FKIE_CVE-2017-12471
Vulnerability from fkie_nvd - Published: 2018-02-07 17:29 - Updated: 2026-06-17 01:03
Severity
Summary
The cnb_parse_lev function in CCN-lite before 2.00 allows context-dependent attackers to have unspecified impact by leveraging failure to check for out-of-bounds conditions, which triggers an invalid read in the hexdump function.
References
| URL | Tags | ||
|---|---|---|---|
| cve@mitre.org | https://github.com/cn-uofbasel/ccn-lite/issues/137 | Third Party Advisory | |
| cve@mitre.org | https://github.com/cn-uofbasel/ccn-lite/releases/tag/2.0.0 | Release Notes, Third Party Advisory | |
| af854a3a-2127-422b-91ae-364da2661108 | https://github.com/cn-uofbasel/ccn-lite/issues/137 | Third Party Advisory | |
| af854a3a-2127-422b-91ae-364da2661108 | https://github.com/cn-uofbasel/ccn-lite/releases/tag/2.0.0 | Release Notes, Third Party Advisory |
{
"affected": [
{
"affectedData": [
{
"product": "n/a",
"vendor": "n/a",
"versions": [
{
"status": "affected",
"version": "n/a"
}
]
}
],
"source": "cve@mitre.org"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:ccn-lite:ccn-lite:*:*:*:*:*:*:*:*",
"matchCriteriaId": "E507B42A-708A-40E9-BC27-0CC03250C55D",
"versionEndExcluding": "2.0.0",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "The cnb_parse_lev function in CCN-lite before 2.00 allows context-dependent attackers to have unspecified impact by leveraging failure to check for out-of-bounds conditions, which triggers an invalid read in the hexdump function."
},
{
"lang": "es",
"value": "La funci\u00f3n cnb_parse_lev en CCN-lite, en versiones anteriores a la 2.00, permite que atacantes dependientes del contexto provoquen un impacto sin especificar aprovechando el error a la hora de comprobar condiciones fuera de l\u00edmites, lo que desencadena una lectura inv\u00e1lida en la funci\u00f3n hexdump."
}
],
"id": "CVE-2017-12471",
"lastModified": "2026-06-17T01:03:21.620",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": true,
"baseSeverity": "HIGH",
"cvssData": {
"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,
"source": "nvd@nist.gov",
"type": "Primary",
"userInteractionRequired": false
}
],
"cvssMetricV30": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.0"
},
"exploitabilityScore": 3.9,
"impactScore": 5.9,
"source": "nvd@nist.gov",
"type": "Primary"
}
]
},
"published": "2018-02-07T17:29:00.967",
"references": [
{
"source": "cve@mitre.org",
"tags": [
"Third Party Advisory"
],
"url": "https://github.com/cn-uofbasel/ccn-lite/issues/137"
},
{
"source": "cve@mitre.org",
"tags": [
"Release Notes",
"Third Party Advisory"
],
"url": "https://github.com/cn-uofbasel/ccn-lite/releases/tag/2.0.0"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Third Party Advisory"
],
"url": "https://github.com/cn-uofbasel/ccn-lite/issues/137"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Release Notes",
"Third Party Advisory"
],
"url": "https://github.com/cn-uofbasel/ccn-lite/releases/tag/2.0.0"
}
],
"sourceIdentifier": "cve@mitre.org",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-119"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
}
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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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