CVE-2026-16317 (GCVE-0-2026-16317)
Vulnerability from cvelistv5 – Published: 2026-07-21 20:12 – Updated: 2026-07-22 19:41
VLAI
EPSS
VEX
Title
Silent Drop of TLS 1.3 Encrypted Records in s2n-tls
Summary
Missing validation of the outer content_type byte on TLS 1.3 encrypted records in s2n-tls allows an active man-in-the-middle to silently discard individual application data records without either endpoint detecting the modification. RFC 8446 Section 5.2 requires that the outer content_type of all encrypted TLS 1.3 records must be application_data (0x17). The s2n-tls AEAD implementation hardcodes this value in the additional authenticated data rather than using the actual wire byte, so the outer content_type is not covered by the authentication tag.
This enables selective suppression of application data. In HTTP pipelining scenarios, dropping a TLS record containing an HTTP request can cause request/response desynchronization, where subsequent responses are delivered to the wrong requests. In write-heavy workloads, a dropped record containing a write request can result in undetectable data loss when the client interprets a subsequent success response as confirmation of the dropped write.
All TLS 1.3 connections are affected. Both TLS clients and servers are affected. TLS 1.2 and QUIC connections are not affected.
We recommend you upgrade s2n-tls to version v1.7.6
Severity
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-07-22 19:31 UTC
CWE
- CWE-354 - Improper validation of integrity check value
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/aws/s2n-tls/releases/tag/v1.7.6 | release-notespatch |
| https://aws.amazon.com/security/security-bulletin… | vendor-advisory |
| https://github.com/aws/s2n-tls/security/advisorie… | release-notes |
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"assignerOrgId": "ff89ba41-3aa1-4d27-914a-91399e9639e5",
"assignerShortName": "AMZN",
"cveId": "CVE-2026-16317",
"datePublished": "2026-07-21T20:12:48.047Z",
"dateReserved": "2026-07-20T16:40:27.027Z",
"dateUpdated": "2026-07-22T19:41:19.156Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2"
}
}
}
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Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
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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.