CVE-2026-63126 (GCVE-0-2026-63126)
Vulnerability from cvelistv5 – Published: 2026-09-16 18:13 – Updated: 2026-09-16 19:41
VLAI
EPSS
VEX
Title
Wire: Unauthenticated decoder crash via 32-bit length integer overflow in ByteArrayProtoReader32 (incomplete fix of CVE-2026-45799)
Summary
Wire provides gRPC and protocol buffers for Android, Kotlin, Swift, and Java. Prior to 6.4.5 and 7.0.0-alpha04, Wire protobuf readers do not consistently validate attacker-controlled lengths against the current logical message boundary before advancing cursors, pointers, limits, slices, or allocations. In Kotlin, ProtoAdapter.decode(ByteArray) and ProtoAdapter.decode(ByteString) use ByteArrayProtoReader32.internalNextLengthDelimited(), where a positive oversized length can wrap pos + length to a negative limit and escape the existing negative-length check. Related ProtoReader, ReadBuffer.readVarint(), ReadBuffer.verifyAdditional(count:), packed-repeated, nested-message, and ProtoDecoder.decodeSizeDelimited(_:from:) paths can cross logical boundaries, perform pointer arithmetic, reserve capacity, or convert an unrepresentable size before proving the requested bytes exist. An attacker who supplies malformed protobuf bytes can cause unchecked exceptions, traps, out-of-bounds behavior, or excessive allocation, resulting in denial of service without known confidentiality, integrity, or code-execution impact. This issue is fixed in versions 6.4.5 and 7.0.0-alpha04.
Severity
7.5 (High)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-16 19:41 UTC
CWE
- CWE-190 - Integer Overflow or Wraparound
Assigner
References
6 references
| URL | Tags |
|---|---|
| https://github.com/square/wire/security/advisorie… | x_refsource_CONFIRM |
| https://github.com/square/wire/pull/3635 | x_refsource_MISC |
| https://github.com/square/wire/commit/082d5d83cec… | x_refsource_MISC |
| https://github.com/square/wire/commit/25ebcabb9ab… | x_refsource_MISC |
| https://github.com/square/wire/releases/tag/6.4.5 | x_refsource_MISC |
| https://github.com/square/wire/releases/tag/7.0.0… | x_refsource_MISC |
Impacted products
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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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