Expr is an expression language and expression evaluation for Go. Prior to version 1.17.7, several builtin functions in Expr, including flatten, min, max, mean, and median, perform recursive traversal over user-provided data structures without enforcing a maximum recursion depth. If the evaluation environment contains deeply nested or cyclic data structures, these functions may recurse indefinitely until exceed the Go runtime stack limit. This results in a stack overflow panic, causing the host application to crash. While exploitability depends on whether an attacker can influence or inject cyclic or pathologically deep data into the
evaluation environment, this behavior represents a denial-of-service (DoS) risk and affects overall library robustness. Instead of returning a recoverable evaluation error, the process may terminate unexpectedly. In affected versions, evaluation of expressions that invoke certain builtin functions on untrusted or insufficiently validated data structures can lead to a process-level crash due to stack exhaustion. This issue is most relevant in scenarios where Expr is used to evaluate expressions against externally supplied or dynamically constructed environments; cyclic references (directly or indirectly) can be introduced into arrays, maps, or structs; and there are no application-level safeguards preventing deeply nested input data. In typical use cases with controlled, acyclic data, the issue may not manifest. However, when present, the resulting panic can be used to reliably crash the application, constituting a denial of service. The issue has been fixed in the v1.17.7 versions of Expr. The patch introduces a maximum recursion depth limit for affected builtin functions. When this limit is exceeded, evaluation aborts gracefully and returns a descriptive error instead of panicking. Additionally, the maximum depth can be customized by users via builtin.MaxDepth, allowing applications with legitimate deep structures to raise the limit in a controlled manner. Users are strongly encouraged to upgrade to the patched release, which includes both the recursion guard and comprehensive test coverage to prevent regressions. For users who cannot immediately upgrade, some mitigations are recommended. Ensure that evaluation environments cannot contain cyclic references, validate or sanitize externally supplied data structures before passing them to Expr, and/or wrap expression evaluation with panic recovery to prevent a full process crash (as a last-resort defensive measure). These workarounds reduce risk but do not fully eliminate the issue without the patch.
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.
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).