FKIE_CVE-2018-25433
Vulnerability from fkie_nvd - Published: 2026-06-01 22:16 - Updated: 2026-07-22 08:10
Severity
Summary
Joomla Component JE Photo Gallery 1.1 contains an SQL injection vulnerability that allows unauthenticated attackers to extract database information by injecting malicious SQL code through the categoryid parameter. Attackers can send GET requests to index.php with crafted categoryid values in the com_jephotogallery component to execute arbitrary SQL queries and retrieve sensitive data like usernames and password hashes.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "JE Photo Gallery",
"vendor": "Joomlaextensions",
"versions": [
{
"status": "affected",
"version": "1.1"
}
]
}
],
"source": "disclosure@vulncheck.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Joomla Component JE Photo Gallery 1.1 contains an SQL injection vulnerability that allows unauthenticated attackers to extract database information by injecting malicious SQL code through the categoryid parameter. Attackers can send GET requests to index.php with crafted categoryid values in the com_jephotogallery component to execute arbitrary SQL queries and retrieve sensitive data like usernames and password hashes."
},
{
"lang": "es",
"value": "El Componente Joomla JE Photo Gallery 1.1 contiene una vulnerabilidad de inyecci\u00f3n SQL que permite a atacantes no autenticados extraer informaci\u00f3n de la base de datos inyectando c\u00f3digo SQL malicioso a trav\u00e9s del par\u00e1metro categoryid. Los atacantes pueden enviar solicitudes GET a index.php con valores categoryid manipulados en el componente com_jephotogallery para ejecutar consultas SQL arbitrarias y recuperar datos sensibles como nombres de usuario y hashes de contrase\u00f1a."
}
],
"id": "CVE-2018-25433",
"lastModified": "2026-07-22T08:10:00.117",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 8.2,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 4.2,
"source": "disclosure@vulncheck.com",
"type": "Secondary"
}
],
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityRequirement": "NOT_DEFINED",
"exploitMaturity": "NOT_DEFINED",
"integrityRequirement": "NOT_DEFINED",
"modifiedAttackComplexity": "NOT_DEFINED",
"modifiedAttackRequirements": "NOT_DEFINED",
"modifiedAttackVector": "NOT_DEFINED",
"modifiedPrivilegesRequired": "NOT_DEFINED",
"modifiedSubAvailabilityImpact": "NOT_DEFINED",
"modifiedSubConfidentialityImpact": "NOT_DEFINED",
"modifiedSubIntegrityImpact": "NOT_DEFINED",
"modifiedUserInteraction": "NOT_DEFINED",
"modifiedVulnAvailabilityImpact": "NOT_DEFINED",
"modifiedVulnConfidentialityImpact": "NOT_DEFINED",
"modifiedVulnIntegrityImpact": "NOT_DEFINED",
"privilegesRequired": "NONE",
"providerUrgency": "NOT_DEFINED",
"subAvailabilityImpact": "NONE",
"subConfidentialityImpact": "NONE",
"subIntegrityImpact": "NONE",
"userInteraction": "NONE",
"valueDensity": "NOT_DEFINED",
"vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:L/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
"version": "4.0",
"vulnAvailabilityImpact": "NONE",
"vulnConfidentialityImpact": "HIGH",
"vulnIntegrityImpact": "LOW",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "disclosure@vulncheck.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2018-25433",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "yes"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-06-02T13:13:44.192991Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-06-01T22:16:16.713",
"references": [
{
"source": "disclosure@vulncheck.com",
"url": "http://joomlaextensions.co.in/download/1387375463_JE%20PhotoGallery%20(%20J-%203.0%20).zip"
},
{
"source": "disclosure@vulncheck.com",
"url": "https://joomlaextensions.co.in"
},
{
"source": "disclosure@vulncheck.com",
"url": "https://www.exploit-db.com/exploits/45930"
},
{
"source": "disclosure@vulncheck.com",
"url": "https://www.vulncheck.com/advisories/joomla-je-photo-gallery-sql-injection-via-categoryid"
}
],
"sourceIdentifier": "disclosure@vulncheck.com",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-89"
}
],
"source": "disclosure@vulncheck.com",
"type": "Secondary"
}
]
}
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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.
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