📄 Description (English)
A vulnerability has been found in PromtEngineer localGPT up to 4d41c7d1713b16b216d8e062e51a5dd88b20b054. The impacted element is the function _route_using_overviews of the file backend/server.py of the component LLM Prompt Handler. Such manipulation leads to injection. The attack may be performed from remote. The exploit has been disclosed to the public and may be used. This product utilizes a rolling release system for continuous delivery, and as such, version information for affected or updated releases is not disclosed. The vendor was contacted early about this disclosure but did not respond in any way.
🤖 AI Executive Summary
CVE-2026-5002 is a high-severity injection vulnerability in PromtEngineer's localGPT affecting the LLM Prompt Handler component. The flaw in the _route_using_overviews function allows remote attackers to inject malicious prompts or commands, potentially leading to unauthorized data access, model manipulation, or system compromise. With no patch available and public exploit disclosure, immediate mitigation is critical for Saudi organizations deploying this AI/ML infrastructure.
📄 Description (Arabic)
🤖 AI Intelligence Analysis Analyzed: May 6, 2026 20:38
🇸🇦 Saudi Arabia Impact Assessment
This vulnerability poses significant risk to Saudi organizations deploying localGPT for AI/ML applications, particularly: (1) Financial institutions (SAMA-regulated banks) using AI for fraud detection or customer service; (2) Government agencies (NCA, CITC) leveraging LLM for data analysis or citizen services; (3) Healthcare providers using AI for diagnostics or administrative tasks; (4) Energy sector (ARAMCO, utilities) employing AI for operational optimization; (5) Telecommunications (STC, Mobily) using LLM for customer support automation. The injection vulnerability could enable prompt injection attacks, data exfiltration, model poisoning, or lateral movement within enterprise networks.
🏢 Affected Saudi Sectors
Banking & Financial Services
Government & Public Administration
Healthcare & Medical Services
Energy & Utilities
Telecommunications
Retail & E-commerce
Insurance
Education & Research
🎯 MITRE ATT&CK Techniques
T1190 - Exploit Public-Facing Application (remote exploitation of LLM endpoint)
T1059 - Command and Scripting Interpreter (prompt injection for command execution)
T1566 - Phishing (malicious prompts delivered via API)
T1557 - Man-in-the-Middle (potential for prompt interception if unencrypted)
T1040 - Traffic Capture (monitoring LLM interactions for data exfiltration)
T1110 - Brute Force (potential for API credential attacks)
T1021 - Remote Services (lateral movement via compromised LLM access)
⚖️ Saudi Risk Score (AI)
7.8
/ 10.0
🔧 Remediation Steps (English)
IMMEDIATE ACTIONS:
1. Inventory all instances of PromtEngineer localGPT across your organization and document deployment locations
2. Isolate affected systems from production networks if possible, or implement network segmentation
3. Disable the _route_using_overviews function or restrict access to trusted internal networks only
4. Monitor all API calls to the LLM Prompt Handler for suspicious prompt patterns
COMPENSATING CONTROLS (until patch available):
5. Implement strict input validation and sanitization on all prompts before reaching the vulnerable function
6. Deploy Web Application Firewall (WAF) rules to detect and block injection patterns (e.g., prompt injection keywords, command separators)
7. Enforce authentication and authorization controls; restrict API access to authenticated users only
8. Implement rate limiting on the _route_using_overviews endpoint
9. Enable comprehensive logging of all LLM interactions for forensic analysis
DETECTION RULES:
10. Monitor for unusual prompt patterns: system role changes, instruction overrides, data exfiltration attempts
11. Alert on API calls containing: "ignore previous", "system prompt", "execute", "bypass", or similar injection keywords
12. Track failed authentication attempts and unusual API access patterns
13. Monitor for abnormal LLM output (e.g., revealing system prompts, credentials, or sensitive data)
LONG-TERM:
14. Contact PromtEngineer vendor regularly for patch status; consider alternative LLM solutions if vendor remains unresponsive
15. Implement a Software Composition Analysis (SCA) tool to track vulnerable dependencies
16. Establish incident response procedures specific to LLM/AI security incidents
🔧 خطوات المعالجة (العربية)
الإجراءات الفورية:
1. قم بحصر جميع نسخ PromtEngineer localGPT عبر مؤسستك وتوثيق مواقع النشر
2. عزل الأنظمة المتأثرة عن شبكات الإنتاج إن أمكن، أو تطبيق تقسيم الشبكة
3. تعطيل دالة _route_using_overviews أو تقييد الوصول إلى الشبكات الداخلية الموثوقة فقط
4. مراقبة جميع استدعاءات API لمعالج مطالبات LLM بحثاً عن أنماط مريبة
الضوابط البديلة (حتى توفر التصحيح):
5. تطبيق التحقق الصارم من صحة المدخلات والتطهير على جميع المطالبات قبل الوصول إلى الدالة الضعيفة
6. نشر قواعد جدار حماية تطبيقات الويب (WAF) للكشف عن أنماط الحقن وحجبها
7. فرض ضوابط المصادقة والتفويض؛ تقييد وصول API للمستخدمين المصرح لهم فقط
8. تطبيق تحديد معدل على نقطة نهاية _route_using_overviews
9. تفعيل السجلات الشاملة لجميع تفاعلات LLM للتحليل الجنائي
قواعد الكشف:
10. مراقبة أنماط المطالبات غير العادية: تغييرات دور النظام، تجاوز التعليمات، محاولات سرقة البيانات
11. التنبيه على استدعاءات API تحتوي على: "تجاهل السابق"، "مطالبة النظام"، "تنفيذ"، "تجاوز"، أو كلمات حقن مشابهة
12. تتبع محاولات المصادقة الفاشلة وأنماط الوصول غير العادية
13. مراقبة مخرجات LLM غير الطبيعية (مثل الكشف عن مطالبات النظام أو بيانات الاعتماد أو البيانات الحساسة)
المدى الطويل:
14. اتصل بمورد PromtEngineer بانتظام لحالة التصحيح؛ فكر في حلول LLM بديلة إذا ظل المورد غير مستجيب
15. تطبيق أداة تحليل تكوين البرامج (SCA) لتتبع التبعيات الضعيفة
16. إنشاء إجراءات الاستجابة للحوادث الخاصة بحوادث أمان LLM/AI
📋 Regulatory Compliance Mapping
🟢 NCA ECC 2024
ECC 2024 A.5.1.1 - Information Security Policies (AI/ML security governance)
ECC 2024 A.6.1.1 - Access Control (API authentication and authorization)
ECC 2024 A.12.2.1 - Change Management (patch management for AI components)
ECC 2024 A.12.6.1 - Management of Technical Vulnerabilities (vulnerability assessment and remediation)
🔵 SAMA CSF
SAMA CSF Governance & Risk Management - AI/ML risk assessment and oversight
SAMA CSF Security & Resilience - Vulnerability management and incident response
SAMA CSF Operational Resilience - System availability and integrity controls
SAMA CSF Third-Party Risk Management - Vendor security and patch management
🟡 ISO 27001:2022
ISO 27001:2022 A.5.1 - Policies for information security (AI security policies)
ISO 27001:2022 A.6.1 - Organization of information security (roles and responsibilities)
ISO 27001:2022 A.8.1 - Asset management (AI/ML asset inventory)
ISO 27001:2022 A.12.6 - Management of technical vulnerabilities (patch management)
ISO 27001:2022 A.14.2 - Information security in supplier relationships (vendor management)
🟣 PCI DSS v4.0.1
PCI DSS 6.2 - Security patches and updates (if LLM processes payment data)
PCI DSS 6.5.1 - Injection flaws (direct applicability to this CVE)
PCI DSS 11.2 - Vulnerability scanning (detection of injection vulnerabilities)