Zod schema-validation library contains an uncontrolled resource consumption vulnerability that allows attackers to exhaust memory by submitting a large array, set or map to an application that uses a container schema without an explicit size constraint. The handleArrayResult parse logic in $ZodArray (and the equivalent set and map paths) accumulates every validation issue for each failing element with no cap or early termination, causing the process to allocate one issue object per element and crash under out-of-memory conditions. This is reachable in the default configuration whenever a container schema such as z.array() is declared without a size bound. The upstream change in commit e06a510 (pull request 6652, first released in 4.6.6) only moves the .max(), .length() and .size() size checks to run before element parsing, so it rejects oversized input for schemas that declare an explicit upper bound; per the maintainer, unbounded containers are unchanged. No released version remediates the unbounded (default) case described here, and an opt-in setting to cap total accumulated errors was proposed but not merged.
Weakness
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.
Potential Mitigations
Assume all input is malicious. Use an “accept known good” input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, “boat” may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as “red” or “blue.”
Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code’s environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
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 can be difficult to effectively institute – and even when properly done, it does not provide a full solution. It simply requires more resources on the part of the attacker.
If the program must fail, ensure that it fails gracefully (fails closed). There may be a temptation to simply let the program fail poorly in cases such as low memory conditions, but an attacker may be able to assert control before the software has fully exited. Alternately, an uncontrolled failure could cause cascading problems with other downstream components; for example, the program could send a signal to a downstream process so the process immediately knows that a problem has occurred and has a better chance of recovery.
Ensure that all failures in resource allocation place the system into a safe posture.
Use quotas or other resource-limiting settings provided by the operating system or environment. For example, when managing system resources in POSIX, setrlimit() can be used to set limits for certain types of resources, and getrlimit() can determine how many resources are available. However, these functions are not available on all operating systems.
When the current levels get close to the maximum that is defined for the application (see CWE-770), then limit the allocation of further resources to privileged users; alternately, begin releasing resources for less-privileged users. While this mitigation may protect the system from attack, it will not necessarily stop attackers from adversely impacting other users.
Ensure that the application performs the appropriate error checks and error handling in case resources become unavailable (CWE-703).
Related Attack Patterns
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