AI Security
Your AI systems are your most valuable — and most vulnerable — enterprise assets. Cybernonics protects the models, pipelines, and data that power your competitive advantage from an entirely new class of adversarial threats that traditional security tools cannot see.
68%
of enterprises have experienced an AI-specific security incident
$12M+
average value of a stolen enterprise AI model
300%
increase in adversarial AI attacks since 2022
91%
of AI models deployed without adversarial testing
AI Has Created a New Attack Surface
Traditional cybersecurity was designed to protect networks, endpoints, and applications. It was not designed to protect machine learning models, training pipelines, or inference APIs. Your AI stack has unique vulnerabilities that require specialized expertise.
Every AI model you deploy is a potential attack vector. Cybernonics closes the gap between AI innovation and AI security.
AI-Specific Threat Vectors
Six categories of AI-specific attacks your security team must be prepared to defend against.
Adversarial Attacks
Subtle input manipulations that cause AI models to make catastrophically wrong decisions — invisible to humans, devastating in production.
Model Theft & Extraction
Competitors and nation-state actors systematically querying your AI APIs to reconstruct proprietary models worth millions in R&D investment.
Training Data Poisoning
Malicious actors corrupting training datasets to embed backdoors or biases that activate under specific conditions — often undetected for months.
Model Inversion Attacks
Reverse-engineering sensitive training data from model outputs — exposing PII, trade secrets, and confidential business information.
Supply Chain AI Risks
Compromised open-source models, malicious pre-trained weights, and vulnerable ML libraries embedded in your production AI stack.
Prompt Injection
Attackers hijacking LLM-powered applications through crafted inputs that override system instructions and exfiltrate sensitive data.
Our AI Security Services
End-to-end protection for your AI systems — from design to production.
AI Red Teaming
Our adversarial AI specialists attack your models the way real threat actors would — identifying exploitable weaknesses before they do.
Secure ML Pipeline Design
Build security into every stage of your ML lifecycle — from data ingestion and labeling through training, validation, and deployment.
Model Monitoring & Drift Detection
Continuous surveillance of model behavior in production to detect performance degradation, adversarial manipulation, and data drift.
AI Security Architecture Review
Comprehensive assessment of your AI infrastructure, APIs, access controls, and data flows against enterprise security standards.
Is Your AI Stack Actually Secure?
Most enterprises don't know the answer. Our AI security audit delivers a complete threat assessment of your models, pipelines, and APIs — with a prioritized remediation roadmap in 5 business days.