FKIE_CVE-2026-43900
Vulnerability from fkie_nvd - Published: 2026-05-11 23:20 - Updated: 2026-10-26 18:10
Severity
Summary
DeepChat is an open-source artificial intelligence agent platform that unifies models, tools, and agents. Prior to v1.0.4-beta.1, a Cross-Site Scripting (XSS) vulnerability exists due to a discrepancy between the backend validation layer and the frontend browser rendering engine. The SVGSanitizer (src/main/lib/svgSanitizer.ts) restricts script execution by scrubbing javascript: protocols using plain-text regular expressions. However, it fails to account for HTML entity decoding prior to Vue's v-html DOM insertion inside the SvgArtifact.vue component. By feeding an SVG artifact with obfuscated entities (e.g., javascript:alert(1)), an attacker can completely bypass the sanitizer, culminating in arbitrary JavaScript execution when a victim interacts with the rendered SVG Element. This vulnerability is fixed in v1.0.4-beta.1.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "deepchat",
"vendor": "ThinkInAIXYZ",
"versions": [
{
"status": "affected",
"version": "\u003c 1.0.4-beta.1"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "DeepChat is an open-source artificial intelligence agent platform that unifies models, tools, and agents. Prior to v1.0.4-beta.1, a Cross-Site Scripting (XSS) vulnerability exists due to a discrepancy between the backend validation layer and the frontend browser rendering engine. The SVGSanitizer (src/main/lib/svgSanitizer.ts) restricts script execution by scrubbing javascript: protocols using plain-text regular expressions. However, it fails to account for HTML entity decoding prior to Vue\u0027s v-html DOM insertion inside the SvgArtifact.vue component. By feeding an SVG artifact with obfuscated entities (e.g., j\u0026#x61;vascript:alert(1)), an attacker can completely bypass the sanitizer, culminating in arbitrary JavaScript execution when a victim interacts with the rendered SVG Element. This vulnerability is fixed in v1.0.4-beta.1."
},
{
"lang": "es",
"value": "DeepChat es una plataforma de agente de inteligencia artificial de c\u00f3digo abierto que unifica modelos, herramientas y agentes. Antes de la v1.0.4-beta.1, existe una vulnerabilidad de cross-site scripting (XSS) debido a una discrepancia entre la capa de validaci\u00f3n del backend y el motor de renderizado del navegador del frontend. El SVGSanitizer (src/main/lib/svgSanitizer.ts) restringe la ejecuci\u00f3n de scripts eliminando los protocolos javascript_disabled: usando expresiones regulares de texto plano. Sin embargo, no tiene en cuenta la decodificaci\u00f3n de entidades HTML antes de la inserci\u00f3n en el DOM de v-html de Vue dentro del componente SvgArtifact.vue. Al alimentar un artefacto SVG con entidades ofuscadas (p. ej., j\u0026#x61;vascript:alert(1)), un atacante puede eludir completamente el saneador, culminando en la ejecuci\u00f3n arbitraria de JavaScript cuando una v\u00edctima interact\u00faa con el elemento SVG renderizado. Esta vulnerabilidad est\u00e1 corregida en la v1.0.4-beta.1."
}
],
"id": "CVE-2026-43900",
"lastModified": "2026-10-26T18:10:00.173",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 9.3,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:N",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 5.8,
"source": "security-advisories@github.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-43900",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "no"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-05-12T13:18:13.480684Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-05-11T23:20:21.557",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/ThinkInAIXYZ/deepchat/security/advisories/GHSA-7r59-67v3-3mgp"
},
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"url": "https://github.com/ThinkInAIXYZ/deepchat/security/advisories/GHSA-7r59-67v3-3mgp"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-79"
}
],
"source": "security-advisories@github.com",
"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.