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Vulnerabilities

CVE-2026-3357

High
CWE-502 — Weakness Type
Published: Apr 8, 2026  ·  Modified: Apr 14, 2026  ·  Source: NVD
CVSS v3
8.8
🔗 NVD Official
📄 Description (English)

IBM Langflow Desktop 1.6.0 through 1.8.2 Langflow could allow an authenticated user to execute arbitrary code on the system, caused by an insecure default setting which permits the deserialization of untrusted data in the FAISS component.

🤖 AI Executive Summary

IBM Langflow Desktop versions 1.6.0-1.8.2 contain a critical insecure deserialization vulnerability in the FAISS component that allows authenticated users to execute arbitrary code. This vulnerability exploits unsafe default settings that permit deserialization of untrusted data, posing significant risk to organizations using Langflow for AI/ML workflows. No patch is currently available, requiring immediate compensating controls.

📄 Description (Arabic)

🤖 AI Intelligence Analysis Analyzed: Apr 23, 2026 05:17
🇸🇦 Saudi Arabia Impact Assessment
Saudi organizations leveraging Langflow for AI/ML applications—particularly in banking (SAMA-regulated institutions), government digital transformation initiatives (NCA oversight), healthcare analytics, and energy sector AI implementations—face direct code execution risks. Financial institutions using Langflow for fraud detection or customer analytics are at highest risk. Government agencies adopting AI tools for citizen services could experience system compromise. The vulnerability is particularly concerning given Saudi Arabia's Vision 2030 AI adoption initiatives and increasing reliance on AI-powered solutions across critical sectors.
🏢 Affected Saudi Sectors
Banking and Financial Services Government and Public Administration Healthcare and Medical Research Energy and Utilities Telecommunications Research and Academia AI/ML Development Organizations
⚖️ Saudi Risk Score (AI)
8.2
/ 10.0
🔧 Remediation Steps (English)
IMMEDIATE ACTIONS:
1. Inventory all Langflow Desktop installations across your organization, particularly versions 1.6.0-1.8.2
2. Restrict network access to Langflow instances using firewall rules—limit to authorized users only
3. Disable FAISS component if not actively required for operations
4. Implement strict authentication controls and disable default credentials
5. Monitor for suspicious deserialization activities in application logs

COMPENSATING CONTROLS:
1. Implement application-level input validation to reject suspicious serialized objects
2. Run Langflow in isolated containers with minimal privileges and restricted filesystem access
3. Deploy Web Application Firewall (WAF) rules to detect and block deserialization payloads
4. Enable comprehensive audit logging for all Langflow user activities
5. Implement network segmentation to isolate Langflow instances from critical systems

DETECTION RULES:
1. Monitor for Java serialization magic bytes (0xaced0005) in network traffic to Langflow
2. Alert on unexpected child process spawning from Langflow application
3. Track modifications to FAISS configuration files and serialization settings
4. Monitor for unusual outbound connections from Langflow processes

PATCHING STRATEGY:
1. Subscribe to IBM security advisories for patch availability
2. Plan immediate upgrade to patched version upon release
3. Consider migration to alternative AI/ML frameworks if patch timeline extends beyond 30 days
🔧 خطوات المعالجة (العربية)
الإجراءات الفورية:
1. قم بحصر جميع تثبيتات Langflow Desktop عبر مؤسستك، خاصة الإصدارات 1.6.0-1.8.2
2. قيد الوصول إلى شبكة مثيلات Langflow باستخدام قواعد جدار الحماية—حصر الوصول على المستخدمين المصرحين فقط
3. عطل مكون FAISS إذا لم يكن مطلوباً بنشاط للعمليات
4. طبق ضوابط مصادقة صارمة وعطل بيانات الاعتماد الافتراضية
5. راقب الأنشطة المريبة لفك التسلسل في سجلات التطبيق

الضوابط التعويضية:
1. طبق التحقق من صحة المدخلات على مستوى التطبيق لرفض الكائنات المسلسلة المريبة
2. قم بتشغيل Langflow في حاويات معزولة بامتيازات محدودة والوصول المقيد للنظام الملفات
3. نشر قواعد جدار تطبيقات الويب (WAF) للكشف عن حمولات فك التسلسل وحجبها
4. فعل تسجيل التدقيق الشامل لجميع أنشطة مستخدمي Langflow
5. طبق تقسيم الشبكة لعزل مثيلات Langflow عن الأنظمة الحرجة

قواعد الكشف:
1. راقب بايتات سحر التسلسل Java (0xaced0005) في حركة الشبكة إلى Langflow
2. تنبيه عند توليد عمليات فرعية غير متوقعة من تطبيق Langflow
3. تتبع التعديلات على ملفات تكوين FAISS وإعدادات التسلسل
4. راقب الاتصالات الخارجية غير العادية من عمليات Langflow

استراتيجية التصحيح:
1. اشترك في استشارات أمان IBM لتوفر التصحيحات
2. خطط للترقية الفورية إلى الإصدار المصحح عند توفره
3. فكر في الهجرة إلى أطر عمل بديلة للذكاء الاصطناعي/التعلم الآلي إذا امتد الجدول الزمني للتصحيح لأكثر من 30 يوماً
📋 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 - Monitoring and logging of access
🔵 SAMA CSF
SAMA CSF ID.BE-1 - Asset management SAMA CSF PR.DS-2 - Data security SAMA CSF DE.CM-1 - Detection processes and tools
🟡 ISO 27001:2022
ISO 27001:2022 A.12.2.1 - Information security event logging ISO 27001:2022 A.14.2.1 - Secure development policy and procedures ISO 27001:2022 A.12.6.1 - Management of technical vulnerabilities
🟣 PCI DSS v4.0.1
PCI DSS 6.2 - Security patches for system components PCI DSS 10.2 - Implement automated audit trails
📊 CVSS Score
8.8
/ 10.0 — High
📊 CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Attack VectorN — None / Network
Attack ComplexityL — Low / Local
Privileges RequiredL — Low / Local
User InteractionN — None / Network
ScopeU — Unchanged
ConfidentialityH — High
IntegrityH — High
AvailabilityH — High
📋 Quick Facts
Severity High
CVSS Score8.8
CWECWE-502
EPSS0.26%
Exploit No
Patch ✗ No
Published 2026-04-08
Source Feed nvd
Views 4
🇸🇦 Saudi Risk Score
8.2
/ 10.0 — Saudi Risk
Priority: HIGH
🏷️ Tags
CWE-502
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