CVE-2025-32393 is a denial-of-service vulnerability classified under CWE-770 (Allocation of Resources Without Limits or Throttling) affecting Significant-Gravitas AutoGPT prior to version 0.6.32. AutoGPT is a platform enabling continuous AI agents to automate complex workflows, including RSS feed parsing via the ReadRSSFeedBlock component. The vulnerability arises because the feedparser.parser function processes XML feeds without imposing limits on parsing time or memory allocation. An attacker can craft a deeply nested or malicious XML feed that causes the parser to consume excessive memory, leading to resource exhaustion and denial of service. This can crash the AutoGPT service or severely degrade its performance, disrupting automated AI workflows. The vulnerability is remotely exploitable without authentication or user interaction, increasing its risk profile. The CVSS 4.0 vector (AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N) indicates network attack vector, low complexity, no privileges or user interaction required, and high impact on availability. Although no public exploits are known, the issue has been patched in autogpt-platform-beta-v0.6.32. Organizations relying on AutoGPT for AI-driven automation should prioritize patching and consider additional controls such as input validation and resource monitoring to mitigate potential exploitation.

For European organizations, this vulnerability poses a significant risk to the availability of AI automation services powered by AutoGPT. Disruption of these services can halt critical automated workflows, leading to operational delays, reduced productivity, and potential financial losses. Industries heavily investing in AI automation, such as manufacturing, finance, and technology sectors, may experience cascading effects if AutoGPT services become unavailable. Given the remote and unauthenticated exploitability, attackers could launch DoS attacks at scale, potentially targeting multiple organizations simultaneously. The lack of user interaction or privileges required lowers the barrier for exploitation, increasing the threat landscape. Additionally, organizations that integrate AutoGPT into customer-facing or critical infrastructure systems risk reputational damage and compliance issues if service disruptions occur. The impact is amplified in countries with advanced AI adoption and digital transformation initiatives, where reliance on continuous AI agents is higher.

1. Immediate upgrade to autogpt-platform-beta-v0.6.32 or later versions where the vulnerability is patched. 2. Implement strict input validation and sanitization on all RSS feed URLs and XML content before parsing to detect and reject deeply nested or malformed XML structures. 3. Introduce resource usage limits and timeouts on XML parsing operations within AutoGPT to prevent excessive memory consumption. 4. Deploy runtime monitoring tools to track memory and CPU usage of AutoGPT processes, enabling rapid detection of anomalous resource spikes. 5. Use network-level protections such as web application firewalls (WAFs) to filter and block suspicious RSS feed requests or malformed XML payloads. 6. Conduct regular security assessments and fuzz testing on XML parsing components to identify and remediate similar resource exhaustion issues proactively. 7. Educate developers and operators on secure coding practices related to XML processing and resource management. 8. Maintain an incident response plan that includes procedures for mitigating DoS attacks targeting AI automation platforms.