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Leader
Identify, prioritize, and reduce AI security risks that impact business, compliance, and accountability.
Make informed decisions about AI governance, vendor risk, and real-world threat exposure.
Practitioner
Secure AI and ML systems against real attacks with practical techniques, architectures, and controls.
Learn how to test, harden, and operate AI systems safely in production.
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Stay ahead of emerging AI security threats with curated, actionable insights.
Each issue helps you decide what to fix, change, or challenge in your AI strategy.
Community
Learn from peers solving real AI security problems in production environments.
Exchange lessons, discuss incidents, and improve how AI is designed and defended.
Get expert support to secure your AI systems
Protect your AI and ML applications from vulnerabilities, attacks, and data breaches with expert security solutions tailored for development teams and IT decision-makers.
The biggest ML Security risks
Your ML models are valuable business assets that need protection. Secure them against attacks that can steal proprietary algorithms, manipulate outcomes, or expose sensitive data. Don’t just meet regulatory requirements—safeguard your competitive edge and customer trust. Because when AI powers your business, security isn’t optional.
Model Theft
Competitors can steal your proprietary algorithms through extraction attacks. Your valuable intellectual property requires specialized protection beyond traditional security.
Data Poisoning
Attackers can corrupt your training data to manipulate model outputs. Even small, undetected manipulations can cause your ML systems to make dangerous decisions.
Adversarial Attacks
Specially crafted inputs can trick your ML models into misclassifications or incorrect predictions. These attacks bypass normal accuracy metrics while targeting specific vulnerabilities.
About Us
We believe that ML security knowledge should be accessible to all organizations building AI systems. Our mission is to demystify machine learning security, equip teams with practical defenses against emerging threats, and foster a community where security best practices evolve alongside AI innovation.
ML Security should be a standard, not an exception.
Adrian Sroka
Software Security AI Architect