expr-lang expr up to 1.16.x on Go allocation of resources

Summaryinfo

A vulnerability classified as problematic has been found in expr-lang expr up to 1.16.x on Go. This vulnerability affects unknown code. Performing a manipulation results in allocation of resources. This vulnerability is reported as CVE-2025-29786. The attack is possible to be carried out remotely. No exploit exists. It is recommended to upgrade the affected component.

Detailsinfo

A vulnerability classified as problematic has been found in expr-lang expr up to 1.16.x on Go. This affects some unknown processing. The manipulation with an unknown input leads to a allocation of resources vulnerability. CWE is classifying the issue as CWE-770. The product allocates a reusable resource or group of resources on behalf of an actor without imposing any restrictions on the size or number of resources that can be allocated, in violation of the intended security policy for that actor. This is going to have an impact on availability. The summary by CVE is:

Expr is an expression language and expression evaluation for Go. Prior to version 1.17.0, if the Expr expression parser is given an unbounded input string, it will attempt to compile the entire string and generate an Abstract Syntax Tree (AST) node for each part of the expression. In scenarios where input size isn’t limited, a malicious or inadvertent extremely large expression can consume excessive memory as the parser builds a huge AST. This can ultimately lead to*excessive memory usage and an Out-Of-Memory (OOM) crash of the process. This issue is relatively uncommon and will only manifest when there are no restrictions on the input size, i.e. the expression length is allowed to grow arbitrarily large. In typical use cases where inputs are bounded or validated, this problem would not occur. The problem has been patched in the latest versions of the Expr library. The fix introduces compile-time limits on the number of AST nodes and memory usage during parsing, preventing any single expression from exhausting resources. Users should upgrade to Expr version 1.17.0 or later, as this release includes the new node budget and memory limit safeguards. Upgrading to v1.17.0 ensures that extremely deep or large expressions are detected and safely aborted during compilation, avoiding the OOM condition. For users who cannot immediately upgrade, the recommended workaround is to impose an input size restriction before parsing. In practice, this means validating or limiting the length of expression strings that your application will accept. For example, set a maximum allowable number of characters (or nodes) for any expression and reject or truncate inputs that exceed this limit. By ensuring no unbounded-length expression is ever fed into the parser, one can prevent the parser from constructing a pathologically large AST and avoid potential memory exhaustion. In short, pre-validate and cap input size as a safeguard in the absence of the patch.

It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2025-29786 since 03/11/2025. The exploitability is told to be easy. It is possible to initiate the attack remotely. No form of authentication is needed for exploitation. The technical details are unknown and an exploit is not publicly available. The attack technique deployed by this issue is T1499 according to MITRE ATT&CK.

The vulnerability scanner Nessus provides a plugin with the ID 233522 (RHEL 9 : opentelemetry-collector (RHSA-2025:3335)), which helps to determine the existence of the flaw in a target environment.

Upgrading to version 1.17.0 eliminates this vulnerability.

The vulnerability is also documented in the vulnerability database at Tenable (233522). Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Vendor

• expr-lang

Name

• expr

Version

• 1.0
• 1.1
• 1.2
• 1.3
• 1.4
• 1.5
• 1.6
• 1.7
• 1.8
• 1.9
• 1.10
• 1.11
• 1.12
• 1.13
• 1.14
• 1.15
• 1.16

Website

• Product: https://github.com/expr-lang/expr/

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Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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