Glaze by University of Chicago
Protects artwork from being used to train AI image models.
Security and governance tools designed specifically for AI/ML systems — adversarial attack defence, model auditing, and compliance automation
Looking for an in-depth guide?
Our curated list ranks every major AI security platform with editorial notes on use case fit.
AI Security & Compliance tools help organizations protect machine learning models from attacks, audit their behavior, and meet regulatory requirements. These tools are used by ML engineers, data scientists, and compliance teams who need to ensure their AI systems are safe, fair, and auditable. They address critical gaps in model robustness, data quality, and governance that standard security tools don't cover.
ML teams securing production models
Machine learning engineers use these tools to monitor deployed models for adversarial attacks and data drift that could degrade performance or enable exploitation.
Compliance and risk officers
Compliance professionals rely on these platforms to generate audit trails, document model decisions, and prove adherence to regulatory requirements for AI systems.
Data quality and governance teams
Data scientists and governance teams use these tools to identify poisoned training data, detect bias, and ensure dataset integrity before models are trained.
Evaluate pricing against model complexity
Compare costs based on the number of models you need to protect and the frequency of audits or monitoring required. Some tools charge per deployment while others use consumption-based pricing.
Check ease of integration with your stack
Look for tools that work with your existing ML frameworks (TensorFlow, PyTorch, Scikit-learn) and deployment platforms without requiring major code rewrites.
Verify compliance standard coverage
Confirm the tool supports the specific regulations you need to meet, such as GDPR, HIPAA, SOC 2, or industry-specific AI governance frameworks.
Test detection of adversarial threats
Assess how well the tool identifies poisoned data, model evasion attacks, and bias issues relevant to your use case before committing.
Head-to-head breakdowns for the most popular ai security & compliance tools — updated as the directory grows.
Protects artwork from being used to train AI image models.
Remove sensitive data from trained AI models without retraining.
Chaos engineering platform that tests system resilience through controlled failures.
AI incident debugging assistant integrated into Slack and Teams
Cloud security platform identifying and fixing infrastructure risks.
Private LLM API with built-in safety controls and compliance.
Compliance software helping government contractors meet federal requirements.
Protects LLM applications from prompt injection and adversarial attacks.
Protects artwork from being used to train AI image models.
Remove sensitive data from trained AI models without retraining.
Chaos engineering platform that tests system resilience through controlled failures.
AI incident debugging assistant integrated into Slack and Teams
Cloud security platform identifying and fixing infrastructure risks.
Private LLM API with built-in safety controls and compliance.
Compliance software helping government contractors meet federal requirements.
Protects LLM applications from prompt injection and adversarial attacks.