CVE-2026-4504 identifies a SQL injection vulnerability in the eosphoros-ai db-gpt product, specifically affecting versions 0.7.0 through 0.7.5. The vulnerability resides in the /api/v1/editor/ endpoint, where incomplete input validation allows attackers to inject malicious SQL statements. This flaw enables remote, unauthenticated attackers to manipulate database queries, potentially extracting sensitive information, modifying data, or disrupting database availability. The vulnerability is classified as medium severity with a CVSS 4.0 score of 6.9, reflecting network attack vector, low attack complexity, no required privileges or user interaction, and limited impact on confidentiality, integrity, and availability. The vendor has not responded to early disclosure attempts, and no official patches have been released. However, exploit code is publicly available, increasing the risk of exploitation. The vulnerability's presence in an AI database product used for managing and querying data in AI applications raises concerns about data integrity and confidentiality in AI workflows. The lack of vendor mitigation heightens the urgency for organizations to implement compensating controls. The vulnerability does not require authentication or user interaction, making it easier for attackers to exploit remotely. The absence of scope change indicates the impact is confined to the vulnerable component without affecting other system components. Overall, this vulnerability represents a significant risk to organizations relying on eosphoros-ai db-gpt for data management in AI environments.

The SQL injection vulnerability in eosphoros-ai db-gpt can lead to unauthorized access to sensitive data, data corruption, or denial of service by manipulating database queries. Attackers can remotely execute arbitrary SQL commands without authentication, potentially exposing confidential information or altering critical data used in AI applications. This can undermine the integrity and reliability of AI models dependent on the database, causing cascading operational impacts. The availability of exploit code increases the likelihood of attacks, especially against organizations that have not applied mitigations. The lack of vendor response and patches prolongs exposure, increasing the window of opportunity for attackers. Organizations operating in sectors with high data sensitivity, such as finance, healthcare, or government, face elevated risks of data breaches or operational disruption. Additionally, compromised AI data stores may lead to flawed AI outputs, affecting decision-making processes. The vulnerability's network accessibility and low exploitation complexity make it attractive for attackers, including cybercriminals and nation-state actors targeting AI infrastructure.

1. Immediately restrict network access to the /api/v1/editor/ endpoint by implementing IP whitelisting or VPN-only access to limit exposure. 2. Deploy a web application firewall (WAF) with robust SQL injection detection and prevention rules tailored to the db-gpt API traffic. 3. Conduct thorough input validation and sanitization on all parameters accepted by the /api/v1/editor/ endpoint, applying strict whitelisting of allowed characters and query structures. 4. Monitor database logs and application logs for unusual or suspicious SQL queries indicative of injection attempts. 5. If possible, isolate the vulnerable db-gpt instances in segmented network zones to contain potential exploitation impact. 6. Engage with the vendor or community to track any forthcoming patches or updates and plan for prompt application once available. 7. Consider deploying database activity monitoring tools that can alert on anomalous query patterns. 8. Educate development and operations teams about the risks of SQL injection and secure coding practices to prevent similar vulnerabilities in future releases. 9. If feasible, migrate to alternative or updated database management solutions that do not exhibit this vulnerability until an official patch is released.