FKIE_CVE-2022-46609
Vulnerability from fkie_nvd - Published: 2022-12-14 15:15 - Updated: 2026-06-17 05:12
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
Python3-RESTfulAPI commit d9907f14e9e25dcdb54f5b22252b0e9452e3970e and e772e0beee284c50946e94c54a1d43071ca78b74 was discovered to contain a code execution backdoor via the request package. This vulnerability allows attackers to access sensitive user information and digital currency keys, as well as escalate privileges.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| python3-restfulapi_project | python3-restfulapi | - |
{
"affected": [
{
"affectedData": [
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"product": "n/a",
"vendor": "n/a",
"versions": [
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"status": "affected",
"version": "n/a"
}
]
}
],
"source": "cve@mitre.org"
}
],
"configurations": [
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"nodes": [
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"cpeMatch": [
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"criteria": "cpe:2.3:a:python3-restfulapi_project:python3-restfulapi:-:*:*:*:*:*:*:*",
"matchCriteriaId": "DEC19DF5-94EC-48CC-8C37-A05BD4C237B3",
"vulnerable": true
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"cveTags": [],
"descriptions": [
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"lang": "en",
"value": "Python3-RESTfulAPI commit d9907f14e9e25dcdb54f5b22252b0e9452e3970e and e772e0beee284c50946e94c54a1d43071ca78b74 was discovered to contain a code execution backdoor via the request package. This vulnerability allows attackers to access sensitive user information and digital currency keys, as well as escalate privileges."
},
{
"lang": "es",
"value": "Se descubri\u00f3 que la confirmaci\u00f3n Python3-RESTfulAPI d9907f14e9e25dcdb54f5b22252b0e9452e3970e y e772e0beee284c50946e94c54a1d43071ca78b74 conten\u00edan una puerta trasera de ejecuci\u00f3n de c\u00f3digo a trav\u00e9s del paquete de solicitud. Esta vulnerabilidad permite a los atacantes acceder a informaci\u00f3n confidencial del usuario y claves de moneda digital, as\u00ed como escalar privilegios."
}
],
"id": "CVE-2022-46609",
"lastModified": "2026-06-17T05:12:04.377",
"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"
},
{
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"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": [
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"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2022-46609",
"options": [
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{
"automatable": "no"
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{
"technicalImpact": "total"
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],
"role": "CISA Coordinator",
"timestamp": "2025-04-22T15:09:12.883960Z",
"version": "2.0.3"
}
}
]
},
"published": "2022-12-14T15:15:10.720",
"references": [
{
"source": "cve@mitre.org",
"tags": [
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"url": "https://github.com/herry-zhang/Python3-RESTfulAPI/"
},
{
"source": "cve@mitre.org",
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"url": "https://github.com/herry-zhang/Python3-RESTfulAPI/blob/1c2081dca357685b3180b9baeb7e761e9a10ca99/SECURITY.md"
},
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},
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"source": "cve@mitre.org",
"tags": [
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"url": "https://mirrors.neusoft.edu.cn/pypi/web/simple/request/"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
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"url": "https://github.com/herry-zhang/Python3-RESTfulAPI/blob/1c2081dca357685b3180b9baeb7e761e9a10ca99/SECURITY.md"
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{
"source": "af854a3a-2127-422b-91ae-364da2661108",
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"url": "https://github.com/herry-zhang/Python3-RESTfulAPI/commit/1c2081dca357685b3180b9baeb7e761e9a10ca99"
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"url": "https://mirrors.neusoft.edu.cn/pypi/web/simple/request/"
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"sourceIdentifier": "cve@mitre.org",
"vulnStatus": "Modified",
"weaknesses": [
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"lang": "en",
"value": "NVD-CWE-noinfo"
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"source": "nvd@nist.gov",
"type": "Primary"
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]
}
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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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