FKIE_CVE-2024-38983
Vulnerability from fkie_nvd - Published: 2024-07-30 21:15 - Updated: 2026-06-17 07:41
Severity
9.8 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
9.8 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
9.8 (Critical) - CVSS:3.1/
Summary
Prototype Pollution in alykoshin mini-deep-assign v0.0.8 allows an attacker to execute arbitrary code or cause a Denial of Service (DoS) and cause other impacts via the _assign() method at (/lib/index.js:91)
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| alykoshin | mini-deep-assign | 0.0.8 |
{
"affected": [
{
"affectedData": [
{
"product": "n/a",
"vendor": "n/a",
"versions": [
{
"status": "affected",
"version": "n/a"
}
]
}
],
"source": "cve@mitre.org"
},
{
"affectedData": [
{
"cpes": [
"cpe:2.3:a:alykoshin:mini-deep-assign:0.0.8:*:*:*:*:*:*:*"
],
"defaultStatus": "unknown",
"product": "mini-deep-assign",
"vendor": "alykoshin",
"versions": [
{
"status": "affected",
"version": "0.0.8"
}
]
}
],
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:alykoshin:mini-deep-assign:0.0.8:*:*:*:*:*:*:*",
"matchCriteriaId": "CAF293A7-7473-46B5-8A70-AB68DE2C1651",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Prototype Pollution in alykoshin mini-deep-assign v0.0.8 allows an attacker to execute arbitrary code or cause a Denial of Service (DoS) and cause other impacts via the _assign() method at (/lib/index.js:91)"
},
{
"lang": "es",
"value": " Prototype Pollution en alykoshin mini-deep-assign v0.0.8 permite a un atacante ejecutar c\u00f3digo arbitrario o causar una denegaci\u00f3n de servicio (DoS) y causar otros impactos a trav\u00e9s del m\u00e9todo _assign() en (/lib/index.js:91)"
}
],
"id": "CVE-2024-38983",
"lastModified": "2026-06-17T07:41:18.157",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 5.9,
"source": "nvd@nist.gov",
"type": "Primary"
},
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 5.9,
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2024-38983",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "yes"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2024-07-31T12:58:24.520708Z",
"version": "2.0.3"
}
}
]
},
"published": "2024-07-30T21:15:09.700",
"references": [
{
"source": "cve@mitre.org",
"tags": [
"Exploit"
],
"url": "https://gist.github.com/mestrtee/f82d0c3a8fe3a125f06425caef5d22ed"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Exploit"
],
"url": "https://gist.github.com/mestrtee/f82d0c3a8fe3a125f06425caef5d22ed"
}
],
"sourceIdentifier": "cve@mitre.org",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-1321"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
},
{
"description": [
{
"lang": "en",
"value": "CWE-1321"
}
],
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"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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