GSD-2017-11424
Vulnerability from gsd - Updated: 2023-12-13 01:21Details
In PyJWT 1.5.0 and below the `invalid_strings` check in `HMACAlgorithm.prepare_key` does not account for all PEM encoded public keys. Specifically, the PKCS1 PEM encoded format would be allowed because it is prefaced with the string `-----BEGIN RSA PUBLIC KEY-----` which is not accounted for. This enables symmetric/asymmetric key confusion attacks against users using the PKCS1 PEM encoded public keys, which would allow an attacker to craft JWTs from scratch.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2017-11424",
"description": "In PyJWT 1.5.0 and below the `invalid_strings` check in `HMACAlgorithm.prepare_key` does not account for all PEM encoded public keys. Specifically, the PKCS1 PEM encoded format would be allowed because it is prefaced with the string `-----BEGIN RSA PUBLIC KEY-----` which is not accounted for. This enables symmetric/asymmetric key confusion attacks against users using the PKCS1 PEM encoded public keys, which would allow an attacker to craft JWTs from scratch.",
"id": "GSD-2017-11424",
"references": [
"https://www.suse.com/security/cve/CVE-2017-11424.html",
"https://www.debian.org/security/2017/dsa-3979",
"https://ubuntu.com/security/CVE-2017-11424"
]
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2017-11424"
],
"details": "In PyJWT 1.5.0 and below the `invalid_strings` check in `HMACAlgorithm.prepare_key` does not account for all PEM encoded public keys. Specifically, the PKCS1 PEM encoded format would be allowed because it is prefaced with the string `-----BEGIN RSA PUBLIC KEY-----` which is not accounted for. This enables symmetric/asymmetric key confusion attacks against users using the PKCS1 PEM encoded public keys, which would allow an attacker to craft JWTs from scratch.",
"id": "GSD-2017-11424",
"modified": "2023-12-13T01:21:15.809363Z",
"schema_version": "1.4.0"
}
},
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},
"gitlab.com": {
"advisories": [
{
"affected_range": "\u003c=1.5.0",
"affected_versions": "All versions up to 1.5.0",
"cvss_v2": "AV:N/AC:L/Au:N/C:N/I:P/A:N",
"cvss_v3": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N",
"cwe_ids": [
"CWE-1035",
"CWE-937"
],
"date": "2019-10-03",
"description": "In PyJWT, the `invalid_strings` check in `HMACAlgorithm.prepare_key` does not account for all PEM encoded public keys. Specifically, the PKCS1 PEM encoded format would be allowed because it is prefaced with the string `-----BEGIN RSA PUBLIC KEY-----` which is not accounted for. This enables `symmetric/asymmetric` key confusion attacks against users using the PKCS1 PEM encoded public keys, which would allow an attacker to craft JWTs from scratch.",
"fixed_versions": [
"1.5.1"
],
"identifier": "CVE-2017-11424",
"identifiers": [
"CVE-2017-11424"
],
"not_impacted": "All versions after 1.5.0",
"package_slug": "pypi/PyJWT",
"pubdate": "2017-08-24",
"solution": "Upgrade to version 1.5.1 or above.",
"title": "Improper Certificate Validation",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2017-11424",
"https://github.com/jpadilla/pyjwt/pull/277"
],
"uuid": "25c6cb12-0763-4e3a-bd28-b68360b076b3"
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"vulnerable": true
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},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "NONE",
"baseScore": 5.0,
"confidentialityImpact": "NONE",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:N/C:N/I:P/A:N",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
},
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"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N",
"version": "3.0"
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"exploitabilityScore": 3.9,
"impactScore": 3.6
}
},
"lastModifiedDate": "2019-10-03T00:03Z",
"publishedDate": "2017-08-24T16:29Z"
}
}
}
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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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