GSD-2022-1930
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
An exponential ReDoS (Regular Expression Denial of Service) can be triggered in the eth-account PyPI package, when an attacker is able to supply arbitrary input to the encode_structured_data method
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-1930",
"description": "An exponential ReDoS (Regular Expression Denial of Service) can be triggered in the eth-account PyPI package, when an attacker is able to supply arbitrary input to the encode_structured_data method",
"id": "GSD-2022-1930"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2022-1930"
],
"details": "An exponential ReDoS (Regular Expression Denial of Service) can be triggered in the eth-account PyPI package, when an attacker is able to supply arbitrary input to the encode_structured_data method",
"id": "GSD-2022-1930",
"modified": "2023-12-13T01:19:27.788726Z",
"schema_version": "1.4.0"
}
},
"namespaces": {
"cve.org": {
"CVE_data_meta": {
"ASSIGNER": "security@jfrog.com",
"ID": "CVE-2022-1930",
"STATE": "PUBLIC",
"TITLE": "ReDoS in eth-account encode_structured_data function"
},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "eth-account",
"version": {
"version_data": [
{
"platform": "",
"version_affected": "\u003c",
"version_name": "0.5.9",
"version_value": ""
}
]
}
}
]
},
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}
]
}
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"description": {
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"value": "An exponential ReDoS (Regular Expression Denial of Service) can be triggered in the eth-account PyPI package, when an attacker is able to supply arbitrary input to the encode_structured_data method"
}
]
},
"impact": {
"cvss": {
"attackComplexity": "HIGH",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 5.9,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
}
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "eng",
"value": "CWE-1333 Inefficient Regular Expression Complexity"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://research.jfrog.com/vulnerabilities/eth-account-redos-xray-248681/",
"refsource": "MISC",
"url": "https://research.jfrog.com/vulnerabilities/eth-account-redos-xray-248681/"
}
]
}
},
"gitlab.com": {
"advisories": [
{
"affected_range": "\u003c0.5.9",
"affected_versions": "All versions before 0.5.9",
"cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-1333",
"CWE-937"
],
"date": "2023-07-24",
"description": "An exponential ReDoS (Regular Expression Denial of Service) can be triggered in the eth-account PyPI package, when an attacker is able to supply arbitrary input to the encode_structured_data method",
"fixed_versions": [
"0.5.9"
],
"identifier": "CVE-2022-1930",
"identifiers": [
"CVE-2022-1930"
],
"not_impacted": "All versions starting from 0.5.9",
"package_slug": "pypi/eth-account",
"pubdate": "2022-08-22",
"solution": "Upgrade to version 0.5.9 or above.",
"title": "Incorrect Comparison",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2022-1930",
"https://research.jfrog.com/vulnerabilities/eth-account-redos-xray-248681/"
],
"uuid": "bb49867d-be52-4580-aed8-36434f7aa1f5"
}
]
},
"nvd.nist.gov": {
"configurations": {
"CVE_data_version": "4.0",
"nodes": [
{
"children": [],
"cpe_match": [
{
"cpe23Uri": "cpe:2.3:a:ethereum:eth-account:*:*:*:*:*:python:*:*",
"cpe_name": [],
"versionEndExcluding": "0.5.9",
"vulnerable": true
}
],
"operator": "OR"
}
]
},
"cve": {
"CVE_data_meta": {
"ASSIGNER": "security@jfrog.com",
"ID": "CVE-2022-1930"
},
"data_format": "MITRE",
"data_type": "CVE",
"data_version": "4.0",
"description": {
"description_data": [
{
"lang": "en",
"value": "An exponential ReDoS (Regular Expression Denial of Service) can be triggered in the eth-account PyPI package, when an attacker is able to supply arbitrary input to the encode_structured_data method"
}
]
},
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "en",
"value": "CWE-1333"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://research.jfrog.com/vulnerabilities/eth-account-redos-xray-248681/",
"refsource": "MISC",
"tags": [
"Exploit",
"Third Party Advisory"
],
"url": "https://research.jfrog.com/vulnerabilities/eth-account-redos-xray-248681/"
}
]
}
},
"impact": {
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6
}
},
"lastModifiedDate": "2023-07-24T13:07Z",
"publishedDate": "2022-08-22T19:15Z"
}
}
}
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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 |
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Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
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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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