HiddenLayer offers a software platform that monitors the inputs and outputs of machine learning models to protect against adversarial attacks, model theft, and data exposure. By utilizing the MITRE ATLAS framework, it provides real-time awareness of model health without requiring access to raw data or algorithms, ensuring the security of proprietary AI assets.
Funding
$55.8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
MMMSFounders
Product
Problem
Organizations deploying AI and machine learning models face increasing risks from adversarial attacks, model theft, data poisoning, and other security threats that can compromise model integrity and business advantage. Traditional security measures often lack visibility into model behavior and require access to sensitive data, creating complexity and potential data exposure.
Solution
HiddenLayer provides a security platform designed to protect AI models from a range of threats without requiring access to the underlying data or algorithms. The platform offers real-time monitoring of model inputs and outputs, enabling organizations to detect and respond to suspicious activity and potential attacks. By leveraging the MITRE ATLAS framework, HiddenLayer delivers comprehensive AI security, including automated red teaming, threat detection and response, and model scanning, ensuring the integrity and security of AI assets across various industries.
Target Audience
The primary target audience includes enterprises in finance, public sector, and technology that are deploying AI and machine learning models and need to protect them from adversarial attacks and other security threats.
Features
- AI Detection & Response: Monitors and responds to suspicious activity around AI assets in real time.
- Automated Red Teaming for AI: Simulates adversarial attacks on AI systems to identify vulnerabilities proactively.
- Model Scanner: Discovers and assesses AI assets to maintain a strong security posture.
- Automated Reporting: Validates security across enterprise AI models with comprehensive reporting.
- Non-invasive monitoring: Secures AI models without requiring access to raw data or algorithms.
- Threat Mitigation: Proactively mitigates cybersecurity risks in real-time as part of the MLOps lifecycle, mapping alerts to the MITRE ATLAS and LLM OWASP frameworks.
- Real-time Protection: Ensures systems are resistant to prompt injection attacks, PII leakage, and model theft.