Bref is an open-source project that helps users go serverless on Amazon Web Services with PHP. When Bref prior to version 2.1.17 is used with the Event-Driven Function runtime and the handler is a RequestHandlerInterface, then the Lambda event is converted to a PSR7 object. During the conversion process, if the request is a MultiPart, each part is parsed. In the parsing process, the Content-Type header of each part is read using the Riverline/multipart-parser library.
The library, in the StreamedPart::parseHeaderContent function, performs slow multi-byte string operations on the header value.
Precisely, the mb_convert_encoding function is used with the first ($string) and third ($from_encoding) parameters read from the header value.
An attacker could send specifically crafted requests which would force the server into performing long operations with a consequent long billed duration.
The attack has the following requirements and limitations: The Lambda should use the Event-Driven Function runtime and the RequestHandlerInterface handler and should implement at least an endpoint accepting POST requests; the attacker can send requests up to 6MB long (this is enough to cause a billed duration between 400ms and 500ms with the default 1024MB RAM Lambda image of Bref); and if the Lambda uses a PHP runtime <= php-82, the impact is higher as the billed duration in the default 1024MB RAM Lambda image of Bref could be brought to more than 900ms for each request. Notice that the vulnerability applies only to headers read from the request body as the request header has a limitation which allows a total maximum size of ~10KB.
Version 2.1.17 contains a fix for this issue.
The product does not properly control the allocation and maintenance of a limited resource, thereby enabling an actor to influence the amount of resources consumed, eventually leading to the exhaustion of available resources.
Limited resources include memory, file system storage, database connection pool entries, and CPU. If an attacker can trigger the allocation of these limited resources, but the number or size of the resources is not controlled, then the attacker could cause a denial of service that consumes all available resources. This would prevent valid users from accessing the product, and it could potentially have an impact on the surrounding environment. For example, a memory exhaustion attack against an application could slow down the application as well as its host operating system. There are at least three distinct scenarios which can commonly lead to resource exhaustion:
Resource exhaustion problems are often result due to an incorrect implementation of the following situations:
Mitigation of resource exhaustion attacks requires that the target system either:
The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question.
The second solution is simply difficult to effectively institute – and even when properly done, it does not provide a full solution. It simply makes the attack require more resources on the part of the attacker.