CVE-2026-82404 (GCVE-0-2026-82404)
Vulnerability from cvelistv5 – Published: 2026-09-02 16:30 – Updated: 2026-09-02 18:59
VLAI
EPSS
VEX
Title
TOON: Prototype pollution when decoding untrusted TOON input
Summary
TOON is a compact, human-readable serialization of JSON data for LLM prompts. Prior to 2.3.1, decoding attacker-controlled TOON with a __proto__, constructor, or prototype key wrote through the object prototype chain instead of creating an own property, polluting Object.prototype for the runtime. In packages/toon/src/decode/expand.ts, the expandPaths: 'safe' path and insertPathSafe function made dotted keys such as a.__proto__.x the strongest vector, while plain nested objects, tabular rows, quoted keys, and streaming decode were also affected. The encoder also dropped own __proto__ properties and could invoke an inherited setter during normalization. Services that decode untrusted TOON could experience denial of service or, when a suitable downstream gadget is present, remote code execution. This issue is fixed in version 2.3.1.
Severity
8.3 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-02 18:58 UTC
CWE
- CWE-1321 - Improperly Controlled Modification of Object Prototype Attributes ('Prototype Pollution')
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/toon-format/toon/security/advi… | x_refsource_CONFIRM |
| https://github.com/toon-format/toon/pull/316 | x_refsource_MISC |
| https://github.com/toon-format/toon/commit/94a2b7… | x_refsource_MISC |
| https://github.com/toon-format/toon/releases/tag/v2.3.1 | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| toon-format | toon |
Affected:
< 2.3.1
|
guessed |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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