AITER 0.1.14 RCE via Unauth MessageQueue.recv() on ZMQ SUB
CVE-2026-49121 Published on June 1, 2026

AI Tensor Engine for ROCm (AITER) 0.1.14 Unauthenticated RCE via MessageQueue.recv() Pickle Deserialization
AI Tensor Engine for ROCm (AITER) through 0.1.14 contains an unauthenticated remote code execution vulnerability in the MessageQueue.recv() function within shm_broadcast.py that allows unauthenticated remote attackers to execute arbitrary code by sending a malicious pickle payload to a ZMQ SUB socket with no authentication, HMAC, or format validation. Attackers who can reach the writer XPUB endpoint on the cluster network or supply a forged Handle with an attacker-controlled remote_subscribe_addr can deliver a crafted pickle payload that executes arbitrary code simultaneously as the inference worker process on every remote reader worker.

NVD

Vulnerability Analysis

CVE-2026-49121 can be exploited with network access, and does not require authorization privileges or user interaction. This vulnerability is consided to have a high level of attack complexity. Public availability of a proof of concept (POC) exploit exists for CVE-2026-49121. The potential impact of an exploit of this vulnerability is considered to be very high.

Attack Vector:
NETWORK
Attack Complexity:
HIGH
Privileges Required:
NONE
User Interaction:
NONE
Scope:
UNCHANGED
Confidentiality Impact:
HIGH
Integrity Impact:
HIGH
Availability Impact:
HIGH

Weakness Type

What is a Marshaling, Unmarshaling Vulnerability?

The application deserializes untrusted data without sufficiently verifying that the resulting data will be valid.

CVE-2026-49121 has been classified to as a Marshaling, Unmarshaling vulnerability or weakness.


Products Associated with CVE-2026-49121

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Affected Versions

ROCm aiter: Red Hat AI Inference Server: Red Hat AI Inference Server: Red Hat Enterprise Linux AI (RHEL AI) 3: Red Hat Enterprise Linux AI (RHEL AI) 3: Red Hat OpenShift AI (RHOAI):

Exploit Probability

EPSS
0.74%
Percentile
49.59%

EPSS (Exploit Prediction Scoring System) scores estimate the probability that a vulnerability will be exploited in the wild within the next 30 days. The percentile shows you how this score compares to all other vulnerabilities.