AI Red Teaming & Offensive Security Services

AI is no longer experimental. It's driving decisions, powering critical infrastructure, and deeply integrated into business workflows. But as organizations adopt AI, the threat landscape is evolving even faster.At NotLAN, we go far beyond model-level testing. We deliver full-spectrum AI Red Teaming and offensive security assessments targeting both the models and the environments where they live.We don’t just test prompts. We simulate adversaries.

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Open laptop on a dimly lit desk showing threat metrics and graphs, with additional data screens blurred in the background.
Tablet on a wooden desk displaying a futuristic AI control interface with a glowing neural network diagram and blurred data charts on a second screen.

AI Red Teaming

• Jailbreaks, prompt injections, prompt leaking, and instruction manipulation
• Model extraction, training data inference, and membership attacks
• Alignment bypass and ethical guardrail evasion
• Abuse of retrieval-augmented generation (RAG) pipelines
• Supply chain compromise targeting model artifacts, APIs, and dependencies

Cybersecurity engineer conducting penetration testing in a dark server room, typing code on multiple monitors with real-time security dashboards and rack-mounted hardware glowing in blue.

Environment & Application Layer Testing

• Web interfaces, chatbots, and orchestration layers
• API endpoints, business logic vulnerabilities, and data brokers
• Improper input validation allowing injection attacks (SQLi, NoSQLi, XPathi, GraphQL)
• Access control flaws such as IDORs and authorization bypass
• Injection and client-side attacks such as XSS, CSRF, SSRF
• Misconfigured backend services and cloud-native attack surfaces

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Adversary Emulation for AI Systems

• Full-scale emulation of real-world adversaries targeting AI systems
• Attack chains mapped to MITRE ATLAS tactics & techniques
• Customized offensive scenarios using our proprietary AI Red Teaming Framework
• Multi-step simulations reflecting emerging AI threat actors and campaigns

Graphic illustrating adversary emulation for AI systems: a layered shield with an AI head silhouette and neural network, surrounded by red threat icons (bugs and warning triangles) and a flowchart labeled “MITRE ATLAS” on a dark circuit-patterned background.

Methodologies Backed by Industry Standards

Our assessments align with the most authoritative AI security frameworks:
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• OWASP Top 10 for LLM Applications (OWASP LLM Top 10)
• MITRE ATLAS (Adversarial Threat Landscape for AI Systems)

We continuously map our offensive techniques to these standards, ensuring your AI deployments are tested against cutting-edge adversarial tactics, not hypothetical checklists.

Neon-gradient graphic showing a layered shield with an AI head silhouette and neural network inside, surrounded by threat icons (warning triangle, bug) and a flowchart, symbolizing methodologies aligned with OWASP LLM Top 10 and MITRE ATLAS.

Why AI Red Teaming Is No Longer Optional

• AI is already making autonomous decisions that affect customers, legal outcomes, transactions, and critical infrastructure.
• Emerging attackers are actively targeting LLMs, multi-agent systems, RAG pipelines, and data integrations.
• The risks are not just in the model, they're in every layer where data flows, users interact, and outputs are consumed.
• Increasing regulatory pressure demands proactive security validation for AI deployments.

If you are deploying AI, you are exposing new risks. The only safe AI is an AI that has been attacked before your adversaries do.

Cybersecurity professional at a dimly lit desk reviewing AI red teaming dashboards on dual monitors—one showing neural network visuals and threat alerts, the other displaying a contract and an “ALERT” warning icon—while a printed contract lies on the desk.

Why Work With Us?

✅ We built and operate the AI Red Teaming Framework, battle-tested for executing full adversarial attack chains across models and environments.

✅ We combine offensive security expertise, AI research, and real-world adversary simulation into one unified methodology.

✅ We test your entire AI attack surface from prompt to backend, from model to business logic, from input to impact.

Two cybersecurity engineers at a dark desk collaborating on AI red teaming: one points at a monitor displaying neural network visuals and threat alerts while the other types code, with a printed report on the desk.