📧 info@ciso.sa | 📱 +966550939344 | Riyadh, Kingdom of Saudi Arabia
🔧 Scheduled Maintenance — Saturday 2:00-4:00 AM AST. Some features may be temporarily unavailable.    ●   
💎
Pro Plan 50% Off Unlock all AI features, unlimited reports, and priority support. Upgrade
Search Center
ESC to close
Global vulnerability Artificial Intelligence and Technology HIGH 2h Global general Technology and Artificial Intelligence MEDIUM 5h Global general Technology and Artificial Intelligence HIGH 6h Global vulnerability Higher Education CRITICAL 15h Global data_breach Government HIGH 16h Global supply_chain Software Development and Open Source Communities CRITICAL 16h Global malware Software Development CRITICAL 16h Global phishing Multiple Sectors HIGH 17h Global vulnerability Web Applications CRITICAL 17h Global apt Critical Infrastructure CRITICAL 17h Global vulnerability Artificial Intelligence and Technology HIGH 2h Global general Technology and Artificial Intelligence MEDIUM 5h Global general Technology and Artificial Intelligence HIGH 6h Global vulnerability Higher Education CRITICAL 15h Global data_breach Government HIGH 16h Global supply_chain Software Development and Open Source Communities CRITICAL 16h Global malware Software Development CRITICAL 16h Global phishing Multiple Sectors HIGH 17h Global vulnerability Web Applications CRITICAL 17h Global apt Critical Infrastructure CRITICAL 17h Global vulnerability Artificial Intelligence and Technology HIGH 2h Global general Technology and Artificial Intelligence MEDIUM 5h Global general Technology and Artificial Intelligence HIGH 6h Global vulnerability Higher Education CRITICAL 15h Global data_breach Government HIGH 16h Global supply_chain Software Development and Open Source Communities CRITICAL 16h Global malware Software Development CRITICAL 16h Global phishing Multiple Sectors HIGH 17h Global vulnerability Web Applications CRITICAL 17h Global apt Critical Infrastructure CRITICAL 17h
Vulnerabilities

CVE-2024-58340

High ⚡ Exploit Available
LangChain versions up to and including 0.3.1 contain a regular expression denial-of-service (ReDoS) vulnerability in the MRKLOutputParser.parse() method (libs/langchain/langchain/agents/mrkl/output_pa
CWE-1333 — Weakness Type
Published: Jan 12, 2026  ·  Modified: Feb 28, 2026  ·  Source: NVD
CVSS v3
7.5
🔗 NVD Official
📄 Description (English)

LangChain versions up to and including 0.3.1 contain a regular expression denial-of-service (ReDoS) vulnerability in the MRKLOutputParser.parse() method (libs/langchain/langchain/agents/mrkl/output_parser.py). The parser applies a backtracking-prone regular expression when extracting tool actions from model output. An attacker who can supply or influence the parsed text (for example via prompt injection in downstream applications that pass LLM output directly into MRKLOutputParser.parse()) can trigger excessive CPU consumption by providing a crafted payload, causing significant parsing delays and a denial-of-service condition.

🤖 AI Executive Summary

CVE-2024-58340 is a Regular Expression Denial-of-Service (ReDoS) vulnerability in LangChain versions up to 0.3.1 affecting the MRKLOutputParser.parse() method. An attacker can exploit this through prompt injection to cause excessive CPU consumption and service disruption. This vulnerability is particularly critical for Saudi organizations deploying LLM-based applications in production environments, as it enables denial-of-service attacks with minimal technical barriers.

📄 Description (Arabic)

🤖 AI Intelligence Analysis Analyzed: May 1, 2026 21:55
🇸🇦 Saudi Arabia Impact Assessment
This vulnerability poses significant risk to Saudi financial institutions (SAMA-regulated banks) using LangChain for AI-powered customer service and fraud detection systems. Government agencies (NCA oversight) deploying LLM applications for citizen services face service availability risks. Healthcare organizations using AI chatbots for patient interaction are vulnerable. Telecom providers (STC, Mobily) leveraging LLMs for customer support could experience widespread service disruptions. Energy sector applications (ARAMCO, SEC) using AI for operational support are at risk. The vulnerability is particularly dangerous in multi-tenant environments where untrusted user input reaches the parser.
🏢 Affected Saudi Sectors
Banking and Financial Services Government and Public Administration Healthcare Energy and Utilities Telecommunications E-commerce and Retail Insurance
⚖️ Saudi Risk Score (AI)
7.8
/ 10.0
🔧 Remediation Steps (English)
IMMEDIATE ACTIONS:
1. Identify all applications using LangChain versions ≤0.3.1 in your environment
2. Assess exposure: determine if user-controlled input can reach MRKLOutputParser.parse()
3. Implement input validation and sanitization before parser invocation

PATCHING GUIDANCE:
1. Upgrade LangChain to version 0.3.2 or later immediately
2. Test upgraded versions in staging environment before production deployment
3. Verify no breaking changes in your LLM agent implementations

COMPENSATING CONTROLS (if immediate patching not possible):
1. Implement request timeout mechanisms (set aggressive timeouts on parser operations)
2. Deploy rate limiting on LLM output processing endpoints
3. Add CPU/memory monitoring with automatic circuit breakers for parser operations
4. Implement prompt injection detection and filtering before LLM output reaches parser
5. Use Web Application Firewall (WAF) rules to detect ReDoS patterns in requests

DETECTION RULES:
1. Monitor for parser execution times exceeding 5 seconds
2. Alert on CPU spikes coinciding with LangChain parser operations
3. Log and analyze MRKLOutputParser.parse() inputs for suspicious regex patterns
4. Implement SIEM rules detecting repeated failed parsing attempts
5. Monitor for patterns like excessive backslashes, nested quantifiers in tool action outputs
🔧 خطوات المعالجة (العربية)
الإجراءات الفورية:
1. حدد جميع التطبيقات التي تستخدم إصدارات LangChain ≤0.3.1 في بيئتك
2. قيّم التعرض: حدد ما إذا كان يمكن للمدخلات التي يتحكم بها المستخدم الوصول إلى MRKLOutputParser.parse()
3. طبّق التحقق من صحة المدخلات والتنظيف قبل استدعاء المحلل

إرشادات التصحيح:
1. قم بترقية LangChain إلى الإصدار 0.3.2 أو أحدث على الفور
2. اختبر الإصدارات المرقاة في بيئة التجريب قبل نشرها في الإنتاج
3. تحقق من عدم وجود تغييرات كسر في تطبيقات وكيل LLM الخاصة بك

الضوابط البديلة (إذا لم يكن التصحيح الفوري ممكناً):
1. طبّق آليات انتهاء المهلة الزمنية على عمليات المحلل
2. نشّر تحديد معدل على نقاط نهاية معالجة مخرجات LLM
3. أضف مراقبة CPU/الذاكرة مع قواطع دوائر تلقائية لعمليات المحلل
4. طبّق الكشف عن حقن الأوامر والتصفية قبل وصول مخرجات LLM إلى المحلل
5. استخدم قواعد جدار الحماية لتطبيقات الويب للكشف عن أنماط ReDoS

قواعد الكشف:
1. راقب أوقات تنفيذ المحلل التي تتجاوز 5 ثوان
2. تنبيهات على ارتفاعات CPU المتزامنة مع عمليات محلل LangChain
3. سجل وحلل مدخلات MRKLOutputParser.parse() بحثاً عن أنماط regex مريبة
4. طبّق قواعد SIEM للكشف عن محاولات التحليل الفاشلة المتكررة
5. راقب الأنماط مثل الشرطات المائلة المفرطة والمحددات المتداخلة في مخرجات الأدوات
📋 Regulatory Compliance Mapping
🟢 NCA ECC 2024
ECC 2024 A.12.6.1 - Management of technical vulnerabilities ECC 2024 A.12.2.1 - Change management procedures ECC 2024 A.5.2.1 - Information security policies and procedures ECC 2024 A.12.1.2 - Monitoring and testing of information systems
🔵 SAMA CSF
SAMA CSF ID.BE-1 - Business Environment SAMA CSF PR.IP-12 - Information and Output Media Protection SAMA CSF DE.CM-1 - Detection and Analysis SAMA CSF RS.MI-1 - Incident Mitigation
🟡 ISO 27001:2022
ISO 27001:2022 A.12.2.1 - Change management ISO 27001:2022 A.12.6.1 - Management of technical vulnerabilities ISO 27001:2022 A.14.2.1 - Secure development policy ISO 27001:2022 A.8.1.3 - Segregation of duties
🟣 PCI DSS v4.0.1
PCI DSS 6.2 - Security patches and updates PCI DSS 11.2 - Vulnerability scanning PCI DSS 6.5.1 - Injection flaws
📦 Affected Products / CPE 1 entries
langchain:langchain
📊 CVSS Score
7.5
/ 10.0 — High
📊 CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Attack VectorN — None / Network
Attack ComplexityL — Low / Local
Privileges RequiredN — None / Network
User InteractionN — None / Network
ScopeU — Unchanged
ConfidentialityN — None / Network
IntegrityN — None / Network
AvailabilityH — High
📋 Quick Facts
Severity High
CVSS Score7.5
CWECWE-1333
EPSS0.08%
Exploit ✓ Yes
Patch ✓ Yes
Published 2026-01-12
Source Feed nvd
Views 5
🇸🇦 Saudi Risk Score
7.8
/ 10.0 — Saudi Risk
Priority: HIGH
🏷️ Tags
exploit-available CWE-1333
Share this CVE

💬 Comments

0
Loading comments
📣 Found this valuable?
Share it with your cybersecurity network
in LinkedIn 𝕏 X / Twitter 💬 WhatsApp ✈ Telegram
🍪 Privacy Preferences
CISO Consulting — Compliant with Saudi Personal Data Protection Law (PDPL)
We use cookies and similar technologies to provide the best experience on our platform. You can choose which types you accept.
🔒
Essential Always On
Required for the website to function properly. Cannot be disabled.
📋 Sessions, CSRF tokens, authentication, language preferences
📊
Analytics
Help us understand how visitors use the site and improve performance.
📋 Page views, session duration, traffic sources, performance metrics
⚙️
Functional
Enable enhanced features like content personalization and preferences.
📋 Dark/light theme, font size, custom dashboards, saved filters
📣
Marketing
Used to deliver content and ads relevant to your interests.
📋 Campaign tracking, retargeting, social media analytics
Privacy Policy →
CISO AI Assistant
Ask anything · Documents · Support
🔐

Introduce Yourself

Enter your details to access the full assistant

Your info is private and never shared
💬
CyberAssist
Online · responds in seconds
5 / 5
🔐 Verify Your Identity

Enter your email to receive a verification code before submitting a support request.

Enter to send · / for commands 0 / 2000
CISO AI · Powered by Anthropic Claude
✦ Quick Survey Help Us Improve CISO Consulting Your feedback shapes the future of our platform — takes less than 2 minutes.
⚠ Please answer this question to continue

How would you rate your overall experience with our platform?

Rate from 1 (poor) to 5 (excellent)

🎉
Thank you!
Your response has been recorded.