CVE-2026-91153 (GCVE-0-2026-91153)
Vulnerability from cvelistv5 – Published: 2026-10-29 09:25 – Updated: 2026-10-29 10:45
VLAI
EPSS
VEX
Title
Everest Forms <= 3.6.2 - Unauthenticated Sensitive Information Exposure via Smart-Tag Injection in Smart-Tag Injection in Form Field Values ({post_meta key=...})
Summary
The Everest Forms – Contact Form, Payment Form, Quiz, Survey & Custom Form Builder with AI plugin for WordPress is vulnerable to Sensitive Information Exposure in all versions up to, and including, 3.6.2 via the process. This makes it possible for unauthenticated attackers to extract arbitrary WordPress post meta values — including license keys, API tokens, SMTP credentials, and Stripe or AWS secrets stored on any post type — via form submission notification emails or stored entries. The submission nonce is publicly rendered in every embedded form and can additionally be minted anonymously via the nopriv everest_forms_get_form_update_nonce action, meaning no account or prior authentication of any kind is required to complete the exploit.
Severity
5.3 (Medium)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-29 10:31 UTC
CWE
- CWE-200 - Exposure of Sensitive Information to an Unauthorized Actor
Assigner
References
9 references
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| wpeverest | Everest Forms – Contact Form, Payment Form, Quiz, Survey & Custom Form Builder with AI |
Affected:
0 , ≤ 3.6.2
(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.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
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Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
How durations are calculated
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vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
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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.
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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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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.