Secure AI. Protect Data. Minimize Risk.
At Cyberintelsys Consulting Services, we offer specialized LLM Penetration Testing Services to assess the security posture of AI-driven applications that utilize Large Language Models (LLMs) like ChatGPT, Bard, Claude, or custom enterprise AI solutions. Our experts simulate real-world attacks against your AI systems to uncover vulnerabilities specific to LLMs, such as prompt injection, data leakage, and unauthorized access, ensuring your AI solutions remain secure, compliant, and trusted.











LLM Penetration Testing is a focused security assessment designed to identify vulnerabilities unique to AI systems powered by Large Language Models. It simulates adversarial scenarios to assess how your AI models, APIs, and integrated applications could be exploited by attackers. This testing is crucial for organizations adopting AI to protect sensitive data, maintain compliance, and mitigate AI-specific security risks.

Identify AI-Specific Threats
Uncovers vulnerabilities such as prompt injection, data leakage, and unauthorized access through LLM interactions.
Secure Sensitive Data
Ensures AI systems do not inadvertently expose confidential, regulated, or proprietary information.
Prevent Model Manipulation
Detects risks where attackers could manipulate LLM outputs for malicious purposes.
Meet Compliance Requirements
Supports alignment with emerging AI security guidelines and industry standards (NIST AI RMF, ISO/IEC 42001, etc.).
A secure LLM environment starts with identifying and mitigating risks across every layer—inputs, outputs, and underlying logic.
Prompt Injection Attacks
Jailbreak & Evasion Techniques
Data Leakage via Responses
Over-Privileged LLM Integrations
Misconfigured APIs & Permissions
Supply Chain Risks in AI Workflows
Model Abuse for Social Engineering / Fraud
Unauthorized Function Calls via LLMs
Insecure Plugins, Extensions, or Tools Access

Understand the AI solution’s architecture, LLM providers, integrations, API exposure, and security objectives. Clearly define the scope to include LLM APIs, applications, and backend systems.


Assess potential attack surfaces, including user interactions, APIs, plugins, and integrations with other systems.
Conduct controlled testing for LLM-specific vulnerabilities using both manual and automated techniques. Validate protections against prompt injections, jailbreaks, and data exposure.


Simulate real-world adversarial attacks targeting your AI systems to demonstrate exploitation paths and business impact.
Analyze the consequences of successful attacks, such as unauthorized access, sensitive data leakage, or reputational damage.


Deliver detailed reports outlining vulnerabilities, severity, risk impact, and actionable mitigation strategies for securing your LLM environments.
Retest after remediation and provide ongoing support for securing AI systems against evolving threats.

Your trusted advisor in penetration testing . Safeguard your digital assets – get in touch today!
Our clients rely on us to secure their critical applications and protect their data. Hear what they have to say about our expertise, dedication, and the impact of our web application penetration testing services.

The team transformed our brand's online presence with creativity & precision.The results exceeded our expectations! Their digital marketing strategies helped us reach a broader audience & significantly boosted our sales

The team transformed our brand's online presence with creativity & precision.The results exceeded our expectations! Their digital marketing strategies helped us reach a broader audience & significantly boosted our sales

The team transformed our brand's online presence with creativity & precision.The results exceeded our expectations! Their digital marketing strategies helped us reach a broader audience & significantly boosted our sales

The team transformed our brand's online presence with creativity & precision.The results exceeded our expectations! Their digital marketing strategies helped us reach a broader audience & significantly boosted our sales
Strengthen AI Security Posture
Identify and mitigate LLM-specific vulnerabilities before exploitation occurs.
Protect Sensitive Data & IP
Ensure AI models do not leak confidential information through unintended prompts or outputs.
Regulatory & Compliance Alignment
Support compliance with AI-specific standards, data protection laws, and enterprise security frameworks.
Reduce Business & Legal Risks
Minimize potential reputational, financial, and legal damage from AI misuse or exploitation.
Enhance Customer Trust
Demonstrate proactive security measures for AI-driven products and services.
Black Box Testing
Simulates external attackers without knowledge of internal systems to assess public-facing LLM security.
White Box Testing
Analyzes source code, APIs, and configurations with full knowledge to identify deeper vulnerabilities.
Gray Box Testing
Combines external and limited internal knowledge to assess realistic threat scenarios, including insider risks.

First-Time Penetration Testing Buiyer Guide
Read the essential with our go-to guide to your first penetration test, everything you need to know to make an informed and successful investment in your security

First-Time Penetration Testing Buiyer Guide
Read the essential with our go-to guide to your first penetration test, everything you need to know to make an informed and successful investment in your security

First-Time Penetration Testing Buiyer Guide
Read the essential with our go-to guide to your first penetration test, everything you need to know to make an informed and successful investment in your security

First-Time Penetration Testing Buiyer Guide
Read the essential with our go-to guide to your first penetration test, everything you need to know to make an informed and successful investment in your security

First-Time Penetration Testing Buiyer Guide
Read the essential with our go-to guide to your first penetration test, everything you need to know to make an informed and successful investment in your security
Our structured, step-by-step process ensures every LLM vulnerability is identified, risks are prioritized, and your systems stay protected from evolving threats. From scoping to final validation, we enhance your AI security posture.
1. Initial Consultation & Requirement Gathering
Identify business objectives, critical data flows, and AI-related risks.
2. Scoping & Planning
Define the LLM systems, APIs, plugins, and integrations to be tested, aligned with business and security priorities.
3. Reconnaissance & Enumeration
Map exposed AI interfaces, plugins, and data flows to understand potential attack surfaces.
4. Adversarial Testing & Exploitation
Conduct controlled tests for LLM-specific threats, including prompt injection, abuse of functions, and data leakage.
5. Impact Assessment
Evaluate the impact of successful exploitation on data, systems, and business operations.
6. Reporting & Actionable Guidance
Deliver comprehensive reports with vulnerabilities, severity ratings, remediation guidance, and security hardening strategies.
7. Debrief & Retesting Support
Present findings, support remediation efforts, and validate fixes through retesting.
Protect Your Business from Emerging Cyber Threats
Cyberintelsys helps you stay one step ahead of today’s advanced cyber risks. Our expert-led penetration testing and security assessments are designed to identify vulnerabilities before attackers do — helping you strengthen your security posture and meet compliance standards. Fill out the form, and we’ll get back to you with a tailored solution.
Frequently Asked Questions
LLMs introduce new attack surfaces that traditional security testing does not cover. Testing helps prevent data leaks, manipulation, and AI-driven exploits.
Depending on scope and complexity, engagements typically range from 2 to 4 weeks.
We ensure controlled, non-destructive testing and recommend using staging environments where possible.
Detailed reports with findings, risk analysis, exploit examples, remediation advice, and executive summaries.
Regularly – ideally after major AI feature updates, model upgrades, or changes to AI integrations.