CVE-2021-36888 (GCVE-0-2021-36888)
Vulnerability from cvelistv5 – Published: 2021-12-15 18:06 – Updated: 2026-04-28 16:07Title
WordPress Image Hover Effects Ultimate plugin <= 9.6.1 - Unauthenticated Arbitrary Options Update leading to full website compromise
Summary
Unauthenticated Arbitrary Options Update vulnerability leading to full website compromise discovered in Image Hover Effects Ultimate (versions <= 9.6.1) WordPress plugin.
Severity
9.8 (Critical)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-03-28 16:16 UTC
CWE
- CWE-284 - Improper Access Control
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://wordpress.org/plugins/image-hover-effects… | x_refsource_CONFIRM |
| https://patchstack.com/database/vulnerability/ima… | x_refsource_CONFIRM |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| Oxilab | Image Hover Effects Ultimate (WordPress plugin) |
Affected:
<= 9.6.1 , ≤ 9.6.1
(custom)
|
Date Public
2021-12-15 00:00
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 362cef42-9ac6-41be-be3f-04d9c1a18dfd
Exploited: Yes
Timestamps
First Seen: 2021-12-15
Asserted: 2021-12-15
Scope
Notes: WordPress Image Hover Effects Ultimate plugin <= 9.6.1 - Unauthenticated Arbitrary Options Update leading to full website compromise | Affected: Oxilab / Image Hover Effects Ultimate (WordPress plugin) | CVSS: 9.8 (CRITICAL) | EPSS: 0.06685 | 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 | WordPress Image Hover Effects Ultimate plugin <= 9.6.1 - Unauthenticated Arbitrary Options Update leading to full website compromise |
| Cve Id | CVE-2021-36888 |
| Vendor | Oxilab |
| Ghsa Id | None |
| Product | Image Hover Effects Ultimate (WordPress plugin) |
| Added Date | 2021-12-15T18:06:58.000Z |
| Cvss Score | 9.8 |
| Epss Score | 0.06685 |
| Previous Ids | |
| Cvss Severity | CRITICAL |
| Virtual Patch | False |
| Cvss Estimated | False |
| Epss Percentile | 0.93698 |
| Used In Malware | unknown |
| Vulnerability Id | CVE-2021-36888 |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | True |
References
Created: 2026-10-02 09:11 CEST
| Updated: 2026-10-02 09:11 CEST
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"dateUpdated": "2025-03-28T16:16:42.122Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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