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CVE-2026-50029 sunnyadn CVE debrief

A vulnerability in the js-toml TOML parser for JavaScript, prior to version 1.1.2, allows for silent overwriting of values when duplicate keys are present, leading to potential type confusion and unexpected behavior in host applications. The vulnerability arises from the parser's incorrect handling of duplicate keys using `if (object[key])` instead of `if (key in object)`. This can result in structural type confusion of attacker-named keys in the value returned by `load()`, potentially causing unexpected behavior in host applications that gate behavior on configuration flags or user data. Defenders should prioritize verifying and updating js-toml to version 1.1.2 or later, and take

Vendor
sunnyadn
Product
js-toml
CVSS
MEDIUM 5.3
CISA KEV
Not listed in stored evidence
Original CVE published
2026-08-14
Original CVE updated
2026-09-18
Advisory published
2026-08-14
Advisory updated
2026-09-18

Who should care

Defenders responsible for applications using js-toml, especially those handling configuration or user data, should assess exposure and prioritize verification and updates. Roles include developers, DevOps engineers, and security teams.

Why it matters

The vulnerability in js-toml allows for silent overwriting of values and potential type confusion, leading to unexpected behavior in host applications. Defenders should prioritize verifying and updating js-toml, especially in critical applications.

  • Potential unexpected behavior in applications due to type confusion
  • Silent overwriting of configuration values
  • Risk of incorrect gating of behavior based on configuration flags
  • Need for verification of affected applications and updates to js-toml

Technical summary

The js-toml parser for JavaScript, prior to version 1.1.2, incorrectly handles duplicate keys in TOML files. When a key already exists, the parser checks for its presence using `if (object[key])` instead of `if (key in object)`. This allows for silent overwriting of values by later sub-tables, dotted-key sub-tables, or array-of-tables with the same name. The result is structural type confusion of attacker-named keys in the value returned by `load()`. For example, a boolean-typed `false` or numeric `0` can become a truthy object. This issue can lead to unexpected behavior in host applications that gate behavior on configuration flags or user data.

Defensive priority

Defenders should prioritize verifying and updating js-toml to version 1.1.2 or later, especially in applications where configuration or user data is critical.

Recommended defensive actions

  • Verify and update js-toml to version 1.1.2 or later
  • Review applications using js-toml for potential exposure
  • Test configurations and user data handling in affected applications
  • Confirm whether affected product deployments exist in managed environments and assign an owner for follow-up
  • Review the supplied official advisory or CVE record to validate affected scope, severity, and vendor guidance
  • Plan vendor-supported updates or mitigations through normal change control where exposure is confirmed
  • Check relevant monitoring, detection, and logs for exposed assets that need extra review

Evidence notes

The CVE record and NVD entry provide details on the vulnerability, including its description, CVSS score, and affected versions. However, the scope of affected deployments and potential impact on specific applications require further verification.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-50029 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-50029

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-50029 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-50029

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.