Ray prior to 2.56.0 contains an unsafe deserialization vulnerability in the WebDataset reader that allows attackers to achieve remote code execution by supplying a malicious tar archive to the read_webdataset() function. The _default_decoder() function in webdataset_datasource.py unconditionally calls pickle.loads() on tar entries with .pkl/.pickle extensions and torch.load() with weights_only=False on .pt/.pth entries, executing arbitrary code inside Ray remote workers on every worker that processes the malicious archive.
Ray is an AI compute engine. In versions 2.53.0 and below, thedashboard HTTP server blocks browser-origin POST/PUT but does not cover DELETE, and key DELETE endpoints are unauthenticated by default. If the dashboard/agent is reachable (e.g., --dashboard-host=0.0.0.0), a web page via DNS rebinding or same-network access can issue DELETE requests that shut down Serve or delete jobs without user interaction. This is a drive-by availability impact. The fix for this vulnerability is to update to Ray 2.54.0 or higher.
Ray is an AI compute engine. Prior to version 2.52.0, developers working with Ray as a development tool can be exploited via a critical RCE vulnerability exploitable via Firefox and Safari. This vulnerability is due to an insufficient guard against browser-based attacks, as the current defense uses the User-Agent header starting with the string "Mozilla" as a defense mechanism. This defense is insufficient as the fetch specification allows the User-Agent header to be modified. Combined with a DNS rebinding attack against the browser, and this vulnerability is exploitable against a developer running Ray who inadvertently visits a malicious website, or is served a malicious advertisement (malvertising). This issue has been patched in version 2.52.0.