FKIE_CVE-2017-16117
Vulnerability from fkie_nvd - Published: 2018-06-07 02:29 - Updated: 2026-06-17 01:08
Severity
Summary
slug is a module to slugify strings, even if they contain unicode. slug is vulnerable to regular expression denial of service is specially crafted untrusted input is passed as input. About 50k characters can block the event loop for 2 seconds.
References
| URL | Tags | ||
|---|---|---|---|
| support@hackerone.com | https://github.com/dodo/node-slug/issues/82 | Third Party Advisory | |
| support@hackerone.com | https://nodesecurity.io/advisories/537 | Third Party Advisory | |
| af854a3a-2127-422b-91ae-364da2661108 | https://github.com/dodo/node-slug/issues/82 | Third Party Advisory | |
| af854a3a-2127-422b-91ae-364da2661108 | https://nodesecurity.io/advisories/537 | Third Party Advisory |
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| slug_project | slug | * |
{
"affected": [
{
"affectedData": [
{
"product": "slug node module",
"vendor": "HackerOne",
"versions": [
{
"status": "affected",
"version": "All versions"
}
]
}
],
"source": "support@hackerone.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:slug_project:slug:*:*:*:*:*:node.js:*:*",
"matchCriteriaId": "B4A860E8-738F-47B1-8D22-44B57392F9F0",
"versionEndIncluding": "0.9.1",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "slug is a module to slugify strings, even if they contain unicode. slug is vulnerable to regular expression denial of service is specially crafted untrusted input is passed as input. About 50k characters can block the event loop for 2 seconds."
},
{
"lang": "es",
"value": "slug es un m\u00f3dulo para \"slugificar\" cadenas, incluso aunque contengan unicode. slug es vulnerable a una denegaci\u00f3n de servicio (DoS) por expresiones regulares si se pasan entradas no fiables especialmente manipuladas como entrada. Una cantidad aproximada de 50k caracteres pueden bloquear el bucle de eventos durante 2 segundos."
}
],
"id": "CVE-2017-16117",
"lastModified": "2026-06-17T01:08:49.610",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": true,
"baseSeverity": "MEDIUM",
"cvssData": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 5.0,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"source": "nvd@nist.gov",
"type": "Primary",
"userInteractionRequired": false
}
],
"cvssMetricV30": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.0"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6,
"source": "nvd@nist.gov",
"type": "Primary"
}
]
},
"published": "2018-06-07T02:29:02.910",
"references": [
{
"source": "support@hackerone.com",
"tags": [
"Third Party Advisory"
],
"url": "https://github.com/dodo/node-slug/issues/82"
},
{
"source": "support@hackerone.com",
"tags": [
"Third Party Advisory"
],
"url": "https://nodesecurity.io/advisories/537"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Third Party Advisory"
],
"url": "https://github.com/dodo/node-slug/issues/82"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Third Party Advisory"
],
"url": "https://nodesecurity.io/advisories/537"
}
],
"sourceIdentifier": "support@hackerone.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-400"
}
],
"source": "support@hackerone.com",
"type": "Secondary"
},
{
"description": [
{
"lang": "en",
"value": "CWE-400"
}
],
"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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