BentoML's outbound connection safeguard (make_safe_connect in _internal/utils/uri.py) blocks private, loopback, and link-local IP addresses but fails to reject the RFC 6598 shared address space (100.64.0.0/10, CGNAT). In versions 1.4.19 through 1.4.39, an unauthenticated attacker can supply URLs pointing to that range via multipart file handling (MultipartSerde.ensure_file) or JSON request parsing (JSONSerde.parse_request), causing the server to make outbound requests to internal hosts on CGNAT networks (Server-Side Request Forgery). This is an incomplete fix for CVE-2025-54381.

BentoML is a Python library for building online serving systems optimized for AI apps and model inference. In versions 1.4.38 and prior, the build packaging workflow follows attacker-controlled symlinks inside the build context and copies the referenced file contents into the generated Bento artifact. If a victim builds an untrusted repository or other attacker-supplied build context, the attacker can place a symlink such as loot.txt -> /tmp/outside-marker.txt or a link to a more sensitive local file. When bentoml build runs, BentoML dereferences the symlink and packages the target file contents into the Bento. The leaked file can then propagate further through export, push, or containerization workflows. An attacker can exfiltrate local files from the build host into the Bento artifact, exposing secrets such as cloud credentials, SSH keys, API tokens, environment files, or other sensitive local configurations. Because Bento artifacts are commonly exported, uploaded, stored, or containerized after build, the leaked file contents can spread beyond the original build machine. This issue has been fixed in version 1.4.39.