CVE-2026-121967 in Coder
Summary
by MITRE • 11/04/2026
Coder 2.28.0 before 2.29.22, 2.30.0 before 2.34.13, 2.35.0 before 2.35.10, 2.36.0 before 2.36.8, 2.37.0 before 2.37.5, and 2.38.0 before 2.38.1 contains a path traversal vulnerability in the AI Gateway passthrough router, which forwards percent-encoded dot segments upstream without rejecting them. Authenticated users can send paths such as %2e%2e or ..%2F under allowlisted prefixes to reach unintended provider endpoints using the deployment's centrally managed provider key.
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Analysis
by VulDB Data Team • 11/04/2026
The vulnerability identified in Coder versions ranging from 2.28.0 up to specific patch releases across multiple major version lines, including 2.29.22, 2.34.13, 2.35.10, 2.36.8, 2.37.5, and 2.38.1, represents a critical path traversal flaw within the AI Gateway passthrough router component. This architectural element is designed to route requests from authenticated users to various external artificial intelligence provider endpoints using centrally managed API keys. The core technical deficiency lies in the handling of URL-encoded characters during request processing. Specifically, the router fails to adequately sanitize or reject percent-encoded dot segments, such as %2e%2e (representing ..) and ..%2F, before forwarding them upstream. This lack of normalization allows an attacker to manipulate the intended destination path by encoding directory traversal sequences that bypass standard access controls designed for allowlisted prefixes.
From a technical perspective, this flaw is classified under CWE-22: Improper Limitation of a Pathname to a Restricted Directory, which describes vulnerabilities where software does not properly neutralize special elements within file paths or URLs. The attacker leverages the fact that many backend systems and proxy layers may interpret percent-encoded sequences after initial routing decisions have been made based on unencoded strings. By submitting requests with encoded traversal characters under prefixes that are normally permitted for legitimate access, the malicious actor can effectively break out of the intended sandboxed environment. This mechanism allows the request to reach unintended provider endpoints rather than staying within the boundaries defined by the allowlist configuration. The vulnerability exploits the gap between how the router parses incoming URLs and how it validates them against security policies before proxying the traffic.
The operational impact of this vulnerability is severe due to its potential for unauthorized resource consumption and data exfiltration. Since authenticated users can exploit this flaw, any user with valid credentials on the Coder instance becomes a potential threat actor. The most significant consequence involves the misuse of centrally managed provider keys. These keys are typically high-privilege tokens intended for legitimate application functionality but carry substantial financial risk if used to access expensive AI model APIs without authorization. An attacker can generate massive costs by sending numerous requests through these unintended endpoints, leading to unexpected billing charges for the organization. Furthermore, depending on the specific providers and configurations involved, there may be risks related to data leakage or injection attacks where user input is processed by external services in ways that compromise confidentiality or integrity of sensitive information handled within the Coder environment.
This vulnerability aligns with MITRE ATT&CK techniques such as T1078: Valid Accounts, which describes adversaries using legitimate credentials to access resources without detection, and potentially relates to lateral movement patterns if the compromised provider keys allow further exploitation against other services integrated into the ecosystem. The attack vector is primarily remote but requires authentication, placing it in a medium-to-high severity category depending on the organization's user base size and sensitivity of data processed through the AI Gateway. Defense-in-depth strategies are essential here because relying solely on input validation at the application layer proved insufficient due to encoding bypasses.
To mitigate this risk, organizations must immediately upgrade Coder to version 2.29.22 or later for the 2.28.x series, 2.34.13 or later for the 2.30.x series, 2.35.10 or later for the 2.35.x series, 2.36.8 or later for the 2.36.x series, 2.37.5 or later for the 2.37.x series, and 2.38.1 or later for the 2.38.x series. These updates contain patches that properly normalize and validate URL paths before forwarding them to upstream providers, ensuring that percent-encoded traversal sequences are rejected rather than passed through. In addition to patching, administrators should review access logs for any signs of abuse involving unusual patterns in AI Gateway requests or spikes in API usage costs. Implementing strict rate limiting on the AI Gateway endpoints can also help mitigate potential financial damage from automated exploitation attempts while waiting for full deployment of the patched software versions across all instances.