Specialized Security Assessments
AI Security Assessment
As organizations embed machine learning and generative AI into core products, the attack surface extends beyond code to data, models and pipelines.
What's Included
- Data Poisoning Defense Review: assessment of training and fine-tuning data pipelines for poisoning, mislabeling and backdoor-injection risk
- Model Manipulation & Adversarial Robustness: testing model resilience against adversarial inputs, evasion attacks and manipulation of inference outputs
- Model Theft & Extraction Protection: evaluation of controls against model extraction, weight theft and unauthorized replication via API abuse
- MLOps Pipeline Security Review: security review of training, deployment and CI/CD pipelines for ML artifacts, including access control and provenance tracking
- Access Control & Watermarking Assessment: review of model access governance, usage monitoring and watermarking/traceability controls
- Governance Alignment: gap assessment against the NIST AI Risk Management Framework and ISO/IEC 42001 AI management system standard
Relevant Frameworks/Standards
NIST AI Risk Management Framework
ISO/IEC 42001
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Tell us about your environment, timeline and objectives — we'll follow up with a tailored, fixed-fee proposal.