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Valibot: record() issue paths can make flatten() throw for inherited Object property names

Moderate severity GitHub Reviewed Published Jul 8, 2026 in open-circle/valibot • Updated Jul 24, 2026

Package

npm valibot (npm)

Affected versions

<= 1.4.1

Patched versions

1.4.2

Description

Summary

valibot 1.4.1 can throw a TypeError inside its flatten() helper when validation issues contain attacker-controlled object keys such as toString, valueOf, or hasOwnProperty.

The issue is reachable through normal record() validation. record() intentionally filters __proto__, prototype, and constructor, but it still accepts other own keys that collide with inherited Object.prototype properties. If the record key schema or value schema rejects such an entry, Valibot creates an issue path containing that key. Passing the resulting issues to Valibot's documented flatten() helper causes flatErrors.nested[dotPath] to resolve to the inherited method instead of an own error array, and the helper calls .push(...) on that function.

This is not a global prototype pollution issue. The impact is availability/error handling: applications that validate user-controlled objects with record() and flatten validation errors for API responses can crash the request path with a TypeError instead of returning structured validation errors.

Affected package

  • Ecosystem: npm
  • Package: valibot
  • Affected version verified: 1.4.1
  • Fixed version: none known
  • Repository: open-circle/valibot
  • Current main ref tested by source review: 9bb6617

Root cause

record() uses _isValidObjectKey() before validating record entries. The helper blocks the three classic prototype pollution keys:

key !== '__proto__' &&
key !== 'prototype' &&
key !== 'constructor'

It does not block other inherited Object.prototype names such as toString, valueOf, and hasOwnProperty. These remain valid own JSON object keys and can appear in issue paths when either the record key schema or value schema rejects the entry.

flatten() then creates nested error storage with an ordinary object:

flatErrors.nested = {};

For a dot path such as toString, this check reads the inherited Object.prototype.toString function:

if (flatErrors.nested![dotPath]) {
  flatErrors.nested![dotPath]!.push(issue.message);
}

Because the inherited function is truthy, flatten() calls .push(...) on a function and throws TypeError: flatErrors.nested[dotPath].push is not a function.

Impact

A remote attacker can trigger this if an application:

  1. validates attacker-controlled JSON objects with v.record(...);
  2. receives an invalid key or invalid value under a key such as toString;
  3. uses Valibot's flatten(result.issues) helper to prepare validation errors.

This is a common pattern in API/form validation: safeParse() collects issues and flatten() converts them into response-friendly error objects. Instead of a validation response, the request can hit an unexpected exception path.

The same root cause can also affect manually constructed issues or other schemas that place inherited Object property names into dot paths. I am reporting the record() path because it uses only public Valibot APIs and attacker-controlled JSON keys.

Local reproduction

Run in a disposable directory:

npm install valibot@1.4.1
node poc_record_flatten_inherited_key_dos.mjs

Minimal example:

import * as v from 'valibot';

const schema = v.record(v.string(), v.number());
const input = JSON.parse('{"toString":"not-a-number"}');

const result = v.safeParse(schema, input);
console.log(result.success); // false
console.log(result.issues[0].path.map((item) => item.key)); // ["toString"]

v.flatten(result.issues); // TypeError

Observed output from valibot@1.4.1:

{
  "name": "record value schema rejects attacker-controlled value",
  "key": "toString",
  "success": false,
  "issueCount": 1,
  "firstPath": ["toString"],
  "firstMessage": "Invalid type: Expected number but received \"not-a-number\"",
  "flattened": {
    "ok": false,
    "exception": "TypeError",
    "message": "flatErrors.nested[dotPath].push is not a function"
  }
}

The local PoC also reproduces the same exception for valueOf, hasOwnProperty, isPrototypeOf, propertyIsEnumerable, and toLocaleString. A control case with an ordinary key produces normal flattened errors.

Duplicate checks performed before submission

  • npm metadata confirmed current valibot release is 1.4.1 and maps to open-circle/valibot.
  • gh api repos/open-circle/valibot/private-vulnerability-reporting returned {"enabled":true}.
  • npm audit for a clean project containing only valibot@1.4.1 returned no vulnerabilities.
  • Repository advisories and the GitHub Advisory Database only returned the historical emoji ReDoS advisory fixed in 1.2.0.
  • OSV exact-version query for npm valibot 1.4.1 returned no vulnerabilities.
  • Public issue/PR searches for flatten toString, flatten hasOwnProperty, record toString, __proto__, constructor, and prototype pollution did not find a matching disclosure of this record() issue-path / flatten() exception.
  • Reviewed related public PRs: open-circle/valibot#67 added prototype pollution mitigation for record() by blacklisting __proto__, prototype, and constructor; it does not cover flatten() collisions with other inherited property names. open-circle/valibot#1429 is an open plain-object / record() type semantics PR and does not disclose this flatten() exception behavior.

Suggested remediation

Use null-prototype containers for flat error maps and/or perform own-property checks before appending:

  • Initialize flatErrors.nested as Object.create(null).
  • Check nested entries with Object.prototype.hasOwnProperty.call(flatErrors.nested, dotPath) rather than truthiness.
  • Consider filtering or escaping unsafe dot path segments in getDotPath() / flatten(), including inherited Object property names.
  • Add regression tests for flatten() with paths toString, valueOf, hasOwnProperty, __proto__, prototype, and constructor.
  • Consider using the same hardening for other accumulator objects that store attacker-controlled keys.

References

@fabian-hiller fabian-hiller published to open-circle/valibot Jul 8, 2026
Published to the GitHub Advisory Database Jul 24, 2026
Reviewed Jul 24, 2026
Last updated Jul 24, 2026

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability Low
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(42nd percentile)

Weaknesses

Improper Handling of Exceptional Conditions

The product does not handle or incorrectly handles an exceptional condition. Learn more on MITRE.

CVE ID

CVE-2026-59952

GHSA ID

GHSA-5qjj-4xww-7phc

Source code

Credits

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