Vulnerability-Lookup

GHSA-7JGX-WX3X-3FP3

Vulnerability from github – Published: 2026-04-24 21:32 – Updated: 2026-04-28 18:30

Details

CyberPanel versions prior to 2.4.4 contain a stored cross-site scripting vulnerability in the AI Scanner dashboard where the POST /api/ai-scanner/callback endpoint lacks authentication and allows unauthenticated attackers to inject malicious JavaScript by overwriting the findings_json field of ScanHistory records. Attackers can inject JavaScript that executes in an administrator's authenticated session when they visit the AI Scanner dashboard, allowing them to issue same-origin requests to plant cron jobs and achieve remote code execution on the server.

Severity

6.1 (Medium)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N

5.3 (Medium)


                  
                    CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:N/VI:N/VA:N/SC:H/SI:H/SA:N

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JSON

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{
  "affected": [],
  "aliases": [
    "CVE-2026-41472"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-79"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-04-24T21:16:18Z",
    "severity": "MODERATE"
  },
  "details": "CyberPanel versions prior to\u00a02.4.4 contain a stored cross-site scripting vulnerability in the AI Scanner dashboard where the POST /api/ai-scanner/callback endpoint lacks authentication and allows unauthenticated attackers to inject malicious JavaScript by overwriting the findings_json field of ScanHistory records. Attackers can inject JavaScript that executes in an administrator\u0027s authenticated session when they visit the AI Scanner dashboard, allowing them to issue same-origin requests to plant cron jobs and achieve remote code execution on the server.",
  "id": "GHSA-7jgx-wx3x-3fp3",
  "modified": "2026-04-28T18:30:30Z",
  "published": "2026-04-24T21:32:02Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-41472"
    },
    {
      "type": "WEB",
      "url": "https://github.com/usmannasir/cyberpanel/commit/0a099b1b193946555fbdd387a28486b1521f9961"
    },
    {
      "type": "WEB",
      "url": "https://itsrez.re/post/cyberpanel-rce"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/cyberpanel-stored-xss-via-ai-scanner-dashboard"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:N/VI:N/VA:N/SC:H/SI:H/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",
      "type": "CVSS_V4"
    }
  ]
}

CVE-2026-41472 (GCVE-0-2026-41472)

Vulnerability from cvelistv5 – Published: 2026-04-24 20:40 – Updated: 2026-08-11 17:35

Title

CyberPanel < 2.4.5 Stored XSS via AI Scanner Dashboard

Summary

CyberPanel versions prior to 2.4.5 contain a stored cross-site scripting vulnerability in the AI Scanner dashboard where the POST /api/ai-scanner/callback endpoint lacks authentication and allows unauthenticated attackers to inject malicious JavaScript by overwriting the findings_json field of ScanHistory records. Attackers can inject JavaScript that executes in an administrator's authenticated session when they visit the AI Scanner dashboard, allowing them to issue same-origin requests to plant cron jobs and achieve remote code execution on the server.

Severity

5.3 (Medium)


                        
                          CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:N/VI:N/VA:N/SC:H/SI:H/SA:N

SSVC

Exploitation: poc Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-04-27 13:37 UTC

CWE

CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')

Assigner

VulnCheck mitre root

References

3 references

URL	Tags
https://itsrez.re/post/cyberpanel-rce	technical-descriptionexploit
https://github.com/usmannasir/cyberpanel/commit/8…	patch
https://www.vulncheck.com/advisories/cyberpanel-s…	third-party-advisory

Impacted products

1 product

Vendor	Product	Version
usmannasir	cyberpanel	Affected: 0 , < 2.4.5 (semver) Unaffected: 8eb29181cb137baa4adb4bba5dce60f601d55a5f (git) cpe:2.3:a:cyberpanel:cyberpanel::::::::

Date Public

2026-01-18 00:00

Credits

Djibril Mounkoro

Show details on NVD website

JSON

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  "containers": {
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        "metrics": [
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                "id": "CVE-2026-41472",
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                  },
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                "role": "CISA Coordinator",
                "timestamp": "2026-04-27T13:37:10.501228Z",
                "version": "2.0.3"
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          "shortName": "CISA-ADP"
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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.

Detection rules are retrieved from Rulezet.

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.

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.