📄 Description (English)
NVIDIA Megatron-LM contains a vulnerability in inferencing where an Attacker may cause an RCE by convincing a user to load a maliciously crafted input. A successful exploit of this vulnerability may lead to code execution, escalation of privileges, information disclosure, and data tampering.
🤖 AI Executive Summary
CVE-2026-24151 is a critical remote code execution vulnerability in NVIDIA Megatron-LM affecting all versions, exploitable through maliciously crafted input during model inference. With a CVSS score of 7.8 and no patch currently available, this poses immediate risk to organizations using Megatron-LM for AI/ML workloads. The vulnerability enables attackers to execute arbitrary code, escalate privileges, and access sensitive data, requiring urgent mitigation measures.
📄 Description (Arabic)
🤖 AI Intelligence Analysis Analyzed: Apr 29, 2026 02:51
🇸🇦 Saudi Arabia Impact Assessment
Saudi organizations in financial services (SAMA-regulated banks), government AI initiatives (NCA oversight), healthcare AI systems, and energy sector (ARAMCO AI applications) face significant risk. Telecommunications providers (STC, Mobily) using Megatron-LM for NLP services are particularly vulnerable. The vulnerability impacts confidentiality, integrity, and availability of AI-driven systems processing sensitive national data. Government entities and critical infrastructure operators must prioritize immediate isolation of affected systems.
🏢 Affected Saudi Sectors
Banking and Financial Services
Government and Public Administration
Healthcare and Medical AI Systems
Energy and Utilities
Telecommunications
Research and Academic Institutions
Defense and Security
🎯 MITRE ATT&CK Techniques
⚖️ Saudi Risk Score (AI)
8.2
/ 10.0
🔧 Remediation Steps (English)
IMMEDIATE ACTIONS:
1. Inventory all systems running NVIDIA Megatron-LM across your organization
2. Isolate affected systems from production networks and external access immediately
3. Disable or restrict access to Megatron-LM inference endpoints until patching is available
4. Review access logs for suspicious model loading activities
COMPENSATING CONTROLS (until patch available):
5. Implement strict input validation and sanitization for all model inputs
6. Deploy network segmentation to restrict Megatron-LM system communications
7. Enable comprehensive logging and monitoring of inference requests
8. Restrict user permissions to load custom models to authorized personnel only
9. Implement file integrity monitoring on model files and configuration directories
10. Use containerization with minimal privileges and read-only filesystems
DETECTION RULES:
- Monitor for unusual process execution spawned from Megatron-LM processes
- Alert on model loading from unexpected file paths or external sources
- Track failed and successful authentication attempts to inference endpoints
- Monitor for abnormal network connections from Megatron-LM systems
- Log all model input/output operations for forensic analysis
PATCHING:
- Subscribe to NVIDIA security advisories for patch availability
- Prepare patching procedures and test in isolated environments immediately upon patch release
- Establish rollback procedures before applying patches to production
🔧 خطوات المعالجة (العربية)
الإجراءات الفورية:
1. قم بحصر جميع الأنظمة التي تقوم بتشغيل NVIDIA Megatron-LM في مؤسستك
2. عزل الأنظمة المتأثرة عن شبكات الإنتاج والوصول الخارجي فوراً
3. تعطيل أو تقييد الوصول إلى نقاط نهاية استدلال Megatron-LM حتى يتوفر التصحيح
4. مراجعة سجلات الوصول للأنشطة المريبة في تحميل النموذج
الضوابط التعويضية (حتى يتوفر التصحيح):
5. تطبيق التحقق الصارم من صحة المدخلات وتنظيفها لجميع مدخلات النموذج
6. نشر تقسيم الشبكة لتقييد اتصالات نظام Megatron-LM
7. تفعيل السجلات الشاملة ومراقبة طلبات الاستدلال
8. تقييد أذونات المستخدم لتحميل النماذج المخصصة للموظفين المصرح لهم فقط
9. تطبيق مراقبة سلامة الملفات على ملفات النموذج ومجلدات التكوين
10. استخدام الحاويات بامتيازات محدودة وأنظمة ملفات للقراءة فقط
قواعد الكشف:
- مراقبة تنفيذ العمليات غير العادية التي تنبثق من عمليات Megatron-LM
- تنبيهات عند تحميل النموذج من مسارات ملفات غير متوقعة أو مصادر خارجية
- تتبع محاولات المصادقة الفاشلة والناجحة لنقاط نهاية الاستدلال
- مراقبة الاتصالات الشبكية غير الطبيعية من أنظمة Megatron-LM
- تسجيل جميع عمليات إدخال/إخراج النموذج للتحليل الجنائي
التصحيح:
- الاشتراك في تنبيهات أمان NVIDIA لتوفر التصحيح
- تحضير إجراءات التصحيح والاختبار في بيئات معزولة فور توفر التصحيح
- إنشاء إجراءات التراجع قبل تطبيق التصحيحات على الإنتاج
📋 Regulatory Compliance Mapping
🟢 NCA ECC 2024
ECC 2024 A.12.6.1 - Management of technical vulnerabilities
ECC 2024 A.14.2.1 - Secure development policy
ECC 2024 A.12.2.1 - User endpoint devices
ECC 2024 A.13.1.3 - Segregation of networks
🔵 SAMA CSF
SAMA CSF ID.RA-1 - Asset Management and Inventory
SAMA CSF PR.IP-12 - Software, firmware, and information integrity mechanisms
SAMA CSF DE.CM-1 - The network is monitored to detect potential cybersecurity events
SAMA CSF RS.MI-1 - Incidents are contained
🟡 ISO 27001:2022
ISO 27001:2022 A.12.2.1 - Endpoint protection
ISO 27001:2022 A.12.6.1 - Management of technical vulnerabilities
ISO 27001:2022 A.14.2.1 - Secure development policy and procedures
ISO 27001:2022 A.8.1.1 - Inventory of assets
🟣 PCI DSS v4.0.1
PCI DSS 6.2 - Ensure that all system components and software are protected from known vulnerabilities
PCI DSS 11.2 - Run automated vulnerability scanning tools regularly
🔗 References & Sources 3
📦 Affected Products / CPE 1 entries
nvidia:megatron-lm