CVE-2026-93836 (GCVE-0-2026-93836)
Vulnerability from cvelistv5 – Published: 2026-09-22 07:41 – Updated: 2026-09-22 10:25Title
WPC Product Bundles for WooCommerce <= 8.6.6 - Unauthenticated Stored Cross-Site Scripting via 'qty' Parameter
Summary
The WPC Product Bundles for WooCommerce plugin for WordPress is vulnerable to Stored Cross-Site Scripting via the 'qty' parameter in all versions up to, and including, 8.6.6 due to insufficient input sanitization and output escaping. This makes it possible for unauthenticated attackers to inject arbitrary web scripts in pages that will execute whenever a user accesses an injected page. The float cast used during quantity validation allows a numeric-prefixed payload such as '1<img src=x onerror=...>' to pass validation while retaining its malicious HTML, which is then stored verbatim in order item metadata under the '_woosb_ids' key.
Severity
7.2 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-22 10:07 UTC
CWE
- CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
6 references
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| wpclever | WPC Product Bundles for WooCommerce |
Affected:
0 , ≤ 8.6.6
(semver)
|
guessed |
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 9508844c-3529-4d84-920b-bfebfd2af3e6
Exploited: Yes
Timestamps
First Seen: 2026-10-07
Asserted: 2026-10-07
Scope
Notes: WPC Product Bundles for WooCommerce <= 8.6.6 - Unauthenticated Stored Cross-Site Scripting via 'qty' Parameter | Affected: Wpclever / WPC Product Bundles for WooCommerce | CVSS: 7.2 (HIGH) | EPSS: 0.00243 | Used in malware: unknown | Not yet in CISA KEV: True
Evidence
Type: Public Report
Signal: Successful Exploitation
Confidence: 70%
Source: previdian
Details
| Feed | Previdian (previdian.com) |
|---|---|
| Title | WPC Product Bundles for WooCommerce <= 8.6.6 - Unauthenticated Stored Cross-Site Scripting via 'qty' Parameter |
| Cve Id | CVE-2026-93836 |
| Vendor | Wpclever |
| Ghsa Id | None |
| Product | WPC Product Bundles for WooCommerce |
| Added Date | 2026-10-07T07:08:00.000Z |
| Cvss Score | 7.2 |
| Epss Score | 0.00243 |
| Previous Ids | |
| Cvss Severity | HIGH |
| Virtual Patch | False |
| Cvss Estimated | False |
| Epss Percentile | 0.14185 |
| Used In Malware | unknown |
| Vulnerability Id | CVE-2026-93836 |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | True |
References
Created: 2026-10-08 08:00 UTC
| Updated: 2026-10-08 08:00 UTC
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FKIE_CVE-2026-93836
Vulnerability from fkie_nvd - Published: 2026-09-22 08:16 - Updated: 2026-09-22 19:04
Severity
Summary
The WPC Product Bundles for WooCommerce plugin for WordPress is vulnerable to Stored Cross-Site Scripting via the 'qty' parameter in all versions up to, and including, 8.6.6 due to insufficient input sanitization and output escaping. This makes it possible for unauthenticated attackers to inject arbitrary web scripts in pages that will execute whenever a user accesses an injected page. The float cast used during quantity validation allows a numeric-prefixed payload such as '1<img src=x onerror=...>' to pass validation while retaining its malicious HTML, which is then stored verbatim in order item metadata under the '_woosb_ids' key.
References
Impacted products
| Vendor | Product | Version |
|---|
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GHSA-M435-6CRG-XQ92
Vulnerability from github – Published: 2026-09-22 09:31 – Updated: 2026-09-22 09:31
VLAI
Details
The WPC Product Bundles for WooCommerce plugin for WordPress is vulnerable to Stored Cross-Site Scripting via the 'qty' parameter in all versions up to, and including, 8.6.6 due to insufficient input sanitization and output escaping. This makes it possible for unauthenticated attackers to inject arbitrary web scripts in pages that will execute whenever a user accesses an injected page. The float cast used during quantity validation allows a numeric-prefixed payload such as '1' to pass validation while retaining its malicious HTML, which is then stored verbatim in order item metadata under the '_woosb_ids' key.
Severity
7.2 (High)
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}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:L/I:L/A:N",
"type": "CVSS_V3"
}
]
}
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Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
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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.