FKIE_CVE-2026-103501
Vulnerability from fkie_nvd - Published: 2026-10-10 11:17 - Updated: 2026-10-10 13:17
Severity
Summary
Heap buffer overflow in the HLL sketch deserialization of Apache DataSketches C++ (repo: datasketches-cpp).
When deserializing a sketch in LIST mode, from either a byte buffer or a stream, the coupon count was read from the input and used as the number of entries to copy into a fixed buffer of 8 entries, without checking it against the buffer's capacity. A crafted sketch could cause a write of up to 988 bytes past the end of this internal heap buffer. This can corrupt heap memory, causing a crash and potentially enabling further exploitation.
This issue affects Apache DataSketches C++: from 1.0.0-incubating before 5.3.0. Only applications that deserialize HLL sketches from untrusted sources are affected.
Users are recommended to upgrade to version 5.3.0, which fixes this issue.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"collectionURL": "https://github.com",
"defaultStatus": "unaffected",
"packageName": "apache/datasketches-cpp",
"packageURL": "pkg:github/apache/datasketches-cpp",
"product": "Apache DataSketches",
"vendor": "Apache Software Foundation",
"versions": [
{
"lessThanOrEqual": "5.2.0",
"status": "affected",
"version": "1.0.0-incubating",
"versionType": "semver"
}
]
}
],
"source": "security@apache.org"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Heap buffer overflow in the HLL sketch deserialization of Apache DataSketches C++ (repo: datasketches-cpp).\n\nWhen deserializing a sketch in LIST mode, from either a byte buffer or a stream, the coupon count was read from the input and used as the number of entries to copy into a fixed buffer of 8 entries, without checking it against the buffer\u0027s capacity. A crafted sketch could cause a write of up to 988 bytes past the end of this internal heap buffer. This can corrupt heap memory, causing a crash and potentially enabling further exploitation.\n\nThis issue affects Apache DataSketches C++: from 1.0.0-incubating before 5.3.0. Only applications that deserialize HLL sketches from untrusted sources are affected.\n\nUsers are recommended to upgrade to version 5.3.0, which fixes this issue."
}
],
"id": "CVE-2026-103501",
"lastModified": "2026-10-10T13:17:30.870",
"metrics": {},
"published": "2026-10-10T11:17:34.853",
"references": [
{
"source": "security@apache.org",
"url": "https://github.com/apache/datasketches-cpp/releases/tag/5.3.0"
},
{
"source": "security@apache.org",
"url": "https://lists.apache.org/thread/n2oc2j841dzsv4239jjp08of66bo79c5"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"url": "http://www.openwall.com/lists/oss-security/2026/10/10/2"
}
],
"sourceIdentifier": "security@apache.org",
"vulnStatus": "Received",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-122"
},
{
"lang": "en",
"value": "CWE-1284"
}
],
"source": "security@apache.org",
"type": "Secondary"
}
]
}
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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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