services may experience degraded performance or outages when targeted with crafted chunked HTTP requests, leading to service unavailability. This can disrupt business operations, customer access, and internal workflows reliant on these services. Organizations in sectors with high availability requirements, such as finance, healthcare, and critical infrastructure, may face operational and reputational damage. Additionally, the asynchronous nature of aiohttp means that a single malicious client could disproportionately consume server CPU resources, amplifying the risk of service degradation. While confidentiality and integrity impacts are not indicated, availability impact is moderate but significant for services with high traffic volumes or critical uptime demands. The lack of authentication or user interaction requirements increases the attack surface, making exposed aiohttp servers vulnerable to remote exploitation. European organizations using aiohttp in public-facing APIs, microservices, or internal asynchronous web applications should consider this a priority vulnerability to address.

1. Upgrade all aiohttp deployments to version 3.13.3 or later immediately to apply the official fix addressing this vulnerability. 2. Implement network-level rate limiting and request throttling on HTTP endpoints to limit the number of chunked requests from individual IP addresses, reducing the risk of resource exhaustion. 3. Deploy Web Application Firewalls (WAFs) with rules to detect and block abnormal chunked transfer encoding patterns or excessive chunked requests. 4. Monitor server CPU usage and request patterns for anomalies indicative of exploitation attempts, enabling rapid incident response. 5. For critical services, consider isolating aiohttp-based applications behind reverse proxies that can enforce additional request validation and rate limiting. 6. Conduct code reviews and testing to ensure that application logic using request.read() handles large or malformed chunked requests gracefully without excessive blocking. 7. Educate development teams on secure asynchronous programming practices and resource management to prevent similar issues. 8. Maintain an up-to-date inventory of Python dependencies and their versions to quickly identify vulnerable components.