Vulnerability-Lookup

FKIE_CVE-2026-41318

Vulnerability from fkie_nvd - Published: 2026-04-24 04:16 - Updated: 2026-06-17 10:46

Severity

5.4 (Medium) - CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:L/A:N

Summary

AnythingLLM is an application that turns pieces of content into context that any LLM can use as references during chatting. Prior to version 1.12.1, AnythingLLM's in-chat markdown renderer has an unsafe custom rule for images that interpolates the markdown image's `alt` text into an HTML `alt="..."` attribute without any HTML encoding. Every call-site in the app wraps `renderMarkdown(...)` with `DOMPurify.sanitize(...)` as defense-in-depth — except the `Chartable` component, which renders chart captions with no sanitization. The chart caption is the natural-language text the LLM emits around a `create-chart` tool call, so any attacker who can influence the LLM's output — most cheaply via indirect prompt injection in a shared workspace document, or directly if they can create a chart record in a multi-user workspace — can trigger stored DOM-level XSS in every other user's browser when they open that conversation. AnythingLLM chat history is loaded server-side via `GET /api/workspace/:slug/chats` and rendered directly into the chat UI. Version 1.12.1 contains a patch for this issue.

References

URL	Tags
security-advisories@github.com	https://github.com/Mintplex-Labs/anything-llm/commit/f5fa03f4728e483949f6360093bc3ea1ef555535	Patch
security-advisories@github.com	https://github.com/Mintplex-Labs/anything-llm/security/advisories/GHSA-4q6m-qh3w-9gf5	Exploit, Vendor Advisory
134c704f-9b21-4f2e-91b3-4a467353bcc0	https://github.com/Mintplex-Labs/anything-llm/security/advisories/GHSA-4q6m-qh3w-9gf5	Exploit, Vendor Advisory

Impacted products

	Vendor	Product	Version
	mintplexlabs	anythingllm	*

JSON

To clipboard

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "anything-llm",
          "vendor": "Mintplex-Labs",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c 1.12.1"
            }
          ]
        }
      ],
      "source": "security-advisories@github.com"
    }
  ],
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:mintplexlabs:anythingllm:*:*:*:*:*:*:*:*",
              "matchCriteriaId": "94CAE6B1-A382-49BB-8EC4-A1AD6F2DF101",
              "versionEndExcluding": "1.12.1",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "AnythingLLM is an application that turns pieces of content into context that any LLM can use as references during chatting. Prior to version 1.12.1, AnythingLLM\u0027s in-chat markdown renderer has an unsafe custom rule for images that interpolates the markdown image\u0027s `alt` text into an HTML `alt=\"...\"` attribute without any HTML encoding. Every call-site in the app wraps `renderMarkdown(...)` with `DOMPurify.sanitize(...)` as defense-in-depth \u2014 except the `Chartable` component, which renders chart captions with no sanitization. The chart caption is the natural-language text the LLM emits around a `create-chart` tool call, so any attacker who can influence the LLM\u0027s output \u2014 most cheaply via indirect prompt injection in a shared workspace document, or directly if they can create a chart record in a multi-user workspace \u2014 can trigger stored DOM-level XSS in every other user\u0027s browser when they open that conversation. AnythingLLM chat history is loaded server-side via `GET /api/workspace/:slug/chats` and rendered directly into the chat UI. Version 1.12.1 contains a patch for this issue."
    }
  ],
  "id": "CVE-2026-41318",
  "lastModified": "2026-06-17T10:46:29.907",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "HIGH",
          "attackVector": "NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 5.4,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "LOW",
          "privilegesRequired": "LOW",
          "scope": "UNCHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:L/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 1.2,
        "impactScore": 4.2,
        "source": "security-advisories@github.com",
        "type": "Secondary"
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2026-41318",
          "options": [
            {
              "exploitation": "poc"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2026-04-24T17:24:46.472539Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2026-04-24T04:16:20.193",
  "references": [
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Patch"
      ],
      "url": "https://github.com/Mintplex-Labs/anything-llm/commit/f5fa03f4728e483949f6360093bc3ea1ef555535"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Exploit",
        "Vendor Advisory"
      ],
      "url": "https://github.com/Mintplex-Labs/anything-llm/security/advisories/GHSA-4q6m-qh3w-9gf5"
    },
    {
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "tags": [
        "Exploit",
        "Vendor Advisory"
      ],
      "url": "https://github.com/Mintplex-Labs/anything-llm/security/advisories/GHSA-4q6m-qh3w-9gf5"
    }
  ],
  "sourceIdentifier": "security-advisories@github.com",
  "vulnStatus": "Analyzed",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-79"
        },
        {
          "lang": "en",
          "value": "CWE-116"
        },
        {
          "lang": "en",
          "value": "CWE-1336"
        }
      ],
      "source": "security-advisories@github.com",
      "type": "Secondary"
    }
  ]
}

CVE-2026-41318 (GCVE-0-2026-41318)

Vulnerability from cvelistv5 – Published: 2026-04-24 02:57 – Updated: 2026-04-24 18:17

Title

AnythingLLM vulnerable to stored DOM XSS in chart caption renderer - LLM-driven prompt injection produces executable HTML via unsanitized renderMarkdown(content.caption) in Chartable component

Summary

Severity

5.4 (Medium)


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

SSVC

Exploitation: poc Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-04-24 17:24 UTC

CWE

CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
CWE-116 - Improper Encoding or Escaping of Output
CWE-1336 - Improper Neutralization of Special Elements Used in a Template Engine

Assigner

GitHub_M mitre root

References

2 references

URL	Tags
https://github.com/Mintplex-Labs/anything-llm/sec…	x_refsource_CONFIRM
https://github.com/Mintplex-Labs/anything-llm/com…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
Mintplex-Labs	anything-llm	Affected: < 1.12.1

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2026-41318",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-04-24T17:24:46.472539Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2026-04-24T18:17:42.185Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "references": [
          {
            "tags": [
              "exploit"
            ],
            "url": "https://github.com/Mintplex-Labs/anything-llm/security/advisories/GHSA-4q6m-qh3w-9gf5"
          }
        ],
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "anything-llm",
          "vendor": "Mintplex-Labs",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c 1.12.1"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "AnythingLLM is an application that turns pieces of content into context that any LLM can use as references during chatting. Prior to version 1.12.1, AnythingLLM\u0027s in-chat markdown renderer has an unsafe custom rule for images that interpolates the markdown image\u0027s `alt` text into an HTML `alt=\"...\"` attribute without any HTML encoding. Every call-site in the app wraps `renderMarkdown(...)` with `DOMPurify.sanitize(...)` as defense-in-depth \u2014 except the `Chartable` component, which renders chart captions with no sanitization. The chart caption is the natural-language text the LLM emits around a `create-chart` tool call, so any attacker who can influence the LLM\u0027s output \u2014 most cheaply via indirect prompt injection in a shared workspace document, or directly if they can create a chart record in a multi-user workspace \u2014 can trigger stored DOM-level XSS in every other user\u0027s browser when they open that conversation. AnythingLLM chat history is loaded server-side via `GET /api/workspace/:slug/chats` and rendered directly into the chat UI. Version 1.12.1 contains a patch for this issue."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "HIGH",
            "attackVector": "NETWORK",
            "availabilityImpact": "NONE",
            "baseScore": 5.4,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "LOW",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "REQUIRED",
            "vectorString": "CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:L/A:N",
            "version": "3.1"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-79",
              "description": "CWE-79: Improper Neutralization of Input During Web Page Generation (\u0027Cross-site Scripting\u0027)",
              "lang": "en",
              "type": "CWE"
            }
          ]
        },
        {
          "descriptions": [
            {
              "cweId": "CWE-116",
              "description": "CWE-116: Improper Encoding or Escaping of Output",
              "lang": "en",
              "type": "CWE"
            }
          ]
        },
        {
          "descriptions": [
            {
              "cweId": "CWE-1336",
              "description": "CWE-1336: Improper Neutralization of Special Elements Used in a Template Engine",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2026-04-24T02:57:16.193Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "name": "https://github.com/Mintplex-Labs/anything-llm/security/advisories/GHSA-4q6m-qh3w-9gf5",
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/Mintplex-Labs/anything-llm/security/advisories/GHSA-4q6m-qh3w-9gf5"
        },
        {
          "name": "https://github.com/Mintplex-Labs/anything-llm/commit/f5fa03f4728e483949f6360093bc3ea1ef555535",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/Mintplex-Labs/anything-llm/commit/f5fa03f4728e483949f6360093bc3ea1ef555535"
        }
      ],
      "source": {
        "advisory": "GHSA-4q6m-qh3w-9gf5",
        "discovery": "UNKNOWN"
      },
      "title": "AnythingLLM vulnerable to stored DOM XSS in chart caption renderer - LLM-driven prompt injection produces executable HTML via unsanitized renderMarkdown(content.caption) in Chartable component"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2026-41318",
    "datePublished": "2026-04-24T02:57:16.193Z",
    "dateReserved": "2026-04-20T14:01:46.671Z",
    "dateUpdated": "2026-04-24T18:17:42.185Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2"
}

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.