Pillar Security
Platform to secure and manage the entire AI lifecycle.
Pricing
About Pillar Security
Pillar Security is a comprehensive platform designed to identify, assess, and mitigate security risks across the entire AI software lifecycle. It provides automated and continuous discovery of all AI assets, integrating directly with code, data, and cloud platforms. The platform offers unmatched visibility, robust control, and resilient defense mechanisms to protect AI systems from emerging threats. It is led by an expert team with backgrounds in cybersecurity, threat intelligence, and AI, and aims to help organizations build and run secure, trustworthy AI solutions from development to deployment.
Who It's For
- •AI development teams and data scientists.
- •Cybersecurity professionals and threat analysts.
- •Organizations deploying AI solutions at scale.
- •Compliance and security managers overseeing AI systems.
- •Cloud security teams managing AI infrastructure.
How It Works
- 1Automated discovery and inventory of all AI assets across environments.
- 2Integration with code repositories, data sources, and cloud platforms for comprehensive security oversight.
- 3Risk assessment tools that simulate attack scenarios and identify security gaps.
- 4Continuous monitoring and threat modeling to mitigate vulnerabilities in real-time.
- 5Provides security controls and best practices tailored for the AI lifecycle.
How to Use Pillar Security
- 1Register and set up the platform with access to your AI development and deployment environments.
- 2Allow the platform to automatically discover and inventory AI assets.
- 3Perform a risk assessment to identify vulnerabilities and security gaps.
- 4Utilize the security controls and best practices recommended by the platform.
- 5Continuously monitor AI systems for threats and respond to any security incidents.
Key Features
- •Automated discovery and asset inventory.
- •AI lifecycle risk assessment and threat modeling.
- •Integration with cloud, code, and data platforms.
- •Real-time monitoring and security alerts.
- •Guided security best practices for AI systems.
Use Cases
- •Securing AI development environments from cyber threats.
- •Continuously monitoring AI models and datasets for security risks.
- •Assessing security posture and identifying vulnerabilities in AI applications.
- •Implementing security controls during AI deployment and operation.
- •Threat modeling and response planning for AI systems.
Pros & Cons
Advantages
- •Comprehensive coverage of AI security throughout the lifecycle.
- •Automated discovery reduces manual overhead and errors.
- •Expert-led insights and risk assessment capabilities.
- •Integration with multiple environments for wide applicability.
Disadvantages
- •May require technical expertise to utilize fully.
- •Potentially costly for small organizations.
- •Details on specific features and user interface are limited.
Alternatives
- IBM Watson OpenScale
- Microsoft Azure AI Security
- Google Cloud AI Security Suite
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Please note: While we regularly update all tool information including descriptions, features, pricing, and other details, this information may change over time as tools evolve and update their offerings. For the most current and accurate information, we recommend visiting the official website directly. Our goal is to provide you with comprehensive and up-to-date information to help you make informed decisions.