CVE-2026-7457 (GCVE-0-2026-7457)
Vulnerability from cvelistv5 – Published: 2026-05-06 06:47 – Updated: 2026-05-06 12:58
VLAI
EPSS
VEX
Title
LatePoint <= 5.5.0 - Authenticated (Subscriber+) Stored Cross-Site Scripting via Customer Cabinet Profile Update
Summary
The LatePoint plugin for WordPress is vulnerable to Stored Cross-Site Scripting in all versions up to and including 5.5.0. This is due to insufficient input sanitization on the customer cabinet profile update endpoint — where raw POST parameters (first_name, last_name, phone, notes) bypass sanitization because OsCustomerModel does not override params_to_sanitize(), causing set_data() to store unsanitized values verbatim in the database — combined with insufficient output escaping in generate_preview(), which injects those stored values into notification template HTML via str_replace() without any esc_html() call before echoing the result. This makes it possible for authenticated attackers with customer-level access or above to inject arbitrary web scripts into the admin notification preview panel that execute in an administrator's or agent's browser whenever a notification template referencing customer variables such as {{customer_full_name}}, {{customer_first_name}}, {{customer_last_name}}, {{customer_phone}}, or {{customer_notes}} is previewed.
Severity
6.4 (Medium)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-05-06 12:58 UTC
CWE
- CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
11 references
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| latepoint | LatePoint – Calendar Booking Plugin for Appointments and Events |
Affected:
0 , ≤ 5.5.0
(semver)
|
guessed |
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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.
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| Author | Source | Type | Date | Other |
|---|
Nomenclature
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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
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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.
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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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