CVE-2026-73487
Received Received - Intake

Flowise Code Validator Bypass via Prompt Injection

Publication date: 2026-08-13

Last updated on: 2026-08-13

Assigner: VulnCheck

Description
Flowise before 3.1.3 contains a regex-based Python code validator bypass in CSV and Airtable Agent nodes that allows unauthenticated attackers to inject malicious code via prompt injection. Attackers can exploit unblocked pandas functions like pd.read_json() to exfiltrate datasets, perform SSRF against internal services, or achieve code execution through the unauthenticated prediction API.

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Meta Information

Published
2026-08-13
Last Modified
2026-08-13
Generated
2026-08-13
AI Q&A
2026-08-13
EPSS Evaluated
N/A
NVD
CVE-2026-73487
EUVD
EUVD-2026-57803

Affected Vendors & Products

Showing 2 associated CPEs
Vendor Product Version / Range
flowise flowise to 3.1.3 (exc)
flowiseai flowise to 3.1.3 (exc)

Helpful Resources

Exploitability

CWE
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KEV
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CWE ID Description
CWE-94 The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.

Attack-Flow Graph

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Executive Summary

CVE-2026-73487 is a critical vulnerability in Flowise versions 3.1.2 and earlier that allows prompt injection attacks to achieve Remote Code Execution (RCE) and Server-Side Request Forgery (SSRF). The issue stems from a regex-based blocklist in the CSV/Airtable Agent Python validator, which fails to block malicious payloads due to structural flaws. Attackers can bypass these checks using methods like pd.read_json(), pd.read_csv(), or pd.read_html() with URLs to exfiltrate data, perform SSRF against internal services, or load native libraries via np.ctypeslib.

Detection Guidance

Check Flowise version with `npm list -g flowise` or `flowise --version`. Inspect logs for suspicious API calls to /api/v1/prediction or nodes like CSV/Airtable Agent. Monitor network traffic for outbound SSRF attempts to internal services or cloud metadata endpoints.

Impact Analysis

This vulnerability allows unauthenticated attackers to inject malicious code via prompt injection through the CSV or Airtable Agent nodes. Exploits can lead to data exfiltration, internal network access via SSRF, or potential remote code execution. The attack requires no authentication or special configuration, as it exploits the unauthenticated prediction API.

Compliance Impact

This vulnerability could lead to severe data breaches, exposing sensitive datasets and violating compliance requirements under GDPR and HIPAA. Unauthorized data exfiltration and internal network access may result in regulatory penalties, reputational damage, and legal consequences due to non-compliance with data protection standards.

Mitigation Strategies

Upgrade Flowise to version 3.1.3 or later immediately. Disable unauthenticated prediction API endpoints if possible. Implement network segmentation to block internal service access from Flowise. Review and restrict pandas/numpy functions in code validators.

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