EXPOSURES › CVE-2026-73487
CVE-2026-73487
CRITICALFlowise AI's CSV and Airtable Agent nodes allowed unauthenticated attackers to inject malicious code via prompt injection, leading to potential data exfiltration, SSRF, and code execution.
The regex-based Python code validator bypass in Flowise before 3.1.3 enabled unauthenticated attackers to exploit unblocked pandas functions like pd.read_json() for data exfiltration, SSRF, and code execution. DIB organizations must ensure their AI/ML platforms are patched and validate input rigorously to prevent similar prompt injection attacks that could compromise sensitive data or enable remote code execution.
Shame score — A critical vulnerability with CVSS 9.8 allowing unauthenticated code execution via prompt injection in an AI platform, which is highly avoidable through proper input validation and patching.
▸ RECOMMENDED ACTION Remote code execution — patch the affected products on priority.
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.