CVE-2022-0952 (GCVE-0-2022-0952)
Vulnerability from cvelistv5 – Published: 2022-05-02 16:05 – Updated: 2024-08-02 23:47Title
Sitemap by click5 < 1.0.36 - Unauthenticated Arbitrary Options Update
Summary
The Sitemap by click5 WordPress plugin before 1.0.36 does not have authorisation and CSRF checks when updating options via a REST endpoint, and does not ensure that the option to be updated belongs to the plugin. As a result, unauthenticated attackers could change arbitrary blog options, such as the users_can_register and default_role, allowing them to create a new admin account and take over the blog.
Severity
8.8 (High)
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://wpscan.com/vulnerability/0f694961-afab-44… | exploitvdb-entrytechnical-description |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| Unknown | Sitemap by click5 |
Affected:
0 , < 1.0.36
(custom)
|
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 2438292e-9397-4dc3-8fa7-26ad0f6467ad
Exploited: Yes
Timestamps
First Seen: 2025-07-21
Asserted: 2025-07-21
Scope
Notes: Sitemap by click5 < 1.0.36 - Unauthenticated Arbitrary Options Update | Affected: click5 / Sitemap | CVSS: 8.8 (HIGH) | EPSS: 0.11419 | 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 | Sitemap by click5 < 1.0.36 - Unauthenticated Arbitrary Options Update |
| Cve Id | CVE-2022-0952 |
| Vendor | click5 |
| Ghsa Id | None |
| Product | Sitemap |
| Added Date | 2025-07-21T00:00:00.000Z |
| Cvss Score | 8.8 |
| Epss Score | 0.11419 |
| Previous Ids | |
| Cvss Severity | HIGH |
| Virtual Patch | False |
| Cvss Estimated | False |
| Epss Percentile | 0.9588 |
| Used In Malware | unknown |
| Vulnerability Id | CVE-2022-0952 |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | True |
References
Created: 2026-10-02 09:09 CEST
| Updated: 2026-10-02 09:09 CEST
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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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