CVE-2026-2558 is a Server-Side Request Forgery (SSRF) vulnerability identified in the GeekAI software up to version 4.2.4. The vulnerability exists in the Download function located in the file api/handler/net_handler.go, where the URL argument is improperly validated or sanitized. This allows an attacker to craft malicious requests that the server will execute on their behalf, potentially accessing internal resources or services that are not directly exposed to the attacker. SSRF vulnerabilities can be leveraged to bypass network access controls, scan internal networks, access sensitive metadata services, or perform further attacks such as data exfiltration or lateral movement. The vulnerability is remotely exploitable without requiring user interaction or elevated privileges, increasing its risk profile. The CVSS 4.0 base score is 5.3, reflecting medium severity due to limited scope and impact on confidentiality, integrity, and availability. The exploit code has been publicly released, which raises the likelihood of active exploitation despite no confirmed reports of attacks in the wild. The vendor has been notified but has not yet issued a patch or mitigation guidance. This leaves users of GeekAI versions 4.2.0 through 4.2.4 exposed to potential attacks. Given the nature of SSRF, attackers could use this flaw to pivot into internal networks, access cloud metadata endpoints, or interact with internal APIs, posing significant security risks.

For European organizations, the SSRF vulnerability in GeekAI could lead to unauthorized access to internal systems and sensitive data, undermining confidentiality and potentially integrity if internal services are manipulated. The ability to make arbitrary server-side requests can facilitate reconnaissance of internal network topology, access to protected resources, and exploitation of other vulnerabilities within the internal environment. This is particularly concerning for organizations that deploy GeekAI in cloud or hybrid environments where metadata services or internal APIs are accessible internally. The medium severity rating indicates that while the vulnerability is not trivially exploitable for full system compromise, it still presents a meaningful risk, especially in environments with weak network segmentation or insufficient monitoring. The public availability of exploit code increases the risk of opportunistic attacks. Disruption of services or data leakage could impact compliance with European data protection regulations such as GDPR, leading to legal and reputational consequences. Organizations relying on GeekAI for AI-driven services or automation should prioritize assessment and mitigation to prevent potential lateral movement or data breaches.

1. Implement strict validation and sanitization of all URL inputs in the Download function to ensure only authorized and safe URLs are processed. 2. Restrict outbound network requests from GeekAI servers using firewall rules or network segmentation to limit access to only necessary external endpoints. 3. Employ allowlists for URLs or domains that GeekAI is permitted to access, blocking all others. 4. Monitor network traffic originating from GeekAI instances for unusual or unauthorized requests, especially to internal IP ranges or metadata services. 5. If possible, deploy GeekAI instances in isolated environments with minimal network privileges to reduce attack surface. 6. Engage with the vendor or community to obtain patches or updates addressing this vulnerability as soon as they become available. 7. Conduct internal audits and penetration testing focusing on SSRF vectors to identify and remediate similar issues. 8. Educate development and operations teams about SSRF risks and secure coding practices related to URL handling. 9. Consider implementing Web Application Firewalls (WAFs) with rules targeting SSRF attack patterns to provide an additional layer of defense. 10. Maintain up-to-date asset inventories to quickly identify affected GeekAI versions and prioritize remediation efforts.