GSD-2018-7537
Vulnerability from gsd - Updated: 2023-12-13 01:22Details
An issue was discovered in Django 2.0 before 2.0.3, 1.11 before 1.11.11, and 1.8 before 1.8.19. If django.utils.text.Truncator's chars() and words() methods were passed the html=True argument, they were extremely slow to evaluate certain inputs due to a catastrophic backtracking vulnerability in a regular expression. The chars() and words() methods are used to implement the truncatechars_html and truncatewords_html template filters, which were thus vulnerable.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2018-7537",
"description": "An issue was discovered in Django 2.0 before 2.0.3, 1.11 before 1.11.11, and 1.8 before 1.8.19. If django.utils.text.Truncator\u0027s chars() and words() methods were passed the html=True argument, they were extremely slow to evaluate certain inputs due to a catastrophic backtracking vulnerability in a regular expression. The chars() and words() methods are used to implement the truncatechars_html and truncatewords_html template filters, which were thus vulnerable.",
"id": "GSD-2018-7537",
"references": [
"https://www.suse.com/security/cve/CVE-2018-7537.html",
"https://www.debian.org/security/2018/dsa-4161",
"https://access.redhat.com/errata/RHSA-2019:0265",
"https://access.redhat.com/errata/RHSA-2018:2927",
"https://ubuntu.com/security/CVE-2018-7537",
"https://advisories.mageia.org/CVE-2018-7537.html",
"https://security.archlinux.org/CVE-2018-7537"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
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"aliases": [
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"details": "An issue was discovered in Django 2.0 before 2.0.3, 1.11 before 1.11.11, and 1.8 before 1.8.19. If django.utils.text.Truncator\u0027s chars() and words() methods were passed the html=True argument, they were extremely slow to evaluate certain inputs due to a catastrophic backtracking vulnerability in a regular expression. The chars() and words() methods are used to implement the truncatechars_html and truncatewords_html template filters, which were thus vulnerable.",
"id": "GSD-2018-7537",
"modified": "2023-12-13T01:22:32.484785Z",
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"affected_range": "\u003e=1.8,\u003c1.8.19||\u003e=1.11,\u003c1.11.11||\u003e=2.0,\u003c2.0.3",
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"cwe_ids": [
"CWE-1035",
"CWE-185",
"CWE-937"
],
"date": "2019-02-28",
"description": "If `django.utils.text.Truncator`\u0027s `chars()` and `words()` methods were passed the `html=True` argument, they were extremely slow to evaluate certain inputs due to a catastrophic backtracking vulnerability in a regular expression. The `chars()` and words()` methods are used to implement the `truncatechars_html` and `truncatewords_html` template filters, which were thus vulnerable.",
"fixed_versions": [
"1.8.19",
"1.11.11",
"2.0.3"
],
"identifier": "CVE-2018-7537",
"identifiers": [
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"not_impacted": "All versions before 1.8, all versions starting from 1.8.19 before 1.11, all versions starting from 1.11.11 before 2.0, all versions starting from 2.0.3",
"package_slug": "pypi/Django",
"pubdate": "2018-03-09",
"solution": "Upgrade to versions 1.8.19, 1.11.11, 2.0.3 or above.",
"title": "Incorrect Regular Expression",
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"baseScore": 5.0,
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"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
"version": "2.0"
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"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
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"attackVector": "NETWORK",
"availabilityImpact": "LOW",
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"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:L",
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"lastModifiedDate": "2019-02-28T22:37Z",
"publishedDate": "2018-03-09T20:29Z"
}
}
}
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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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