CVE-2026-86583 (GCVE-0-2026-86583)
Vulnerability from cvelistv5 – Published: 2026-09-23 21:27 – Updated: 2026-09-24 13:23
VLAI
EPSS
VEX
Title
Import and export users and customers <= 2.4.17 - Authenticated (Subscriber+) Privilege Escalation via CSV Escape-Character Mismatch in Export/Import Round Trip via display_name and nickname Profile Fields
Summary
The Import and export users and customers plugin for WordPress is vulnerable to Privilege Escalation in all versions up to, and including, 2.4.17 via the plugin's own export and re-import workflow. The vulnerability exists because the exporter writes CSV cells using fputcsv() with a NUL byte (\0) as the escape character, while the importer parses the same file using SplFileObject::fgetcsv() with only a single delimiter argument, causing PHP's default backslash escape character to be applied instead; because the export column layout places display_name immediately before the role column and nickname immediately after, an attacker can store crafted values in those two profile fields — saved by WordPress core via the standard profile page — such that the escape mismatch causes the parser to merge the display_name cell into the role field and rebalance the column count via nickname, yielding administrator as the parsed role for their own row when it reaches the import_user function's add_role function. This makes it possible for authenticated attackers with Subscriber-level access or above to escalate their privileges to Administrator. Exploitation requires a site administrator to trigger the plugin's documented export re-import migration with both "Update existing users" and "Update roles for existing users" set to "yes".
Severity
8.8 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-24 13:22 UTC
CWE
- CWE-266 - Incorrect Privilege Assignment
Assigner
References
7 references
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| carazo | Import and export users and customers |
Affected:
0 , ≤ 2.4.17
(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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