GSD-2021-24651
Vulnerability from gsd - Updated: 2023-12-13 01:23Details
The Poll Maker WordPress plugin before 3.4.2 allows unauthenticated users to perform SQL injection via the ays_finish_poll AJAX action. While the result is not disclosed in the response, it is possible to use a timing attack to exfiltrate data such as password hash.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2021-24651",
"description": "The Poll Maker WordPress plugin before 3.4.2 allows unauthenticated users to perform SQL injection via the ays_finish_poll AJAX action. While the result is not disclosed in the response, it is possible to use a timing attack to exfiltrate data such as password hash.",
"id": "GSD-2021-24651"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2021-24651"
],
"details": "The Poll Maker WordPress plugin before 3.4.2 allows unauthenticated users to perform SQL injection via the ays_finish_poll AJAX action. While the result is not disclosed in the response, it is possible to use a timing attack to exfiltrate data such as password hash.",
"id": "GSD-2021-24651",
"modified": "2023-12-13T01:23:37.340196Z",
"schema_version": "1.4.0"
}
},
"namespaces": {
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"ASSIGNER": "contact@wpscan.com",
"ID": "CVE-2021-24651",
"STATE": "PUBLIC",
"TITLE": "Poll Maker \u003c 3.4.2 - Unauthenticated Time Based SQL Injection"
},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "Poll Maker",
"version": {
"version_data": [
{
"version_affected": "\u003c",
"version_name": "3.4.2",
"version_value": "3.4.2"
}
]
}
}
]
},
"vendor_name": "Unknown"
}
]
}
},
"credit": [
{
"lang": "eng",
"value": "apple502j"
}
],
"data_format": "MITRE",
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"description": {
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"value": "The Poll Maker WordPress plugin before 3.4.2 allows unauthenticated users to perform SQL injection via the ays_finish_poll AJAX action. While the result is not disclosed in the response, it is possible to use a timing attack to exfiltrate data such as password hash."
}
]
},
"generator": "WPScan CVE Generator",
"problemtype": {
"problemtype_data": [
{
"description": [
{
"lang": "eng",
"value": "CWE-89 SQL Injection"
}
]
},
{
"description": [
{
"lang": "eng",
"value": "CWE-203 Observable Discrepancy"
}
]
}
]
},
"references": {
"reference_data": [
{
"name": "https://wpscan.com/vulnerability/24f933b0-ad57-4ed3-817d-d637256e2fb1",
"refsource": "MISC",
"url": "https://wpscan.com/vulnerability/24f933b0-ad57-4ed3-817d-d637256e2fb1"
}
]
},
"source": {
"discovery": "EXTERNAL"
}
},
"nvd.nist.gov": {
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"nodes": [
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"cpe_match": [
{
"cpe23Uri": "cpe:2.3:a:ays-pro:poll_maker:*:*:*:*:*:wordpress:*:*",
"cpe_name": [],
"versionEndExcluding": "3.4.2",
"vulnerable": true
}
],
"operator": "OR"
}
]
},
"cve": {
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"description": {
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}
]
},
"problemtype": {
"problemtype_data": [
{
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{
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"value": "CWE-89"
},
{
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}
]
},
"references": {
"reference_data": [
{
"name": "https://wpscan.com/vulnerability/24f933b0-ad57-4ed3-817d-d637256e2fb1",
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"tags": [
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}
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},
"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "NONE",
"baseScore": 5.0,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:N/C:P/I:N/A:N",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 2.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
},
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6
}
},
"lastModifiedDate": "2022-11-09T21:49Z",
"publishedDate": "2021-10-11T11:15Z"
}
}
}
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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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