CVE-2023-1255 (GCVE-0-2023-1255)
Vulnerability from cvelistv5 – Published: 2023-04-20 16:14 – Updated: 2025-02-13 16:39
VLAI
EPSS
VEX
Title
Input buffer over-read in AES-XTS implementation on 64 bit ARM
Summary
Issue summary: The AES-XTS cipher decryption implementation for 64 bit ARM
platform contains a bug that could cause it to read past the input buffer,
leading to a crash.
Impact summary: Applications that use the AES-XTS algorithm on the 64 bit ARM
platform can crash in rare circumstances. The AES-XTS algorithm is usually
used for disk encryption.
The AES-XTS cipher decryption implementation for 64 bit ARM platform will read
past the end of the ciphertext buffer if the ciphertext size is 4 mod 5 in 16
byte blocks, e.g. 144 bytes or 1024 bytes. If the memory after the ciphertext
buffer is unmapped, this will trigger a crash which results in a denial of
service.
If an attacker can control the size and location of the ciphertext buffer
being decrypted by an application using AES-XTS on 64 bit ARM, the
application is affected. This is fairly unlikely making this issue
a Low severity one.
Severity
5.9 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-02-04 21:14 UTC
CWE
- buffer over-read
- CWE-125 - Out-of-bounds Read
Assigner
References
4 references
Impacted products
Date Public
2023-03-21 00:00
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"assignerShortName": "openssl",
"cveId": "CVE-2023-1255",
"datePublished": "2023-04-20T16:14:54.707Z",
"dateReserved": "2023-03-07T14:56:07.099Z",
"dateUpdated": "2025-02-13T16:39:19.031Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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.