CVE-2026-17534 in Kimi Code
Summary
by MITRE • 07/27/2026
Kimi Code (@moonshot-ai/kimi-code) before 0.27.0 implements FetchURL SSRF hardening as a static hostname and IP-literal denylist in assertSafeFetchTarget, without resolving DNS or re-validating hosts after HTTP redirects. An attacker who can influence a FetchURL call (for example via prompt injection) can supply a crafted public hostname that resolves to loopback or another internal address, or a public URL that redirects to such a target, and thereby reach internal network services that the denylist was intended to block. FetchURL is included in the default auto-approve tool set, so the call does not require interactive user confirmation in manual mode.
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Analysis
by VulDB Data Team • 07/27/2026
This vulnerability resides in the Kimi Code software version 0.27.0 and earlier, where the FetchURL functionality implements server-side request forgery protection through a static hostname and IP-literal denylist mechanism known as assertSafeFetchTarget. The security implementation fails to account for dynamic network behavior by not resolving DNS records or re-validating hostnames after HTTP redirects occur during the fetch operation. This fundamental flaw creates a pathway for attackers to bypass intended network restrictions through carefully crafted input that exploits the static nature of the validation process.
The technical execution of this vulnerability leverages the fact that the denylist operates on hostname and IP literal values at the time of initial request processing, without considering that DNS resolution might map a public hostname to an internal address such as loopback addresses or private network ranges. Attackers can utilize prompt injection techniques to influence FetchURL calls, supplying domain names that resolve to internal targets through DNS resolution or HTTP redirects. When these requests are processed through the tool's default auto-approve mechanism, no user interaction is required, making the exploitation particularly dangerous as it requires no manual confirmation from end users.
The operational impact of this vulnerability extends significantly beyond typical SSRF scenarios due to the inclusion of FetchURL in the default auto-approve tool set. This configuration means that any maliciously crafted URL or hostname that bypasses the static denylist can automatically access internal network services without requiring additional user approval steps. The vulnerability essentially allows attackers to perform reconnaissance and potentially exploit internal services that should remain isolated from external access, creating a substantial risk for organizations relying on this software for automated processing tasks.
Mitigation strategies must address both the immediate implementation flaw and broader architectural considerations for secure HTTP request handling. Organizations should implement dynamic DNS resolution validation within their SSRF protection mechanisms, ensuring that hostname and IP literal checks occur after all redirects are processed rather than only at initial request time. The solution should include maintaining up-to-date denylists that account for common internal network ranges and loopback addresses while implementing proper redirect validation that re-evaluates target addresses during the entire request lifecycle. This approach aligns with established security practices such as those outlined in CWE-918 and follows ATT&CK techniques related to server-side request forgery and command injection, where the static nature of denylists creates exploitable gaps in network isolation.
The vulnerability represents a classic case of insufficient input validation and inadequate consideration of dynamic network behavior in security controls. The static denylist approach fails to account for the complex interplay between DNS resolution, HTTP redirects, and network topology that modern applications encounter. Organizations should implement comprehensive security testing that includes scenarios involving DNS-based bypass attempts and redirect chain analysis to properly evaluate their SSRF protection mechanisms against similar implementation flaws.