Harness AI Security provides a unified control plane for AI discovery, risk visibility, and runtime protection, helping organizations operationalize key requirements of the EU AI Act. Instead of relying on manual audits or fragmented tooling, teams get continuous insight into how AI systems are built, exposed, and used, along with the evidence needed to demonstrate compliance.
By combining AI asset discovery, risk classification, data flow visibility, and runtime enforcement, Harness enables customers to proactively identify high-risk systems, prevent unsafe integrations, and continuously monitor AI behavior in production. This approach aligns directly with the EU AI Act's focus on transparency, traceability, and ongoing risk management.
Harness helps in the following areas of the EU AI Act
AI System Inventory
Harness automatically discovers all AI assets—AI APIs, Agents, MCP servers, MCP tools, resources, prompts, and AI backends by analyzing live network traffic. The centralized inventory provides a real-time breakdown of discovered assets by type, call volume trends, and sensitive data exposure across your environment. Security and compliance teams gain a single, continuously updated source of truth for every AI component in use, without requiring manual cataloging or developer-submitted forms.
Risk Identification & Classification (Article 6)
Once assets are discovered, Harness derives a risk score for each based on policy violations, known vulnerabilities, exposure level (internal vs. external), and sensitive data flow. This scoring helps teams prioritize remediation efforts and demonstrate that high-risk AI systems have been identified and assessed, which is a core expectation under the EU AI Act's risk-based framework.
Prohibited Use Cases (Article 5)
Harness detects shadow AI vendors, unapproved MCP servers, and undocumented AI APIs surfacing in your environment. The Third Party view surfaces AI APIs grouped by vendor (e.g., OpenAI, Google, Anthropic) so teams can identify integrations that haven't undergone procurement or security review. This is directly relevant to the EU AI Act's prohibition on certain AI use cases and its requirements around supply chain transparency for AI systems.
Data Governance & Quality (Article 10)
Harness monitors sensitive data flows across all discovered AI assets, identifying where PII and regulated data enters and exits AI systems. The platform classifies data sensitivity automatically by analyzing asset metadata and observed traffic patterns, giving teams a continuous view of which assets handle sensitive information and surfacing misuse risks before they become compliance incidents.
Technical Documentation & Auditability (Articles 11, 16)
Harness automatically generates schemas for AI APIs, MCP tools, resources, and prompts by analyzing real network traffic with no manual documentation effort required. Each asset detail page captures the asset's type, dependencies, call volume, risk posture, and data flows in one place. This detail provides compliance teams with the structured technical records required under Articles 11 and 16 without burdening engineering teams with additional documentation.
Logging & Traceability (Article 12)
Harness captures all AI interactions, including AI API calls, MCP tool invocations, database calls, and non-AI API calls, in a centralized data lake with seven-day standard retention and 30-day retention for threat activity. This complete, queryable record of AI system behavior supports both routine audit needs and forensic investigations, directly satisfying Article 12's requirements for logging and traceability of high-risk AI systems.
Accuracy, Robustness & Security (Article 9)
The AI Firewall (beta) provides runtime enforcement against the most common AI-layer threats: prompt injection attacks, PII leakage in model responses, excessive model usage, and unauthorized model access. Together, these controls address the robustness and security requirements of Article 9, helping organizations demonstrate that their AI systems have active protections in place rather than passive policies.
Post-Market Monitoring (Article 72)
Harness continuously discovers new AI assets, shadow AI usage, and emerging sensitive data risks in production as your environment evolves. Real-time alerts are triggered for new vulnerabilities and compliance violations, with native integrations into SOC/SIEM workflows for rapid response. This ongoing monitoring capability aligns directly with the EU AI Act's post-market surveillance requirements, ensuring compliance doesn't end at deployment.
Bottom line: Harness AI Security provides the visibility, controls, and audit evidence layer required to operationalize EU AI Act compliance at scale and oversee AI system security. (Article 14)
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Vikas Gautam is a product leader with 12+ years of experience across cybersecurity, BI, and UGC platforms. At Harness, he leads AI-native AppSec initiatives, including AI Security, API Discovery, and the AI Platform, driving strategy, scaling products, and leading cross-functional teams.
