AI Security Assessment

Secure Your AI Systems

Comprehensive security assessment for AI and machine learning systems including model security, training data protection, and AI infrastructure security.

AISecurityML

What's Included

Comprehensive service features designed to meet your security and development needs.

Model Security Testing

Test AI models for adversarial attacks, model extraction, and poisoning attempts.

Training Data Security

Validate training data integrity, privacy, and protection against data poisoning.

AI Infrastructure Audit

Security assessment of ML pipelines, model serving, and AI infrastructure.

Bias & Fairness Testing

Identify algorithmic bias, fairness issues, and discriminatory outputs.

Key Benefits

Why organizations choose this service

Prevent AI model theft and exploitation

Protect sensitive training data

Ensure fair and unbiased AI systems

Meet AI governance requirements

AI Security Assessment Methodology

Our proven methodology for delivering ai security assessment

1
01

AI System Architecture Analysis

Map AI/ML system architecture including training pipelines, model serving infrastructure, data sources, API endpoints, and understand model lifecycle from training to production deployment.

2
02

Model Security Testing

Test for adversarial attacks including evasion attacks, model inversion, membership inference, model extraction attempts, and backdoor triggers in trained models.

3
03

Training Data Security Assessment

Evaluate training data protection, test for data poisoning vulnerabilities, validate data provenance and integrity, assess privacy preserving ML implementations, and review data governance.

4
04

AI Infrastructure & Pipeline Security

Audit ML pipeline security, test model registry access controls, review MLOps security, validate container and dependency security, and assess secrets management for API keys and credentials.

5
05

Bias, Fairness & Explainability Testing

Test for algorithmic bias across protected characteristics, evaluate model fairness metrics, assess discriminatory outputs, review model explainability, and validate AI ethics compliance.

6
06

AI Specific Threat Modeling

Conduct threat modeling specific to AI systems, identify attack vectors unique to ML, assess business impact of AI failures, and evaluate AI supply chain risks.

7
07

Reporting & AI Security Recommendations

Deliver comprehensive AI security report with OWASP ML Top 10 mapping, provide model robustness recommendations, AI governance guidance, and secure ML deployment best practices.

Ready to Get Started?

Contact us today to discuss your ai security assessment needs and receive a custom proposal.