Vulnerability · CVE-2026-41279
Flowise is a drag & drop user interface to build a customized large language model flow.
Published Apr 23, 2026 · corrected/updated Jun 17, 2026 · flowiseai flowise · evidence confidence high
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the text-to-speech generation endpoint (POST /api/v1/text-to-speech/generate) is whitelisted (no auth) and accepts a credentialId directly in the request body. When called without a chatflowId, the endpoint uses the provided credentialId to decrypt the stored credential (e.g., OpenAI or ElevenLabs API key) and generate speech. This vulnerability is fixed in 3.1.0.
Grounded briefings
Catalog interpretations for three audiences. Each brief cites ingested metadata and the original advisories below. They are not independent research and they do not invent exploit steps.
Executive
CVE-2026-41279 is a high public vulnerability record for flowiseai flowise. It is not currently listed in the CISA Known Exploited catalog. Check the linked vendor or CERT advisories for patch status. This summary is a catalog interpretation of the ingested metadata and cites the original advisories below.
System administrator
Identify whether flowiseai flowise is in your estate, then compare installed versions with the affected ranges. Affected packages or ranges on record: flowiseai/flowise. Check the linked vendor or CERT advisories for patch status. Prefer the vendor or distribution advisory linked in Sources before changing production systems. This is a catalog interpretation, not a runbook.
Security analyst
Signals on file: CVSS 8.2, EPSS 0.4%. It is not currently listed in the CISA Known Exploited catalog. Weakness classes: CWE-639. Sources contributing to this record: cve_org, epss, nvd. Public exploit references, when present, are outbound links only and are not proof of active exploitation. This is a catalog interpretation of stored metadata.
Exploitation and remediation
Exploitation evidence
Not listed as known exploited in CISA KEV. Not in CISA KEV or VulnCheck KEV.
Patch and remediation
No required-action text is stored yet. Use the vendor or CERT links in Sources for patch availability.
Safe detection guidance
Compare installed versions with the affected ranges below and verify the advisory from the original publisher. This site stores metadata and outbound links only; it does not ship exploit code or proof-of-concept payloads.
Code
The project this record applies to. Exploit listings stay in References.
No public source repository is identified for this product.
Timeline
Detection, updates, and resolution for this record.
Apr 23, 2026 · NIST NVD
Detected
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the text-to-speech generation endpoint (POST /api/v1/text-to-speech/generate) is whitelisted (no auth) and accepts a credentialId directly in the request body. When called without a chatflowId, the endpoint uses the provided credentialId to decrypt the stored credential (e.g., OpenAI or ElevenL
Jun 17, 2026 · NIST NVD
Updated
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the text-to-speech generation endpoint (POST /api/v1/text-to-speech/generate) is whitelisted (no auth) and accepts a credentialId directly in the request body. When called without a chatflowId, the endpoint uses the provided credentialId to decrypt the stored credential (e.g., OpenAI or ElevenL
Affected
- cpe flowiseai/flowiseversion unspecified
Sources
- CVE.orgVulnerability recordCVE-2026-41279
Official CVE identifier
cve.org - FIRST EPSSExploitation probabilityCVE-2026-41279
30-day exploitation probability 0.4%
first.org - NIST NVDVulnerability recordCVE-2026-41279
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the text-to-speech generation endpoint (POST /api/v1/text-to-speech/generate) is whitelisted (no auth) and accepts a credentialId directly in the request body. When called wit
nvd.nist.gov