GSD-2020-7226
Vulnerability from gsd - Updated: 2023-12-13 01:21Details
CiphertextHeader.java in Cryptacular 1.2.3, as used in Apereo CAS and other products, allows attackers to trigger excessive memory allocation during a decode operation, because the nonce array length associated with "new byte" may depend on untrusted input within the header of encoded data.
Aliases
Aliases
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"description": "CiphertextHeader.java in Cryptacular 1.2.3, as used in Apereo CAS and other products, allows attackers to trigger excessive memory allocation during a decode operation, because the nonce array length associated with \"new byte\" may depend on untrusted input within the header of encoded data.",
"id": "GSD-2020-7226",
"references": [
"https://access.redhat.com/errata/RHSA-2020:5568",
"https://access.redhat.com/errata/RHSA-2020:2515",
"https://access.redhat.com/errata/RHSA-2020:2513",
"https://access.redhat.com/errata/RHSA-2020:2512",
"https://access.redhat.com/errata/RHSA-2020:2511",
"https://access.redhat.com/errata/RHSA-2020:2112",
"https://access.redhat.com/errata/RHSA-2020:2061",
"https://access.redhat.com/errata/RHSA-2020:2060",
"https://access.redhat.com/errata/RHSA-2020:2059",
"https://access.redhat.com/errata/RHSA-2020:2058"
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"date": "2021-12-08",
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"package_slug": "maven/org.cryptacular/cryptacular",
"pubdate": "2020-01-24",
"solution": "Upgrade to versions 1.1.4, 1.2.4 or above.",
"title": "Allocation of Resources Without Limits or Throttling",
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"scope": "UNCHANGED",
"userInteraction": "NONE",
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},
"lastModifiedDate": "2022-05-12T15:00Z",
"publishedDate": "2020-01-24T15:15Z"
}
}
}
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| Author | Source | Type | Date | Other |
|---|
Nomenclature
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- 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.