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CVE-2026-70477

Flowise is a drag & drop user interface to build a customized large language model flow.

Published Aug 4, 2026CWE-94EPSS 0.81%

Overview

CVE-2026-70477 is a known-severity vulnerability. It was published on August 4, 2026.

Technical description

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, a prompt injection sent to a chatflow using a CSV Agent node can cause the LLM to respond with a malicious Python script that bypasses the blocklist validator and executes in an unsandboxed Pyodide environment. The specific flaw exists within the run method of the CSV_Agents class, where untrusted data is used to construct an LLM prompt and the resulting pythonCode is validated by validatePythonCodeForDataFrame before execution. An attacker can leverage this to execute arbitrary code in the context of the service account. This issue is fixed in 3.1.3.

Remediation

Check the references section for vendor advisories, patches, and mitigation guidance. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.

Frequently asked questions

What is CVE-2026-70477?

CVE-2026-70477 is a known-severity vulnerability. It was published on August 4, 2026.

How severe is CVE-2026-70477?

CVSS score information is not yet available for this vulnerability. Check back as the CVE record is updated by NVD analysts.

How do I fix or remediate CVE-2026-70477?

Check the references section for vendor advisories, patches, and mitigation guidance. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.

How can CyberStrike help with CVE-2026-70477?

CyberStrike is an open-source, AI-augmented pentesting engine. Rather than flag a version number, it tests whether an issue like CVE-2026-70477 is actually reachable in your own applications and APIs, then verifies each finding before reporting it. That tells you if the weakness is a real, exploitable risk in your environment or a false positive you can safely deprioritize.