CVE-2024-5753 is an SQL injection vulnerability classified under CWE-89 affecting vanna-ai/vanna version 0.3.4. The vulnerability exists in file-critical functions such as pg_read_file(), which are accessible through a Python Flask API endpoint. Due to improper neutralization of special characters in SQL commands, unauthenticated remote attackers can inject malicious SQL queries that manipulate the database to read arbitrary local files on the server. This includes highly sensitive system files like /etc/passwd, which can disclose user account information and potentially facilitate further attacks. The vulnerability does not require any authentication or user interaction, increasing its risk profile. The CVSS v3.0 score of 7.5 reflects a high severity, emphasizing the critical confidentiality impact while integrity and availability remain unaffected. No patches are currently listed, and no known exploits have been reported in the wild, but the vulnerability's nature makes it a prime target for attackers seeking to exfiltrate sensitive data. The exposure through a Flask API suggests that the attack surface includes any publicly accessible endpoints that invoke vulnerable SQL queries without proper sanitization or parameterization. This vulnerability highlights the importance of secure coding practices, especially in AI-related software that may handle sensitive data and system-level operations.

The primary impact of CVE-2024-5753 is the unauthorized disclosure of sensitive local files on affected servers, compromising confidentiality. For European organizations, this can lead to exposure of critical system information and potentially sensitive user data, increasing the risk of identity theft, privilege escalation, and further network compromise. The breach of files like /etc/passwd can facilitate lateral movement and privilege escalation within the network. Additionally, organizations subject to GDPR and other data protection regulations may face legal and financial penalties due to inadequate protection of personal data. The vulnerability's exploitation could undermine trust in AI and data analytics platforms, impacting business continuity and reputation. Since the vulnerability is exploitable remotely without authentication, it poses a significant threat to any exposed instances of vanna-ai/vanna, especially those integrated into critical infrastructure or handling sensitive datasets. The lack of current known exploits provides a window for proactive defense, but the high severity score necessitates urgent attention.

1. Immediately restrict access to the vulnerable Flask API endpoints by implementing network-level controls such as IP whitelisting or VPN access to limit exposure. 2. Employ Web Application Firewalls (WAFs) with custom rules to detect and block SQL injection attempts targeting the pg_read_file() function or similar endpoints. 3. Implement rigorous input validation and sanitization on all user-supplied inputs before they reach SQL queries, using parameterized queries or prepared statements to prevent injection. 4. Monitor logs for unusual query patterns or repeated access attempts to sensitive API functions indicative of exploitation attempts. 5. Engage with the vendor or community to obtain patches or updates addressing this vulnerability and apply them promptly once available. 6. Conduct a thorough security review of all API endpoints and database interaction code to identify and remediate similar injection flaws. 7. Educate development teams on secure coding practices, emphasizing the dangers of SQL injection and the importance of input neutralization. 8. Consider deploying runtime application self-protection (RASP) solutions to detect and block injection attacks in real-time. 9. For critical environments, isolate the application servers from direct internet exposure and use reverse proxies with strict access controls.