Today’s high performance computing (HPC) data centers process petabytes of information used by large language models (LLMs) for artificial intelligence (AI)-based technologies.
However, security and operations teams rely on legacy technologies to defend their high-volume, high-speed, low-latency environments. These outmoded technologies cannot keep up because they were never designed to monitor today’s HPC environments.
As a result, security and operations teams lack the real-time detection, unlimited scalability, and comprehensive observability they need to defend their HPC environments from a range of risks and attacks.
Legacy Tech Cannot Secure HPC Data Centers
Your HPC data centers and LLMs used for AI-based technologies are at risk due to the lack of observability and scalability in traditional security and network monitoring controls. For HPC data centers with workloads and data across multi-cloud platforms, legacy security infrastructure lacks a unified view of disparate data flows. On-prem data centers processing and storing petabytes of data using GPU clusters need a horizontally scalable security architecture not found in traditional security solutions.
The inability of outdated security infrastructure to keep up with the mammoth volume of data and processing speeds that HPC environments require creates significant observability gaps and performance bottlenecks. It also results in significant risks to your organization’s and your customers’ security. These risks include:
- AI Systems Compromises: Anomalous behavior, like suspicious activity patterns, unauthorized access attempts, or unusual data transfers in your HPC environments, can signal significant threats to data integrity, model security, and the overall trustworthiness of AI systems and LLMs.
- Data Poisoning: Anomalous activity could represent malicious or corrupted data injection into your LLM datasets. Such data poisoning attacks aim to manipulate the training process by introducing biased or misleading information, ultimately compromising the integrity and accuracy of your LLM’s output.
- Model Tampering: Threat actors may attempt to modify your training model or its parameters through API abuse. By injecting malicious code or altering the model’s architecture, they can manipulate your LLM’s behavior, leading to biased or distorted output during inference.
- Data Theft or Leakage: The exfiltration of sensitive or proprietary data from your LLM datasets enables threat actors to steal your valuable intellectual property, trade secrets, or confidential information used in the training process, posing significant risks to your competitiveness and reputation.
- Data Integrity Compromise: Unusual data transfers may also result from unintentional errors or data corruption within your LLM datasets. These integrity issues could arise from software flaws or hardware failures, leading to inconsistencies or inaccuracies in the training data and affecting the reliability of your LLM’s predictions.
Netography Fusion Enables Real-Time Detection at Scale for HPC Environments
Netography Fusion® is engineered to meet the extreme performance requirements of your multi-cloud and on-prem HPC environments. It delivers the horizontally scalable architecture, continuous monitoring, and real-time performance that legacy security and monitoring technologies cannot.
Using advanced analytics powered by AI, Fusion identifies anomalous behavior that can indicate active compromises and other threats to data integrity, including unusual data transfers, unauthorized access attempts, and suspicious patterns of environment activity. Fusion utilizes context-enriched metadata and streaming telemetry to deliver high-confidence, high-fidelity alerts.
The platform analyzes millions of flows per second and is the only security tool to monitor multi-cloud and on-prem networks in real-time. It provides the scalable, accurate, high-performance monitoring you need to detect active threat actors.
Netography Fusion Delivers Critical Capabilities for HPC Environments
The Fusion platform delivers the performance and scalability your HPC environment requires with these purpose-built features.
Frictionless Architecture: Fusion is cloud-native, and its 100% SaaS frictionless deployment model means you can monitor any segment or instance across your cloud and on-prem environment at any time. The platform eliminates the need to deploy costly sensors, taps, or agents, enabling your security teams to visualize activity anywhere in your HPC environment. Streaming telemetry provides the continuous observability at scale that HPC environments rely on to identify anomalous activity as soon as it occurs to speed remediation. Fusion utilizes enriched metadata from devices, products, and services already running to provide unmatched real-time security and analytics.
Context-Rich Visualizations: The Fusion platform combines metadata from your multi-cloud and/or on-prem HPC environment with context attributes from your tech stack to create enriched metadata — transforming your mammoth tables of IP addresses, ports, and protocols into context-rich visualizations of the activities of your users, applications, and devices. Context is a critical component of the unique value the Fusion platform delivers. It enables your SecOps, NetOps, or CloudOps teams to understand the significance of the devices and workloads being investigated without having to access additional tools or engage with other teams.
Enhanced Observability Across Cloud Environments: Many AI companies leverage multi-cloud or hybrid cloud environments for their HPC needs, especially due to the scarcity of AI-optimized GPUs across all providers. Fusion provides comprehensive visibility and context across your diverse cloud infrastructures, allowing you to monitor and secure your entire footprint, regardless of your cloud service provider or deployment model. This enhanced observability gives you greater flexibility in negotiating with your cloud providers, and nimbleness in leveraging the most cost-effective infrastructure.
Advanced Analytics to Detect Insider Threats: Insiders pose a significant risk to your LLMs’ sensitive intellectual property or proprietary algorithms. Fusion’s AI-powered analytics can detect insider threats by identifying abnormal user behavior, such as unauthorized data access or exfiltration attempts, even among legitimate users with elevated privileges.
Protection Against Data Exfiltration: Your LLMs require access to large datasets for training, often including sensitive or confidential information. Fusion helps prevent data exfiltration by monitoring your environment’s trust boundaries for signs of unauthorized data transfers or exfiltration attempts. The Fusion platform can also enforce policies to restrict data access based on your user roles and permissions.
Rapid Response and Mitigation: In case of a security incident or potential breach, Netography Fusion enables your rapid response and mitigation playbooks. Fusion’s automated alerting and remediation capabilities help your security and operations teams investigate and contain compromises before they escalate. This proactive approach minimizes the blast radius of security incidents and reduces the time to resolution.
Comprehensive Compliance and Reporting: LLMs increasingly operate in highly regulated industries, such as healthcare and finance. These organizations are held to strict compliance requirements, including protecting PII, HIPAA, and other regulations. Netography Fusion assists you in meeting your compliance obligations by providing detailed audit trails, logging environment activity, and generating compliance reports to demonstrate adherence to industry standards and regulations.
Start Defending Your HPC Environments. Today.
Fusion continuously monitors context-enriched metadata from everywhere in your multi-cloud and on-prem networks to enable you to detect, investigate, and respond faster to malicious activity within your HPC environments:
- East/West and North/South observability monitors activity across all environments, including between clouds, cloud-to-on-prem, on-prem, on-prem-to-remote locations.
- Integration with your existing tech stack automates response workflows and playbooks with other tools in your stack, including SIEM, SOAR, EDR, and ticketing systems.
- Frictionless architecture eliminates deploying sensors, taps, or agents to collect data.
- Auto-discovery and monitoring of new VPCs and VNets automates the initial on-boarding of public cloud assets, eliminating the risk of unknown instances. Centralized, user-customizable dashboards enable the creation of team-specific visualizations and security monitoring.
- Centralized, user-customizable dashboards enable the creation of team-specific visualizations and security monitoring.
- Customizable detection and response models with Netography Detection Models (NDMs) give you complete control over pinpointing anomalous activity and enabling multiple response workflows from a single NDM.
- Standard language of Netography Query Language (NQL) enables real-time searching of any number of records and eliminates data silos with a uniform detection, analysis, and reporting framework.
- Flexible licensing and data retention to meet your requirements and budget.
To see for yourself how the Netography Fusion platform can start delivering value in your HPC environment today, contact us for more information or start a free trial.
About Netography
Netography is the leader in using context-enriched metadata to detect activity that should never happen in your multi-cloud or hybrid network. Netography Fusion is a 100% SaaS, cloud-native platform that provides real-time detection and response to compromises and anomalies at scale, without the burden of deploying sensors, agents, or taps.
Based in Annapolis, MD, Netography® is backed by leading venture firms, including Bessemer Venture Partners, SYN Ventures, and A16Z. For more information, visit netography.com.