CVE-2024-10829 identifies a Denial of Service vulnerability in the multipart/form-data request boundary processing of the eosphoros-ai/db-gpt software, specifically version 0.6.0. The vulnerability arises from a loop with an unreachable exit condition (CWE-835) in the server's handling of multipart request boundaries. When an attacker sends a multipart request with an excessively long boundary string appended with additional characters, the server enters an infinite loop during boundary parsing. This results in excessive CPU and memory consumption, effectively causing a complete denial of service for legitimate users. The vulnerability is exploitable remotely without any authentication or user interaction, increasing its risk profile. All endpoints that process multipart/form-data requests are affected, indicating a broad attack surface within the application. Although no public exploits have been reported yet, the vulnerability's characteristics make it a prime candidate for exploitation once weaponized. The CVSS v3.0 score of 7.5 reflects a high severity due to the network attack vector, low attack complexity, no privileges required, no user interaction, and a high impact on availability. The lack of patches at the time of reporting necessitates interim mitigations to reduce exposure. This vulnerability highlights the importance of robust input validation and loop exit conditions in request parsing logic, especially in AI and data processing platforms like eosphoros-ai/db-gpt.

For European organizations utilizing eosphoros-ai/db-gpt, this vulnerability poses a significant risk of service disruption due to Denial of Service attacks. The infinite loop triggered by malformed multipart requests can exhaust server resources, leading to downtime and unavailability of critical AI or data processing services. This can impact business operations, customer experience, and potentially lead to financial losses, especially for organizations relying on real-time or high-availability systems. The unauthenticated nature of the exploit means attackers can launch attacks without prior access, increasing the threat from external adversaries. Additionally, the broad impact on all multipart/form-data endpoints expands the attack surface, making mitigation more challenging. In sectors such as finance, healthcare, and critical infrastructure within Europe, where AI-driven applications are increasingly integrated, the disruption could have cascading effects. Furthermore, regulatory compliance frameworks like GDPR emphasize service availability and data protection, so prolonged outages might also lead to compliance risks. Organizations must assess their exposure and prioritize remediation to maintain operational resilience.

1. Monitor vendor communications closely and apply official patches or updates as soon as they become available to address the vulnerability directly. 2. Implement strict input validation and enforce limits on multipart request boundary lengths at the application or web server level to prevent excessively long boundaries from being processed. 3. Deploy Web Application Firewalls (WAFs) with custom rules to detect and block malformed multipart/form-data requests that exhibit abnormal boundary lengths or patterns indicative of exploitation attempts. 4. Configure rate limiting and anomaly detection on endpoints handling multipart requests to reduce the risk of resource exhaustion from repeated attack attempts. 5. Conduct thorough code reviews and testing of multipart parsing logic to identify and fix any other potential infinite loop or resource exhaustion issues. 6. Isolate critical AI/data processing services behind reverse proxies or API gateways that can provide additional filtering and protection layers. 7. Maintain comprehensive logging and alerting for multipart request anomalies to enable rapid detection and response to exploitation attempts. 8. Educate development and security teams about CWE-835 and secure coding practices related to input parsing loops to prevent similar vulnerabilities in future releases.