1. AI & LLM Security Assessment
Assess artificial intelligence systems and large language models for security vulnerabilities, data leakage, and adversarial threats. Identify potential risks and recommend security controls to protect AI applications, sensitive information, and business operations.
2. Prompt Injection Testing
Evaluate AI applications for prompt injection vulnerabilities that could manipulate model behavior or bypass security controls. Identify weaknesses in instruction handling and recommend safeguards against unauthorized actions and sensitive data exposure.
3. AI Agent Security Assessment
Assess autonomous AI agents for insecure tool integrations, excessive permissions, and unauthorized system interactions. Strengthen agent security through access control validation, workflow testing, and risk-based remediation recommendations.
4. AI Governance Review
Evaluate AI policies, risk management practices, and organizational controls against recognized AI governance frameworks. Support responsible AI adoption through security oversight, regulatory alignment, accountability, and continuous risk monitoring.
5. AI Model & Data Security Assessment
Assess AI models, training datasets, and inference pipelines for data poisoning, model manipulation, and information leakage. Protect AI assets through secure data handling, model integrity validation, and recommended security controls.