CVE-2024-24548 (GCVE-0-2024-24548)
Vulnerability from cvelistv5 – Published: 2024-02-01 06:31 – Updated: 2024-08-01 23:19
VLAI
EPSS
VEX
Summary
Payment EX Ver1.1.5b and earlier allows a remote unauthenticated attacker to obtain the information of the user who purchases merchandise using Payment EX.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-06-28 16:44 UTC
CWE
- Information disclosure
- CWE-200 - Exposure of Sensitive Information to an Unauthorized Actor
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://jvn.jp/en/jp/JVN41129639/ |
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Simplesite | Payment EX |
Affected:
Ver1.1.5b and earlier
|
guessed | |
| estore-wss | payment_ex |
Affected:
0 , ≤ 1.1.5b
(custom)
cpe:2.3:a:estore-wss:payment_ex:*:*:*:*:*:*:*:* |
{
"containers": {
"adp": [
{
"affected": [
{
"cpes": [
"cpe:2.3:a:estore-wss:payment_ex:*:*:*:*:*:*:*:*"
],
"defaultStatus": "unknown",
"product": "payment_ex",
"vendor": "estore-wss",
"versions": [
{
"lessThanOrEqual": "1.1.5b",
"status": "affected",
"version": "0",
"versionType": "custom"
}
]
}
],
"metrics": [
{
"cvssV3_1": {
"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"
}
},
{
"other": {
"content": {
"id": "CVE-2024-24548",
"options": [
{
"Exploitation": "none"
},
{
"Automatable": "yes"
},
{
"Technical Impact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2024-06-28T16:44:32.673813Z",
"version": "2.0.3"
},
"type": "ssvc"
}
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-200",
"description": "CWE-200 Exposure of Sensitive Information to an Unauthorized Actor",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2024-06-28T16:47:56.665Z",
"orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"shortName": "CISA-ADP"
},
"title": "CISA ADP Vulnrichment"
},
{
"providerMetadata": {
"dateUpdated": "2024-08-01T23:19:52.359Z",
"orgId": "af854a3a-2127-422b-91ae-364da2661108",
"shortName": "CVE"
},
"references": [
{
"tags": [
"x_transferred"
],
"url": "https://jvn.jp/en/jp/JVN41129639/"
}
],
"title": "CVE Program Container"
}
],
"cna": {
"affected": [
{
"product": "Payment EX",
"vendor": "Simplesite",
"versions": [
{
"status": "affected",
"version": "Ver1.1.5b and earlier"
}
]
}
],
"descriptions": [
{
"lang": "en",
"value": "Payment EX Ver1.1.5b and earlier allows a remote unauthenticated attacker to obtain the information of the user who purchases merchandise using Payment EX."
}
],
"problemTypes": [
{
"descriptions": [
{
"description": "Information disclosure",
"lang": "en",
"type": "text"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2024-02-01T06:31:20.445Z",
"orgId": "ede6fdc4-6654-4307-a26d-3331c018e2ce",
"shortName": "jpcert"
},
"references": [
{
"url": "https://jvn.jp/en/jp/JVN41129639/"
}
]
}
},
"cveMetadata": {
"assignerOrgId": "ede6fdc4-6654-4307-a26d-3331c018e2ce",
"assignerShortName": "jpcert",
"cveId": "CVE-2024-24548",
"datePublished": "2024-02-01T06:31:20.445Z",
"dateReserved": "2024-01-25T11:07:20.033Z",
"dateUpdated": "2024-08-01T23:19:52.359Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1",
"vulnerability-lookup:meta": {
"epss": {
"cve": "CVE-2024-24548",
"date": "2026-09-17",
"epss": "0.00571",
"percentile": "0.45794"
},
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"redhat_vex": {
"current_release_date": "2025-05-28T20:51:24+00:00",
"cve": "CVE-2024-24548",
"id": "CVE-2024-24548",
"initial_release_date": "2024-01-01T00:00:00+00:00",
"product_status:known_not_affected": "1",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "CVE-2024-24548",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2024/cve-2024-24548.json",
"version": "3"
},
"vulnrichment": {
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"dataType": "CVE_RECORD",
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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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