Megatron Bridge CVE-2026-61773

Exploitation requires a local account with at minimum low-level operating system privileges on the host running NVIDIA Megatron Bridge - the CVSS vector (AV:L/PR:L) confirms both conditions. The attacker must be able to write to or inject data into the specific local channel (socket, IPC path, or shared file) that the Bridge component reads and deserializes; this channel's accessibility to non-root local users is the critical gating condition. No user interaction by any other party is required once the payload is positioned. Exploitation is limited to environments where untrusted or semi-trusted local users share system access with the Megatron Bridge process; isolated single-user workstations or deployments where the Bridge runs under a dedicated service account unreachable by general users are not meaningfully exposed. Remote unauthenticated exploitation is not supported by the CVSS vector or description.

The CVSS 3.1 vector (AV:L/AC:L/PR:L/UI:N) constrains exploitation to local, authenticated (low-privilege) access, which limits the attack surface compared to network-exposed vulnerabilities. However, once local access exists, the attack is low-complexity and requires no user interaction, making it reliable in applicable environments. Full CIA impact (C:H/I:H/A:H) produces a 7.8 base score, accurately reflecting code execution consequences. No EPSS data was provided, and the absence of a CISA KEV listing suggests no confirmed widespread active exploitation at time of analysis; however, deserialization vulnerabilities are historically weaponized quickly once public research emerges. The highest-risk deployment scenario is a shared GPU compute cluster where multiple low-privilege users share access to Megatron infrastructure - this is common in academic HPC environments and cloud AI training platforms. Single-user or tightly service-account-isolated deployments face substantially reduced real-world risk. EPSS and POC status are unknown; affected version range is not confirmed from available data.

A low-privileged user on a shared GPU training cluster crafts a malicious serialized object - such as a Python pickle payload embedding an OS command or a Java gadget chain - and injects it into the local IPC channel or data path consumed by the Megatron Bridge component. Upon deserialization, the embedded payload executes arbitrary code under the Bridge process's identity, granting the attacker access to model weights, training datasets, API credentials stored in memory, or the ability to corrupt ongoing training runs. No public proof-of-concept code has been identified at time of analysis, but deserialization exploit techniques for common frameworks are well-documented and widely understood.