GSD-2020-7845
Vulnerability from gsd - Updated: 2023-12-13 01:21Details
Spamsniper 5.0 ~ 5.2.7 contain a stack-based buffer overflow vulnerability caused by improper boundary checks when parsing MAIL FROM command. It leads remote attacker to execute arbitrary code via crafted packet.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2020-7845",
"description": "Spamsniper 5.0 ~ 5.2.7 contain a stack-based buffer overflow vulnerability caused by improper boundary checks when parsing MAIL FROM command. It leads remote attacker to execute arbitrary code via crafted packet.",
"id": "GSD-2020-7845"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2020-7845"
],
"details": "Spamsniper 5.0 ~ 5.2.7 contain a stack-based buffer overflow vulnerability caused by improper boundary checks when parsing MAIL FROM command. It leads remote attacker to execute arbitrary code via crafted packet.",
"id": "GSD-2020-7845",
"modified": "2023-12-13T01:21:52.169025Z",
"schema_version": "1.4.0"
}
},
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"ID": "CVE-2020-7845",
"STATE": "PUBLIC",
"TITLE": "Jiransecurity Spamsniper Stack-based Buffer Overflow Vulnerability"
},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "Spamsniper",
"version": {
"version_data": [
{
"version_affected": "\u003c=",
"version_name": "5.2.7",
"version_value": "5.7.8 revision 5500"
}
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]
},
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}
]
}
},
"credit": [
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"value": "KrCERT/CC Vulnerability Analysis Team Researcher Honggi Kim, Hyunsoo Gil, Jeesoo Jurn"
}
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}
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"impact": {
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"attackComplexity": "HIGH",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H",
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"url": "https://www.krcert.or.kr/krcert/secNoticeView.do?bulletin_writing_sequence=35855"
}
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},
"source": {
"discovery": "INTERNAL"
}
},
"nvd.nist.gov": {
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"versionEndExcluding": "5.7.6",
"versionStartIncluding": "5.0.2",
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},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 7.5,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 6.4,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "HIGH",
"userInteractionRequired": false
},
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"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
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"exploitabilityScore": 3.9,
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}
},
"lastModifiedDate": "2020-12-30T15:36Z",
"publishedDate": "2020-12-27T02:15Z"
}
}
}
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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 |
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Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
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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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