Postmortem · CVE-2023-48022 · Actively Exploited
Ray’s dashboard and job API ship without auth by default. Exposed to a network, that is remote code execution — and it has been exploited at scale.
If you run Ray for distributed training or inference and the dashboard or job-submission API is reachable from an untrusted network, anyone who can reach it can run arbitrary code on your cluster.
ShadowRay (CVE-2023-48022) stems from the fact that Ray’s job-submission API — exposed by default via the Ray Dashboard — performs no authentication and accepts arbitrary Python for execution on cluster nodes. Any attacker with network access can submit malicious jobs that run with the Ray process’s privileges. Security researchers (Oligo) found it actively exploited for cryptojacking and data theft across 200,000+ exposed Ray servers, spanning education, crypto, and biopharma, with a later "ShadowRay 2.0" campaign turning clusters into a self-spreading botnet. The status is notably "disputed": Anyscale states Ray is designed to run only inside a strictly controlled network and that the missing auth is an intentional architectural choice — which makes network isolation your responsibility, not a patch. The record and hardening are below.
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Ask on WhatsAppOligo Security’s ShadowRay research, the GitHub Security Advisory GHSA-6wgj-66m2-xxp2 (CVE-2023-48022, including the disputed status and Anyscale’s position), and Ray’s own security documentation on running in a controlled network.
Read the GitHub Security Advisory (CVE-2023-48022)Get Started Today
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