CVE-2026-76798 (GCVE-0-2026-76798)
Vulnerability from cvelistv5 – Published: 2026-08-28 19:24 – Updated: 2026-08-28 19:24
VLAI
EPSS
VEX
Title
MongoSQL Transition Readiness Tool Improper Output Encoding in Generated HTML Reports
Summary
The MongoSQL Transition Readiness Tool writes query text and user names read from BI Connector log files into its generated HTML report without encoding them for that output context. A user able to issue queries through the BI Connector can influence log content so that markup supplied in a query is interpreted by the browser when an operator later generates and opens the report, which may disclose other users' logged query text and user names to an external party or present misleading content to the operator. Generating a report over logs containing the affected entries and opening that report in a browser is required.
Severity
6.3 (Medium)
CWE
- CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
1 reference
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| MongoDB | BI Connector Transition Readiness Report |
Affected:
1.0.0 , < 1.1.3
(semver)
|
guessed |
{
"containers": {
"cna": {
"affected": [
{
"defaultStatus": "unaffected",
"product": "BI Connector Transition Readiness Report",
"vendor": "MongoDB",
"versions": [
{
"lessThan": "1.1.3",
"status": "affected",
"version": "1.0.0",
"versionType": "semver"
}
]
}
],
"descriptions": [
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"supportingMedia": [
{
"base64": false,
"type": "text/html",
"value": "The MongoSQL Transition Readiness Tool writes query text and user names read from BI Connector log files into its generated HTML report without encoding them for that output context. A user able to issue queries through the BI Connector can influence log content so that markup supplied in a query is interpreted by the browser when an operator later generates and opens the report, which may disclose other users\u0027 logged query text and user names to an external party or present misleading content to the operator. Generating a report over logs containing the affected entries and opening that report in a browser is required."
}
],
"value": "The MongoSQL Transition Readiness Tool writes query text and user names read from BI Connector log files into its generated HTML report without encoding them for that output context. A user able to issue queries through the BI Connector can influence log content so that markup supplied in a query is interpreted by the browser when an operator later generates and opens the report, which may disclose other users\u0027 logged query text and user names to an external party or present misleading content to the operator. Generating a report over logs containing the affected entries and opening that report in a browser is required."
}
],
"metrics": [
{
"cvssV4_0": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"baseScore": 6.9,
"baseSeverity": "MEDIUM",
"exploitMaturity": "NOT_DEFINED",
"privilegesRequired": "LOW",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "ACTIVE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:A/VC:H/VI:L/VA:N/SC:N/SI:N/SA:N",
"version": "4.0",
"vulnAvailabilityImpact": "NONE",
"vulnConfidentialityImpact": "HIGH",
"vulnIntegrityImpact": "LOW",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"format": "CVSS",
"scenarios": [
{
"lang": "en",
"value": "GENERAL"
}
]
},
{
"cvssV3_1": {
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"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 6.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "HIGH",
"integrityImpact": "LOW",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:L/A:N",
"version": "3.1"
},
"format": "CVSS",
"scenarios": [
{
"lang": "en",
"value": "GENERAL"
}
]
}
],
"problemTypes": [
{
"descriptions": [
{
"cweId": "CWE-79",
"description": "CWE-79: Improper Neutralization of Input During Web Page Generation (\u0027Cross-site Scripting\u0027)",
"lang": "en",
"type": "CWE"
}
]
}
],
"providerMetadata": {
"dateUpdated": "2026-08-28T19:24:46.039Z",
"orgId": "a39b4221-9bd0-4244-95fc-f3e2e07f1deb",
"shortName": "mongodb"
},
"references": [
{
"url": "https://www.mongodb.com/docs/sql-interface/changelog/"
}
],
"source": {
"discovery": "INTERNAL"
},
"title": "MongoSQL Transition Readiness Tool Improper Output Encoding in Generated HTML Reports",
"x_generator": {
"engine": "Vulnogram 1.0.5"
}
}
},
"cveMetadata": {
"assignerOrgId": "a39b4221-9bd0-4244-95fc-f3e2e07f1deb",
"assignerShortName": "mongodb",
"cveId": "CVE-2026-76798",
"datePublished": "2026-08-28T19:24:46.039Z",
"dateReserved": "2026-08-19T19:18:12.867Z",
"dateUpdated": "2026-08-28T19:24:46.039Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.2",
"vulnerability-lookup:meta": {
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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.
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.
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