CVE-2026-89093 (GCVE-0-2026-89093)
Vulnerability from cvelistv5 – Published: 2026-09-19 02:27 – Updated: 2026-09-19 02:27
VLAI
EPSS
VEX
Title
Better Messages <= 2.15.33 - Unauthenticated Information Exposure Spoofing via 'X-Real-IP' Header via /guests/register
Summary
The Better Messages – Chat Rooms, Group Chat, Private Messages & AI Chat Bots plugin for WordPress is vulnerable to Information Exposure by Spoofing in all versions up to, and including, 2.15.33. This is due to the `is_ai_bot_user()` function identifying privileged internal AI bot accounts by performing a prefix check for `'ai-chat-bot-'` against a guest record's stored IP address, which is populated verbatim from the client-controlled `X-Real-IP` request header during unauthenticated guest registration. This makes it possible for unauthenticated attackers to register a guest identity that the plugin treats as its own internal AI bot, bypassing the per-room role allowlist, draft-status check, and join filters — which are all short-circuited by the bot check in `user_can_join()` and `user_can_read()` — to join administrator-restricted chat rooms, post messages into them, and read the private message history of other users.
Severity
5.3 (Medium)
CWE
- CWE-287 - Improper Authentication
Assigner
References
9 references
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| wordplus | Better Messages – Chat Rooms, Group Chat, Private Messages & AI Chat Bots |
Affected:
0 , ≤ 2.15.33
(semver)
|
guessed |
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}
],
"metrics": [
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"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
"version": "3.1"
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"problemTypes": [
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"descriptions": [
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"description": "CWE-287 Improper Authentication",
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"providerMetadata": {
"dateUpdated": "2026-09-19T02:27:11.997Z",
"orgId": "b15e7b5b-3da4-40ae-a43c-f7aa60e62599",
"shortName": "Wordfence"
},
"references": [
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"url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/df28ecd7-d463-48b7-95e6-8adc9f34d6bd?source=cve"
},
{
"url": "https://plugins.trac.wordpress.org/browser/bp-better-messages/tags/2.15.33/inc/functions.php#L4155"
},
{
"url": "https://plugins.trac.wordpress.org/browser/bp-better-messages/tags/2.15.33/inc/chats.php#L2145"
},
{
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},
{
"url": "https://plugins.trac.wordpress.org/browser/bp-better-messages/tags/2.15.33/inc/chats.php#L2196"
},
{
"url": "https://plugins.trac.wordpress.org/browser/bp-better-messages/tags/2.15.33/inc/guests.php#L577"
},
{
"url": "https://plugins.trac.wordpress.org/browser/bp-better-messages/tags/2.15.33/inc/guests.php#L467"
},
{
"url": "https://plugins.trac.wordpress.org/browser/bp-better-messages/tags/2.15.33/inc/guests.php#L311"
},
{
"url": "https://plugins.trac.wordpress.org/changeset?old_path=bp-better-messages%2Ftags%2F2.15.33%2Finc%2Ffunctions.php\u0026new_path=bp-better-messages%2Ftags%2F3.0.0%2Finc%2Ffunctions.php"
}
],
"timeline": [
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"lang": "en",
"time": "2026-09-10T20:48:32.000Z",
"value": "Vendor Notified"
},
{
"lang": "en",
"time": "2026-09-18T13:53:09.000Z",
"value": "Disclosed"
}
],
"title": "Better Messages \u003c= 2.15.33 - Unauthenticated Information Exposure Spoofing via \u0027X-Real-IP\u0027 Header via /guests/register"
}
},
"cveMetadata": {
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"cveId": "CVE-2026-89093",
"datePublished": "2026-09-19T02:27:11.997Z",
"dateReserved": "2026-09-10T20:32:26.852Z",
"dateUpdated": "2026-09-19T02:27:11.997Z",
"state": "PUBLISHED"
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"dataType": "CVE_RECORD",
"dataVersion": "5.2",
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}
],
"id": "CVE-2026-89093",
"lastModified": "2026-09-19T03:17:16.443",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
"version": "3.1"
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"impactScore": 1.4,
"source": "security@wordfence.com",
"type": "Primary"
}
]
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"url": "https://plugins.trac.wordpress.org/browser/bp-better-messages/tags/2.15.33/inc/chats.php#L2145"
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"source": "security@wordfence.com",
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}
}
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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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