CVE-2026-93606 (GCVE-0-2026-93606)
Vulnerability from cvelistv5 – Published: 2026-09-18 13:20 – Updated: 2026-09-18 13:20
VLAI
EPSS
VEX
Title
vm2 before 3.12.1 Sandbox Escape via Promise Symbol.species
Summary
vm2 (npm) versions 3.12.0 and earlier contain a sandbox escape in `VM` and `NodeVM`. When an embedder exposes a host API that returns a host-realm Promise, the bridge's rejection sanitizer (hostPromiseSanitizeReject / makeSanitizedPromiseCallback / normalizeHostPromiseCallbacks in lib/bridge.js) only wraps `then`/`catch` rejection slots that hold a function, and the sandbox-side `Symbol.species`/`.then` neutralization is installed only on the sandbox intrinsic `Promise.prototype`, so it never applies to a host Promise. Code running inside the sandbox can overwrite `p.constructor[Symbol.species]` on the host Promise and then call `p.then()` with no `onRejected` handler; V8 substitutes its internal Thrower, which re-throws the raw host rejection value into a resolve/reject closure captured by the attacker. This delivers an unsanitized, fully functional bridge proxy of the host object to sandboxed code, bypassing handleException and hostPromiseSanitizeReject. If the rejection value is host-pivotable (for example a host `process` object), this results in arbitrary code execution on the host. Fixed in 3.12.1.
Severity
10 (Critical)
CWE
- CWE-693 - Protection Mechanism Failure
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/patriksimek/vm2/security/advis… | vendor-advisory |
| https://www.vulncheck.com/advisories/vm2-before-3… | third-party-advisory |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| patriksimek | vm2 |
Affected:
0 , < 3.12.1
(semver)
Unaffected: 3.12.1 (semver) cpe:2.3:a:vm2_project:vm2:*:*:*:*:*:node.js:*:* |
Date Public
2026-09-03 00:00
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}
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},
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"dateReserved": "2026-09-18T11:01:45.930Z",
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}
],
"id": "CVE-2026-93606",
"lastModified": "2026-09-18T14:19:12.617",
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}
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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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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