FKIE_CVE-2026-25535
Vulnerability from fkie_nvd - Published: 2026-02-19 15:16 - Updated: 2026-08-18 12:17
Severity
7.5 (High) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
7.5 (High) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
7.5 (High) - CVSS:3.1/
Summary
jsPDF is a library to generate PDFs in JavaScript. Prior to 4.2.0, user control of the first argument of the `addImage` method results in denial of service. If given the possibility to pass unsanitized image data or URLs to the `addImage` method, a user can provide a harmful GIF file that results in out of memory errors and denial of service. Harmful GIF files have large width and/or height entries in their headers, which lead to excessive memory allocation. Other affected methods are: `html`. The vulnerability has been fixed in jsPDF 4.2.0. As a workaround, sanitize image data or URLs before passing it to the addImage method or one of the other affected methods.
References
{
"affected": [
{
"affectedData": [
{
"product": "jsPDF",
"vendor": "parallax",
"versions": [
{
"status": "affected",
"version": "\u003c 4.2.0"
}
]
}
],
"source": "security-advisories@github.com"
},
{
"affectedData": [
{
"collectionURL": "https://catalog.redhat.com/software/containers/",
"cpes": [
"cpe:/a:redhat:advanced_cluster_security:4.8::el8"
],
"defaultStatus": "affected",
"packageName": "advanced-cluster-security/rhacs-main-rhel8",
"product": "Red Hat Advanced Cluster Security 4.8",
"vendor": "Red Hat",
"versions": [
{
"lessThan": "*",
"status": "unaffected",
"version": "1775594119",
"versionType": "rpm"
}
]
},
{
"collectionURL": "https://catalog.redhat.com/software/containers/",
"cpes": [
"cpe:/a:redhat:advanced_cluster_security:4.9::el8"
],
"defaultStatus": "affected",
"packageName": "advanced-cluster-security/rhacs-main-rhel8",
"product": "Red Hat Advanced Cluster Security 4.9",
"vendor": "Red Hat",
"versions": [
{
"lessThan": "*",
"status": "unaffected",
"version": "1775594284",
"versionType": "rpm"
}
]
}
],
"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:parall:jspdf:*:*:*:*:*:node.js:*:*",
"matchCriteriaId": "7EACE56E-B77C-421B-AAFE-F5FD3C80FE94",
"versionEndExcluding": "4.2.0",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "jsPDF is a library to generate PDFs in JavaScript. Prior to 4.2.0, user control of the first argument of the `addImage` method results in denial of service. If given the possibility to pass unsanitized image data or URLs to the `addImage` method, a user can provide a harmful GIF file that results in out of memory errors and denial of service. Harmful GIF files have large width and/or height entries in their headers, which lead to excessive memory allocation. Other affected methods are: `html`. The vulnerability has been fixed in jsPDF 4.2.0. As a workaround, sanitize image data or URLs before passing it to the addImage method or one of the other affected methods."
},
{
"lang": "es",
"value": "jsPDF es una librer\u00eda para generar PDFs en JavaScript. Anteriormente a la 4.2.0, el control del usuario sobre el primer argumento del m\u00e9todo \u0027addImage\u0027 resulta en denegaci\u00f3n de servicio. Si se le da la posibilidad de pasar datos de imagen o URLs no saneados al m\u00e9todo \u0027addImage\u0027, un usuario puede proporcionar un archivo GIF malicioso que resulta en errores de falta de memoria y denegaci\u00f3n de servicio. Los archivos GIF maliciosos tienen entradas de ancho y/o alto grandes en sus cabeceras, lo que lleva a una asignaci\u00f3n excesiva de memoria. Otros m\u00e9todos afectados son: \u0027html\u0027. La vulnerabilidad ha sido corregida en jsPDF 4.2.0. Como soluci\u00f3n alternativa, sanee los datos de imagen o las URLs antes de pasarlos al m\u00e9todo addImage o a uno de los otros m\u00e9todos afectados."
}
],
"id": "CVE-2026-25535",
"lastModified": "2026-08-18T12:17:45.263",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6,
"source": "nvd@nist.gov",
"type": "Primary"
},
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6,
"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
"type": "Secondary"
}
],
"cvssMetricV40": [
{
"cvssData": {
"Automatable": "NOT_DEFINED",
"Recovery": "NOT_DEFINED",
"Safety": "NOT_DEFINED",
"attackComplexity": "LOW",
"attackRequirements": "NONE",
"attackVector": "NETWORK",
"availabilityRequirement": "NOT_DEFINED",
"baseScore": 8.7,
"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:N/VI:N/VA:H/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": "HIGH",
"vulnConfidentialityImpact": "NONE",
"vulnIntegrityImpact": "NONE",
"vulnerabilityResponseEffort": "NOT_DEFINED"
},
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-25535",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "yes"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-02-19T16:03:04.920714Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-02-19T15:16:12.130",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Exploit",
"Third Party Advisory"
],
"url": "https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-25535.md"
},
{
"source": "security-advisories@github.com",
"tags": [
"Patch"
],
"url": "https://github.com/parallax/jsPDF/commit/2e5e156e284d92c7d134bce97e6418756941d5e6"
},
{
"source": "security-advisories@github.com",
"tags": [
"Release Notes"
],
"url": "https://github.com/parallax/jsPDF/releases/tag/v4.2.0"
},
{
"source": "security-advisories@github.com",
"tags": [
"Vendor Advisory"
],
"url": "https://github.com/parallax/jsPDF/security/advisories/GHSA-67pg-wm7f-q7fj"
},
{
"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
"url": "https://access.redhat.com/errata/RHSA-2026:7110"
},
{
"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
"url": "https://access.redhat.com/errata/RHSA-2026:7128"
},
{
"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
"url": "https://access.redhat.com/security/cve/CVE-2026-25535"
},
{
"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2440992"
},
{
"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-25535.json"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-400"
},
{
"lang": "en",
"value": "CWE-770"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
},
{
"description": [
{
"lang": "en",
"value": "CWE-770"
}
],
"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
"type": "Secondary"
}
]
}
Loading…
Loading…
Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
Loading timeline…
Loading…
Loading…
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.
Loading…
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.