GHSA-7G73-99R4-M4MJ

Vulnerability from github – Published: 2026-05-14 14:58 – Updated: 2026-06-09 13:10
VLAI
Summary
FlowiseAI Vulnerable to Credential Data Leak
Details

Severity: HIGH (CVSS ~7.5) Type: CWE-200 (Exposure of Sensitive Information) File: packages/server/src/services/credentials/index.ts:62-71

Description: When credentials are fetched with a credentialName filter parameter, the encryptedData field is NOT stripped from the response. The code properly omits encryptedData when NO filter is used (line 102) but fails to do so when a filter IS used (lines 62-63, 70-71). Credential Data Leak Evidence:

// Lines 62-63: WITH filter - encryptedData LEAKED
const credentials = await appServer.AppDataSource.getRepository(Credential).findBy(searchOptions)
dbResponse.push(...credentials)  // encryptedData NOT removed!

// Lines 100-102: WITHOUT filter - encryptedData properly omitted
for (const credential of credentials) {
    dbResponse.push(omit(credential, ['encryptedData']))  // Correctly omitted
}

Impact: Authenticated users can extract encrypted credential data (API keys, passwords, tokens for services like OpenAI, AWS, etc.). Combined with access to the encryption key file (~/.flowise/encryption.key written with default permissions), this enables full credential theft.

Reproduction:

curl https://TARGET/api/v1/credentials?credentialName=openAIApi \
  -H "Authorization: Bearer API_KEY"
# Response includes encryptedData field with AES-encrypted credentials
Severity
7.0 (High)
CVSS:4.0/AV:N/AC:H/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:H/SI:N/SA:N
Show details on source website
To clipboard 

{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 3.1.1"
      },
      "package": {
        "ecosystem": "npm",
        "name": "flowise"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.1.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-46443"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-200"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-05-14T14:58:12Z",
    "nvd_published_at": "2026-06-08T16:16:41Z",
    "severity": "HIGH"
  },
  "details": "**Severity**: HIGH (CVSS ~7.5)\n**Type**: CWE-200 (Exposure of Sensitive Information)\n**File**: `packages/server/src/services/credentials/index.ts:62-71`\n\n**Description**: When credentials are fetched with a `credentialName` filter parameter, the `encryptedData` field is NOT stripped from the response. The code properly omits `encryptedData` when NO filter is used (line 102) but fails to do so when a filter IS used (lines 62-63, 70-71).\nCredential Data Leak\n**Evidence**:\n```typescript\n// Lines 62-63: WITH filter - encryptedData LEAKED\nconst credentials = await appServer.AppDataSource.getRepository(Credential).findBy(searchOptions)\ndbResponse.push(...credentials)  // encryptedData NOT removed!\n\n// Lines 100-102: WITHOUT filter - encryptedData properly omitted\nfor (const credential of credentials) {\n    dbResponse.push(omit(credential, [\u0027encryptedData\u0027]))  // Correctly omitted\n}\n```\n\n**Impact**: Authenticated users can extract encrypted credential data (API keys, passwords, tokens for services like OpenAI, AWS, etc.). Combined with access to the encryption key file (`~/.flowise/encryption.key` written with default permissions), this enables full credential theft.\n\n**Reproduction**:\n```bash\ncurl https://TARGET/api/v1/credentials?credentialName=openAIApi \\\n  -H \"Authorization: Bearer API_KEY\"\n# Response includes encryptedData field with AES-encrypted credentials\n```",
  "id": "GHSA-7g73-99r4-m4mj",
  "modified": "2026-06-09T13:10:23Z",
  "published": "2026-05-14T14:58:12Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-7g73-99r4-m4mj"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-46443"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/FlowiseAI/Flowise"
    },
    {
      "type": "WEB",
      "url": "https://github.com/FlowiseAI/Flowise/releases/tag/flowise%403.1.2"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:4.0/AV:N/AC:H/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:H/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "FlowiseAI Vulnerable to Credential Data Leak"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.





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.



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.