Identify. Exploit. Secure.

Red Team for AI/LLM Systems

 

Attack. Expose. Strengthen.


At Cyberintelsys Consulting Services, our Red Team for AI / LLM Systems simulates real-world adversarial attacks against AI-powered applications and Large Language Models (LLMs) to uncover security, safety and misuse risks before attackers do. We go beyond traditional testing to evaluate how AI systems behave under hostile, deceptive and abuse-driven scenarios, helping organizations build robust, resilient and trustworthy AI systems.

Red Team
Brands We Helped Secure Through Their VDP Programs
What is Red Teaming for AI/LLM Systems?

AI / LLM Red Teaming is an adversarial assessment that simulates real attackers attempting to manipulate or abuse AI systems. It helps identify prompt injection, jailbreaks, data leakage and control weaknesses while testing AI decision logic. Unlike traditional VAPT, it focuses on behavioral exploitation and emerging AI risks.

Red Team for AI LLM

Real-World Attack Simulation

Test AI systems against realistic attacker behavior, including malicious prompts, deception and misuse scenarios.

Early Detection of AI-Specific Risks

Identify risks such as prompt injection, jailbreaks, hallucination abuse, unsafe outputs and data leakage.

Stronger AI Safety & Trust

Ensure AI systems behave predictably, safely and within defined governance boundaries.

Why AI Systems Require Red Teaming

AI systems introduce new and unique attack surfaces that traditional security testing does not fully address.

Our AI / LLM Red Team Assessments cover:

Prompt injection and indirect prompt injection attacks

Jailbreak techniques and guardrail bypass attempts

Training data inference and sensitive data leakage

Abuse of AI agents, plugins and tool integrations

Unauthorized actions via AI-driven automation

Multi-step attack chains using AI reasoning

Cross-system impact triggered by AI outputs

Misuse of AI APIs and rate-limiting weaknesses

Red Teaming for AI systems
Our Red Team for AI/LLM Systems Approach

At Cyberintelsys, we strengthen AI and LLM systems through Red Team assessments, simulating real-world attacks to uncover weaknesses, reduce abuse risks and improve overall AI security and resilience.

We define AI assets, models, applications, integrations, use cases and risk tolerance.

We identify AI-specific threat scenarios including misuse, abuse, deception and adversarial manipulation.

We execute controlled red team attacks against AI prompts, APIs, agents and workflows using realistic attacker techniques.

We assess the effectiveness of guardrails, moderation systems, access controls and misuse detection mechanisms.

We evaluate business, legal, safety and reputational impact of successful AI exploitation.

You receive a detailed report outlining attack scenarios, findings, severity, impact and prioritized remediation actions.

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Client Experiences With Our Testing Process

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.

Improved AI Safety & Alignment

Validate guardrails, safety policies and usage constraints

Reduced AI Abuse & Misuse Risk

Identify and mitigate harmful or unintended AI behaviors

Data Protection & Privacy Assurance

Prevent leakage of sensitive or proprietary information

Operational AI Risk Reduction

Prevent costly AI failures, automation errors and trust erosion

Stronger Stakeholder Confidence

Demonstrate proactive AI risk management to customers and regulators

Regulatory Readiness

Support alignment with NIST AI RMF, ISO/IEC 42001, EU AI Act and internal AI governance programs

Benefits of Red Teaming for AI/LLM Systems
Types of AI Red Teaming We Offer

Prompt & Interaction Red Teaming

 

Focuses on prompt injection, jailbreaks, deception and instruction manipulation.

 

Application-Level AI Red Teaming

 

Assesses strategic AI-powered applications, chatbots, copilots, agents and workflows.

 

API & Integration Red Teaming

 

Evaluates risks from AI APIs, plugins, tools and external third-party integrations.

 

Explore Our Important Resources And Reports
Our Proven Process for AI/LLM Red Teaming

Our structured Red Team process simulates real-world attacks to identify AI weaknesses, validate defenses and strengthen the security and resilience of your AI and LLM systems.

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.

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    Frequently Asked Questions

    Quick Answers to Your AI/LLM Red Teaming Concerns

    Before production deployment, after major model updates, when deploying AI agents or when expanding AI use cases.

    No. AI Red Teaming focuses on adversarial behavior, misuse and safety failures, while AI penetration testing focuses on technical vulnerabilities.

    No. All testing is performed in controlled environments under agreed rules of engagement.

    Prompt injection, jailbreaks, unsafe outputs, data leakage, automation abuse and AI-driven logic flaws.

    A comprehensive AI / LLM Red Team Report with attack scenarios, exploit paths, impact assessment, and prioritized remediation guidance.