CVE-2025-62616 identifies a Server-Side Request Forgery (SSRF) vulnerability in Significant-Gravitas AutoGPT, a platform designed to automate complex workflows using continuous AI agents. The vulnerability resides in the SendDiscordFileBlock feature, which uses the aiohttp.ClientSession().get method to fetch URLs without filtering or validating the input URL parameter. This lack of input sanitization allows an attacker to craft malicious URLs that the server will fetch, potentially accessing internal resources, metadata services, or other protected network endpoints inaccessible externally. The vulnerability affects all versions prior to autogpt-platform-beta-v0.6.34, where the issue has been patched. The CVSS 4.0 score of 9.3 reflects the ease of exploitation (no authentication or user interaction required), network-level attack vector, and the high impact on confidentiality and integrity. Exploiting this SSRF can lead to unauthorized data access, internal network reconnaissance, and possibly further exploitation chains. Although no known exploits are reported in the wild yet, the critical nature and widespread use of AutoGPT in AI-driven automation make this a significant threat. The vulnerability highlights the risks of integrating third-party libraries without proper input validation in AI platforms that interact with external services.

For European organizations, this SSRF vulnerability poses a severe risk, especially for those leveraging AutoGPT to automate workflows involving external APIs or internal network resources. Exploitation could allow attackers to bypass perimeter defenses, access sensitive internal services, exfiltrate confidential data, or pivot within the network. Sectors such as finance, healthcare, manufacturing, and critical infrastructure that increasingly adopt AI automation are particularly vulnerable. The confidentiality and integrity of data processed or accessed by AutoGPT agents could be compromised, leading to regulatory non-compliance under GDPR and potential operational disruptions. The vulnerability's ease of exploitation without authentication increases the attack surface, potentially enabling widespread attacks if vulnerable instances are exposed to the internet. Additionally, the SSRF could be used to target cloud metadata services, leading to credential theft and further compromise. The lack of known exploits currently provides a window for proactive mitigation but also suggests that attackers may develop exploits soon given the criticality.

Immediate upgrade to autogpt-platform-beta-v0.6.34 or later is the primary mitigation step to eliminate the vulnerability. Organizations should audit their AutoGPT deployments to identify and remediate any instances running vulnerable versions. Implement strict input validation and sanitization on all URL inputs used by AutoGPT components, especially those invoking HTTP client libraries. Network segmentation should be enforced to restrict AutoGPT servers' access to only necessary external and internal resources, minimizing the impact of potential SSRF exploitation. Employ web application firewalls (WAFs) with SSRF detection capabilities to monitor and block suspicious outbound requests. Conduct regular security assessments and penetration testing focusing on AI automation platforms. Additionally, monitor logs for unusual outbound HTTP requests originating from AutoGPT services. Educate developers and DevOps teams about secure coding practices related to SSRF and third-party library usage. Finally, consider implementing runtime application self-protection (RASP) solutions to detect and prevent SSRF attacks dynamically.