CVE-2024-50050 Remote Code Execution Vulnerability affecting Meta
Evidence indicates that Meta is affected by remote code execution.
STABLE
What Happened
Evidence indicates that Meta is affected by remote code execution.
Why This Matters
The evidence matters to defenders using Meta because it could let an attacker run code in affected environments.
Recommended Action
No confirmed vendor remediation is available in the current evidence. Confirm whether Meta is present in your environment and review the affected configuration.
Exposure
Nov 14, 2025 05:30
Dec 07, 2025 05:30
Exploitation status: UNKNOWN
Primary entities:
Authoritative Intelligence
Timeline
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Incident first seen
Nov 14, 2025 05:30BugSkan first recorded this incident.
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Copy-paste vulnerability hits AI inference frameworks at Meta, Nvidia, and Microsoft - csoonline.com
Nov 14, 2025 05:30csoonline.com ยท Vulnerability
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Researchers Find Serious AI Bugs Exposing Meta, Nvidia, and Microsoft Inference Frameworks - The Hacker News
Nov 14, 2025 05:30thehackernews.com ยท Vulnerability
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ShadowMQ Vulnerabilities: Over 30 Critical Flaws in Meta Llama, NVIDIA TensorRT-LLM, vLLM, and Other AI Inference Engines Enable Data Theft and Remote Code Execution - Rescana
Dec 07, 2025 05:30rescana.com ยท Vulnerability
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Latest observed development
Dec 07, 2025 05:30Most recent source or update associated with this incident.
Sources
csoonline.com ยท Nov 14, 2025 05:30
A series of critical Remote Code Execution (RCE) vulnerabilities, dubbed 'ShadowMQ,' were discovered in major AI inference frameworks (Meta Llama Stack, Nvidia TensorRT-LLM, vLLM, etc.) due to insecure Python pickle deserialization over unauthenticated ZeroMQ sockets. These flaws, including CVE-2024-50050 and CVE-2025-23254, were widely replicated through code reuse, creating systemic risk for arbitrary code execution on enterprise AI infrastructure and potential data exfiltration.
Open publisher sourcethehackernews.com ยท Nov 14, 2025 05:30
Critical remote code execution vulnerabilities have been discovered across major AI inference engines, including Meta, Nvidia, and Microsoft, stemming from the unsafe use of ZeroMQ and Python's pickle deserialization. This "ShadowMQ" pattern allows attackers to execute arbitrary code, escalate privileges, and conduct model theft by exploiting unauthenticated ZMQ TCP sockets.
Open publisher sourcerescana.com ยท Dec 07, 2025 05:30
Over 30 critical "ShadowMQ" vulnerabilities, stemming from insecure ZeroMQ `recv_pyobj()` and Python `pickle` deserialization, affect leading AI inference engines such as Meta Llama LLM and NVIDIA TensorRT-LLM. These flaws enable remote code execution, data theft, and privilege escalation, with specific CVEs like CVE-2024-50050 attributed, and active exploitation has been observed.
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