FKIE_CVE-2026-17538
Vulnerability from fkie_nvd - Published: 2026-10-08 00:16 - Updated: 2026-10-08 17:24
Severity
Summary
The LatePoint - Appointment Booking & Reservation plugin for WordPress is vulnerable to Insecure Direct Object Reference in versions up to, and including, 5.6.9. This is due to the process_step_customer() function using is_user_logged_in() as the sole gate before merging POSTed customer data into an existing LatePoint customer, without any ownership checks. This makes it possible for authenticated attackers, with Subscriber-level access and above, to modify the personal information (first name, last name, email, phone, notes) of arbitrary LatePoint customers, and, when the contact_merge setting is 'phone', to overwrite the victim's email address and take over the account via a password reset.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "Appointment Booking Plugin \u2013 LatePoint | Calendar \u0026 Scheduling for WordPress",
"vendor": "latepoint",
"versions": [
{
"lessThanOrEqual": "5.6.9",
"status": "affected",
"version": "0",
"versionType": "semver"
}
]
}
],
"source": "security@wordfence.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "The LatePoint - Appointment Booking \u0026 Reservation plugin for WordPress is vulnerable to Insecure Direct Object Reference in versions up to, and including, 5.6.9. This is due to the process_step_customer() function using is_user_logged_in() as the sole gate before merging POSTed customer data into an existing LatePoint customer, without any ownership checks. This makes it possible for authenticated attackers, with Subscriber-level access and above, to modify the personal information (first name, last name, email, phone, notes) of arbitrary LatePoint customers, and, when the contact_merge setting is \u0027phone\u0027, to overwrite the victim\u0027s email address and take over the account via a password reset."
}
],
"id": "CVE-2026-17538",
"lastModified": "2026-10-08T17:24:31.040",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 5.4,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 2.5,
"source": "security@wordfence.com",
"type": "Primary"
}
]
},
"published": "2026-10-08T00:16:35.153",
"references": [
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/changeset/3631493/"
},
{
"source": "security@wordfence.com",
"url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/83cdc51f-b5e1-42b9-972a-7e781f97b43e?source=cve"
}
],
"sourceIdentifier": "security@wordfence.com",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-639"
}
],
"source": "security@wordfence.com",
"type": "Primary"
}
]
}
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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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