
HiddenLayer AI Detection and Response (AIDR)HiddenLayer
Ensure deployments remain secure by preventing data leaks, malicious use, and compliance risks, protecting enterprise IP and enabling safe adoption at scale.
Vendor
HiddenLayer
Company Website

HL_AI Dete… Datasheet.pdf
Product details
HiddenLayer AI Detection & Response (AIDR) is a purpose-built solution for securing agentic and generative AI applications at scale. It integrates seamlessly with existing security infrastructure to deliver real-time visibility, detection, and response without exposing proprietary model data or disrupting operations. Designed for enterprises adopting AI, AIDR ensures resilience, compliance, and safe innovation.
Features
- Real-Time Protection: Blocks prompt injection, PII leakage, malicious agent behavior, and privilege escalation.
- Threat Mitigation: Continuous risk monitoring across the MLOps lifecycle with alerts mapped to MITRE ATLAS and OWASP LLM standards.
- Regulatory Compliance: Supports leading LLMs and agent frameworks (OpenAI, Anthropic, Azure, GCP, Meta, Mistral, AWS Bedrock) and aligns with NIST, EU AI Act, ISO 42001, and Fed standards.
- Advanced Detection: Uses supervised, unsupervised, behavioral, and static analysis to identify adversarial AI attacks.
- Model Theft Prevention: Blocks reconnaissance and inference-based extraction attempts.
- Model Tampering Protection: Detects and prevents unauthorized changes to model layers or components.
- Data Poisoning Defense: Stops adversaries from corrupting training or inference data.
- Prompt Injection Defense: Prevents malicious inputs and context manipulation from hijacking workflows.
Benefits
- Enterprise Resilience: Protects critical IP and ensures operational continuity.
- Compliance Assurance: Streamlines audits and governance adherence.
- Risk Reduction: Accelerates remediation and minimizes downtime.
- Safe AI Adoption: Enables secure deployment of agentic and generative AI across all use cases.
- Comprehensive Coverage: Guards against evolving threats like inference attacks, memory corruption, and tool misuse.
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