CVE-2026-75957 (GCVE-0-2026-75957)
Vulnerability from cvelistv5 – Published: 2026-10-01 07:40 – Updated: 2026-10-01 07:40
VLAI
EPSS
VEX
Title
Ultimate Multisite <= 2.15.0 - Unauthenticated Authentication Bypass via 'checkout_form' Parameter
Summary
The Ultimate Multisite – WordPress Multisite SaaS & WaaS Platform plugin for WordPress is vulnerable to Authentication Bypass in all versions up to, and including, 2.15.0 via the `checkout_form` parameter of the `login_customer_after_checkout` function. This is due to the publicly accessible `wu_ajax_nopriv_wu_validate_form` AJAX handler accepting a freely obtainable checkout nonce, and the `checkout_form=wu-finish-checkout` parameter causing `get_validation_rules()` to discard all validation rules while `finish_checkout_form_fields()` returns an empty step list — forcing `is_last_step()` to return true and routing the request directly into full order processing — after which `maybe_create_customer()` resolves the attacker-supplied `email_address` to an existing WordPress user ID without any authentication or ownership verification, and `login_customer_after_checkout()` calls `wp_set_auth_cookie()` for that user ID via a passwordless code path. This makes it possible for unauthenticated attackers to log in as any existing WordPress user — including a Network Super Admin — simply by knowing their email address. Exploitation requires that the targeted user account has no pre-existing Ultimate Multisite customer record; accounts such as a Network Super Admin on a fresh Multisite install, or any administrator or editor added before Ultimate Multisite was configured, satisfy this condition and are therefore exploitable.
Severity
9.8 (Critical)
CWE
- CWE-287 - Improper Authentication
Assigner
References
13 references
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| superdav42 | Ultimate Multisite – WordPress Multisite SaaS & WaaS Platform |
Affected:
0 , ≤ 2.15.0
(semver)
|
guessed |
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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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