Adversarial AI Pentesting
Secure the brain of your enterprise. We provide specialized security audits for Large Language Models (LLMs) and ML pipelines to prevent poisoning, theft, and prompt injection.
Securing the New Attack Surface
As organizations integrate AI into their core products, they open a new frontier of vulnerabilities. Traditional firewalling and code review cannot detect "prompt injection" or "model inversion"—exploits that target the very logic of the neural network.
ARM Innovations uses cutting-edge adversarial ML research to stress-test your AI systems. From LLM-based customer support bots to proprietary financial prediction models, we ensure your AI is robust, ethical, and safe from adversarial manipulation.
- LLM Prompt Injection (Direct/Indirect)
- Training Data Poisoning Simulations
- Adversarial Example Generation
- AI Governance & Safety Alignment
Intelligence-Led Frameworks
We use the world's most advanced AI security standards to benchmark your model's resistance to attack.
OWASP ML Top 10
Auditing for critical machine learning risks including data poisoning, model inversion, and membership inference.
MITRE ATLAS™
Applying the Adversarial Threat Landscape for AI Systems to model TTPs specific to machine learning pipelines.
Prompt Injection (LLM)
Deep-dive testing for direct and indirect prompt hacking in Large Language Model applications.
NIST AI RMF
Ensuring your AI systems align with the NIST AI Risk Management Framework for security and trustworthiness.
The AI Security Lifecycle
Model Topology Analysis
Understanding the neural network architecture, training data sources, and deployment environment.
Adversarial Input Testing
Crafting 'adversarial examples'—subtly modified inputs that bypass safety filters and cause misclassification.
Data Poisoning Simulation
Evaluating the vulnerability of the training pipeline to malicious data injection that could create backdoors.
Model Extraction Defense
Testing if a competitor could 'steal' your proprietary model logic through structured API queries.
Compliance & Ethical Audit
Measuring model bias and ensuring alignment with emerging global AI regulations (EU AI Act).
AI Vulnerabilities Targeted
Build AI You Can Trust
Don't let adversarial attacks compromise your business logic. Secure your AI/ML ecosystem with forensic precision.