Vulnerability-Lookup

GHSA-CV56-R9M6-79RX

Vulnerability from github – Published: 2025-07-22 15:32 – Updated: 2025-07-22 18:30

Details

Stored Cross-Site Scripting (XSS) vulnerability in Chaindesk thru 2025-05-26 in its agent chat component. An attacker can achieve arbitrary client-side script execution by crafting an AI agent whose system prompt instructs the underlying Large Language Model (LLM) to embed malicious script payloads (e.g., SVG-based XSS) into its chat responses. When a user interacts with such a malicious agent or accesses a direct link to a conversation containing an XSS payload, the script executes in the user's browser. Successful exploitation can lead to the theft of sensitive information, such as JWT session tokens, potentially resulting in account hijacking.

Severity

6.5 (Medium)


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

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{
  "affected": [],
  "aliases": [
    "CVE-2025-51859"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-79"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-07-22T15:15:36Z",
    "severity": "MODERATE"
  },
  "details": "Stored Cross-Site Scripting (XSS) vulnerability in Chaindesk thru 2025-05-26 in its agent chat component. An attacker can achieve arbitrary client-side script execution by crafting an AI agent whose system prompt instructs the underlying Large Language Model (LLM) to embed malicious script payloads (e.g., SVG-based XSS) into its chat responses. When a user interacts with such a malicious agent or accesses a direct link to a conversation containing an XSS payload, the script executes in the user\u0027s browser. Successful exploitation can lead to the theft of sensitive information, such as JWT session tokens, potentially resulting in account hijacking.",
  "id": "GHSA-cv56-r9m6-79rx",
  "modified": "2025-07-22T18:30:41Z",
  "published": "2025-07-22T15:32:52Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-51859"
    },
    {
      "type": "WEB",
      "url": "https://github.com/Secsys-FDU/CVE-2025-51859"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2025-51859 (GCVE-0-2025-51859)

Vulnerability from cvelistv5 – Published: 2025-07-22 00:00 – Updated: 2025-07-22 15:26

Summary

Severity

6.5 (Medium)


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

SSVC

Exploitation: poc Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-07-22 15:21 UTC

CWE

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

Assigner

mitre CNA under the mitre root

CNA scorecard E 28/100 over 2340 records in the last 180 days details

References

1 reference

URL	Tags
https://github.com/Secsys-FDU/CVE-2025-51859

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{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "cvssV3_1": {
              "attackComplexity": "LOW",
              "attackVector": "NETWORK",
              "availabilityImpact": "NONE",
              "baseScore": 6.5,
              "baseSeverity": "MEDIUM",
              "confidentialityImpact": "HIGH",
              "integrityImpact": "NONE",
              "privilegesRequired": "NONE",
              "scope": "UNCHANGED",
              "userInteraction": "REQUIRED",
              "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
              "version": "3.1"
            }
          },
          {
            "other": {
              "content": {
                "id": "CVE-2025-51859",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-07-22T15:21:49.204368Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "problemTypes": [
          {
            "descriptions": [
              {
                "cweId": "CWE-79",
                "description": "CWE-79 Improper Neutralization of Input During Web Page Generation (\u0027Cross-site Scripting\u0027)",
                "lang": "en",
                "type": "CWE"
              }
            ]
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-07-22T15:26:08.741Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "n/a",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "n/a"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "Stored Cross-Site Scripting (XSS) vulnerability in Chaindesk thru 2025-05-26 in its agent chat component. An attacker can achieve arbitrary client-side script execution by crafting an AI agent whose system prompt instructs the underlying Large Language Model (LLM) to embed malicious script payloads (e.g., SVG-based XSS) into its chat responses. When a user interacts with such a malicious agent or accesses a direct link to a conversation containing an XSS payload, the script executes in the user\u0027s browser. Successful exploitation can lead to the theft of sensitive information, such as JWT session tokens, potentially resulting in account hijacking."
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "description": "n/a",
              "lang": "en",
              "type": "text"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2025-07-22T14:48:56.436Z",
        "orgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
        "shortName": "mitre"
      },
      "references": [
        {
          "url": "https://github.com/Secsys-FDU/CVE-2025-51859"
        }
      ]
    }
  },
  "cveMetadata": {
    "assignerOrgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
    "assignerShortName": "mitre",
    "cveId": "CVE-2025-51859",
    "datePublished": "2025-07-22T00:00:00.000Z",
    "dateReserved": "2025-06-16T00:00:00.000Z",
    "dateUpdated": "2025-07-22T15:26:08.741Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

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

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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.
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.

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