Your AI Guardrails need an Adversary
Pressure-test AI chatbots, copilots, applications, and agents with realistic prompt attacks. Identify where safety, security, and business controls can be bypassed before attackers, users, or model changes expose those weaknesses.
Securing AI Risk Vectors
Automated adversarial testing for AI models, apps, and agents, structured around three core categories of AI risk management.
Safety
Some AI attack vectors revolve around triggering AI agents to produce unsafe content, potentially leading to direct or reputational harm.
Security
Threat actors may use AI agents as a vulnerability when pursuing traditional objectives such as remote code execution or sensitive data compromise.
Responsibility
AI solutions also pose an inherent risk of misaligned responses if not provisioned with appropriate guardrails and guidance.
Find Weaknesses Before They Become Incidents
AI systems can behave unpredictably even when the surrounding infrastructure is secure. Harbour AI Red Teaming helps organizations understand how their AI applications, models, copilots, and agents respond under adversarial pressure, uncovering weaknesses that traditional security assessments may not detect.
By testing real-world attack paths against your specific use cases and guardrails, ADS helps your team reduce uncertainty, strengthen controls, and make more informed decisions as AI adoption expands.
Put your AI environment to the test
AI systems introduce risks that traditional security testing was never designed to uncover. ADS Harbour Red Teaming challenges AI applications, copilots, models, and agents with realistic adversarial techniques to identify where safeguards can be bypassed, sensitive information exposed, or connected capabilities misused.
Built around your system’s actual purpose, users, and business requirements, each assessment helps you uncover meaningful weaknesses, prioritize remediation, and validate that your AI controls hold up under pressure.
Prompt Injection
Test whether malicious or manipulative prompts can override intended behavior, bypass controls, or expose restricted information.
Multi-Turn Attacks
Simulate longer conversations where an attacker gradually steers the model toward unsafe behavior or works around safeguards over time.
Context-Aware Testing
Build attacks around your AI system’s actual purpose, users, capabilities, and restrictions for more realistic validation.
Obfuscation & Evasion
Test whether paraphrasing, encoding, roleplay, or other indirect techniques can slip past established guardrails.
Expose AI-Specific Risk
Identify whether AI systems can be manipulated into revealing confidential information, protected data, or internal system details.
System Prompt Leakage
Determine whether users can uncover hidden instructions, system prompts, or other information intended to remain behind the scenes.
Tool & Agent Misuse
Test whether connected tools, integrations, and agent capabilities can be triggered or manipulated in unintended ways.
Unsafe Outputs
Evaluate the system for harmful, inappropriate, misleading, or otherwise prohibited responses that could create business or reputational risk.
Custom Attack Objectives
Tailor testing around the risks that matter most to your organization, from data leakage and policy violations to unauthorized actions.
Secure your AI future Today
Atlantic Data Security's team of cybersecurity experts is ready to help
you navigate the evolving threat landscape.
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Choose ADS.
ADS provides complete cybersecurity solutions and services to help organizations protect their digital assets. When you work with us, you’re working with a company dedicated to elevating your cybersecurity strategy to meet the challenges of tomorrow, today.
