JVNDB-2025-000030
Vulnerability from jvndb - Published: 2025-05-12 09:00 - Updated:2025-07-17 01:06| Type | URL | ||||||||||
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{
"@rdf:about": "https://jvndb.jvn.jp/en/contents/2025/JVNDB-2025-000030.html",
"dc:date": "2025-07-17T10:06+09:00",
"dcterms:issued": "2025-05-12T18:00+09:00",
"dcterms:modified": "2025-07-17T10:06+09:00",
"description": "Web Image Monitor provided by Ricoh Company, Ltd. is an web server included and runs in laser printers and MFPs (multifunction printers).\r\nWeb Image Monitor contains the vulnerability listed below.\r\n\r\n* Reflected cross-site scripting (CWE-79) - CVE-2025-41393\r\n\r\nJuan Pablo Gomez Postigo of Sprocket Security, Niels Eris of HackDefense, and Vincent Theriault of Precicom Technologies Inc. reported this vulnerability to Ricoh Company, Ltd. directly and coordinated. After the coordination, Ricoh Company, Ltd. reported this case to IPA under Information Security Early Warning Partnership, and JPCERT/CC coordinated with Ricoh Company, Ltd. for JVN publication.",
"link": "https://jvndb.jvn.jp/en/contents/2025/JVNDB-2025-000030.html",
"sec:cpe": {
"#text": "cpe:/a:misc:multiple_vendors",
"@product": "(Multiple Products)",
"@vendor": "(Multiple Venders)",
"@version": "2.2"
},
"sec:cvss": {
"@score": "6.1",
"@severity": "Medium",
"@type": "Base",
"@vector": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N",
"@version": "3.0"
},
"sec:identifier": "JVNDB-2025-000030",
"sec:references": [
{
"#text": "https://jvn.jp/en/jp/JVN20474768/index.html",
"@id": "JVN#20474768",
"@source": "JVN"
},
{
"#text": "https://www.cve.org/CVERecord?id=CVE-2025-41393",
"@id": "CVE-2025-41393",
"@source": "CVE"
},
{
"#text": "https://www.ipa.go.jp/en/security/vulnerabilities/cwe.html",
"@id": "CWE-79",
"@title": "Cross-site Scripting(CWE-79)"
}
],
"title": "Reflected cross-site scripting vulnerability in multiple laser printers and MFPs which implement Ricoh Web Image Monitor"
}
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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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
How durations are calculated
Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.
Each result shows its source dates. A negative interval means the end event came first; when date-only inputs leave the order open, the result says so. Date-only inputs are approximate. The earliest evidence wins: KEV report dates and sightings are labelled as such. Records describing another vulnerability are listed but never calculated from, and a PoC alone does not establish exploitation. Missing patch evidence does not prove that no patch exists. Filters below change the event list only.
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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.