CVE-2026-66732 (GCVE-0-2026-66732)
Vulnerability from cvelistv5 – Published: 2026-08-06 12:53 – Updated: 2026-08-06 18:44 X_Open Source
VLAI
EPSS
VEX
Title
Sonic 3 A.I.R. Missing Source Address Validation in ConnectionManager
Summary
Sonic 3 A.I.R. before commit 2492d18 contains a missing source address validation vulnerability in ConnectionManager where established connections are resolved by a two-byte local connection handle alone without verifying that the datagram source address matches the registered remote address for the connection. An on-path attacker who can observe cleartext UDP traffic can inject arbitrary packets into any established session by forging the two-byte connection identifier, enabling session termination via TerminateConnectionPacket, arbitrary channel message forgery, and forged request responses without requiring IP address spoofing.
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-06 18:32 UTC
CWE
- CWE-346 - Origin Validation Error
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/Eukaryot/sonic3air/commit/2492… | patch |
| https://www.vulncheck.com/advisories/sonic-3-a-i-… | third-party-advisory |
Impacted products
Date Public
2026-07-29 00:00
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Sightings
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|---|
Nomenclature
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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
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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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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.