CVE-2024-10935 affects the automatic1111/stable-diffusion-webui, a widely used web interface for stable diffusion AI image generation. The vulnerability arises because the server component fails to correctly handle multipart HTTP requests when excessive arbitrary characters are appended to the end of multipart boundaries. Multipart boundaries are used to separate parts of a multipart/form-data request, typically for file uploads or form submissions. The flaw allows an attacker to craft malformed multipart requests with extended boundary strings that cause the server to allocate excessive resources without any limits or throttling, as described by CWE-770. This unchecked resource consumption can overwhelm the server's memory or processing capacity, leading to a denial of service (DoS) condition that disrupts service availability for all users. The vulnerability is unauthenticated, meaning attackers do not need valid credentials or user interaction to exploit it remotely over the network. The CVSS v3.0 score of 7.5 reflects a high severity due to the ease of exploitation (network vector, no privileges or user interaction required) and the impact on availability, though confidentiality and integrity remain unaffected. No patches or fixes are currently linked, and no known exploits have been reported in the wild yet. However, the popularity of automatic1111/stable-diffusion-webui in AI research and creative industries increases the risk of exploitation. The root cause is insufficient input validation and lack of resource allocation limits when parsing multipart boundaries, which should be addressed by implementing strict boundary length checks and throttling mechanisms to prevent resource exhaustion.

For European organizations, the impact of CVE-2024-10935 can be significant, particularly for those relying on automatic1111/stable-diffusion-webui for AI image generation workflows, research, or creative projects. A successful exploitation leads to a denial of service, causing service outages and disruption of operations. This can affect productivity, delay projects, and potentially lead to financial losses. Since the vulnerability is unauthenticated and remotely exploitable, attackers can launch DoS attacks without insider access, increasing the attack surface. Critical sectors such as research institutions, media companies, and AI startups using this tool may experience downtime, impacting their service availability and reputation. Additionally, organizations hosting public-facing instances of this web UI are at higher risk of external DoS attacks. The lack of confidentiality or integrity impact means data breaches or tampering are not a direct concern, but availability degradation alone can have cascading effects on dependent systems and users. The absence of known exploits currently provides a window for proactive mitigation before widespread attacks occur.

To mitigate CVE-2024-10935, organizations should implement the following specific measures: 1) Apply any available patches or updates from the automatic1111 project as soon as they are released. 2) If patches are unavailable, deploy web application firewalls (WAFs) or reverse proxies configured to detect and block malformed multipart requests with suspiciously long or malformed boundary strings. 3) Implement strict input validation on multipart boundaries, enforcing maximum length limits and rejecting requests exceeding these thresholds. 4) Introduce resource throttling and rate limiting on multipart/form-data parsing to prevent excessive memory or CPU consumption from malformed requests. 5) Monitor server resource usage and network traffic for unusual spikes indicative of attempted DoS attacks targeting multipart boundaries. 6) Restrict access to stable-diffusion-webui instances to trusted networks or authenticated users where possible to reduce exposure. 7) Conduct regular security assessments and penetration testing focusing on multipart request handling. 8) Educate development and operations teams about CWE-770 risks and secure coding practices related to resource allocation. These targeted mitigations go beyond generic advice by focusing on multipart boundary handling and resource management specific to this vulnerability.