Snyk has a proof-of-concept or detailed explanation of how to exploit this vulnerability.
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
In a few clicks we can analyze your entire application and see what components are vulnerable in your application, and suggest you quick fixes.
Test your applicationsUpgrade flowise to version 3.1.0 or higher.
flowise is a Flowiseai Server
Affected versions of this package are vulnerable to Insertion of Sensitive Information Into Sent Data via the getSinglePublicChatflow handler in chatflows/index.ts. An attacker can retrieve sensitive flow configuration by requesting a public chatflow and reading the returned flowData payload. The exposed flowData can include node inputs and embedded credentials or authorization headers from the chatflow definition, allowing unauthenticated users to learn secrets used by the public flow.
Workarounds
GET /api/v1/public-chatflows/:id or the public chatbot config endpoint and retrieve raw flowData containing plaintext API keys, passwords, and credential IDs.