Vulnerabilities > CVE-2023-50730 - Allocation of Resources Without Limits or Throttling vulnerability in Typelevel Grackle

047910
CVSS 7.5 - HIGH
Attack vector
NETWORK
Attack complexity
LOW
Privileges required
NONE
Confidentiality impact
NONE
Integrity impact
NONE
Availability impact
HIGH
network
low complexity
typelevel
CWE-770

Summary

Grackle is a GraphQL server written in functional Scala, built on the Typelevel stack. The GraphQL specification requires that GraphQL fragments must not form cycles, either directly or indirectly. Prior to Grackle version 0.18.0, that requirement wasn't checked, and queries with cyclic fragments would have been accepted for type checking and compilation. The attempted compilation of such fragments would result in a JVM `StackOverflowError` being thrown. Some knowledge of an applications GraphQL schema would be required to construct such a query, however no knowledge of any application-specific performance or other behavioural characteristics would be needed. Grackle uses the cats-parse library for parsing GraphQL queries. Prior to version 0.18.0, Grackle made use of the cats-parse `recursive` operator. However, `recursive` is not currently stack safe. `recursive` was used in three places in the parser: nested selection sets, nested input values (lists and objects), and nested list type declarations. Consequently, queries with deeply nested selection sets, input values or list types could be constructed which exploited this, causing a JVM `StackOverflowException` to be thrown during parsing. Because this happens very early in query processing, no specific knowledge of an applications GraphQL schema would be required to construct such a query. The possibility of small queries resulting in stack overflow is a potential denial of service vulnerability. This potentially affects all applications using Grackle which have untrusted users. Both stack overflow issues have been resolved in the v0.18.0 release of Grackle. As a workaround, users could interpose a sanitizing layer in between untrusted input and Grackle query processing.

Vulnerable Configurations

Part Description Count
Application
Typelevel
97

Common Attack Pattern Enumeration and Classification (CAPEC)

  • Locate and Exploit Test APIs
    An attacker exploits a sample, demonstration, or test API that is insecure by default and should not be resident on production systems. Some applications include APIs that are intended to allow an administrator to test and refine their domain. These APIs should usually be disabled once a system enters a production environment. Testing APIs may expose a great deal of diagnostic information intended to aid an administrator, but which can also be used by an attacker to further refine their attack. Moreover, testing APIs may not have adequate security controls or may not have undergone rigorous testing since they were not intended for use in production environments. As such, they may have many flaws and vulnerabilities that would allow an attacker to severely disrupt a target.
  • Flooding
    An attacker consumes the resources of a target by rapidly engaging in a large number of interactions with the target. This type of attack generally exposes a weakness in rate limiting or flow control in management of interactions. Since each request consumes some of the target's resources, if a sufficiently large number of requests must be processed at the same time then the target's resources can be exhausted. The degree to which the attack is successful depends upon the volume of requests in relation to the amount of the resource the target has access to, and other mitigating circumstances such as the target's ability to shift load or acquired additional resources to deal with the depletion. The more protected the resource and the greater the quantity of it that must be consumed, the more resources the attacker may need to have at their disposal. A typical TCP/IP flooding attack is a Distributed Denial-of-Service attack where many machines simultaneously make a large number of requests to a target. Against a target with strong defenses and a large pool of resources, many tens of thousands of attacking machines may be required. When successful this attack prevents legitimate users from accessing the service and can cause the target to crash. This attack differs from resource depletion through leaks or allocations in that the latter attacks do not rely on the volume of requests made to the target but instead focus on manipulation of the target's operations. The key factor in a flooding attack is the number of requests the attacker can make in a given period of time. The greater this number, the more likely an attack is to succeed against a given target.
  • Excessive Allocation
    An attacker causes the target to allocate excessive resources to servicing the attackers' request, thereby reducing the resources available for legitimate services and degrading or denying services. Usually, this attack focuses on memory allocation, but any finite resource on the target could be the attacked, including bandwidth, processing cycles, or other resources. This attack does not attempt to force this allocation through a large number of requests (that would be Resource Depletion through Flooding) but instead uses one or a small number of requests that are carefully formatted to force the target to allocate excessive resources to service this request(s). Often this attack takes advantage of a bug in the target to cause the target to allocate resources vastly beyond what would be needed for a normal request. For example, using an Integer Attack, the attacker could cause a variable that controls allocation for a request to hold an excessively large value. Excessive allocation of resources can render a service degraded or unavailable to legitimate users and can even lead to crashing of the target.
  • XML Ping of the Death
    An attacker initiates a resource depletion attack where a large number of small XML messages are delivered at a sufficiently rapid rate to cause a denial of service or crash of the target. Transactions such as repetitive SOAP transactions can deplete resources faster than a simple flooding attack because of the additional resources used by the SOAP protocol and the resources necessary to process SOAP messages. The transactions used are immaterial as long as they cause resource utilization on the target. In other words, this is a normal flooding attack augmented by using messages that will require extra processing on the target.
  • XML Entity Expansion
    An attacker submits an XML document to a target application where the XML document uses nested entity expansion to produce an excessively large output XML. XML allows the definition of macro-like structures that can be used to simplify the creation of complex structures. However, this capability can be abused to create excessive demands on a processor's CPU and memory. A small number of nested expansions can result in an exponential growth in demands on memory.