Varonis is excited to announce the availability of Varonis Atlas, a complete AI Security Platform that empowers businesses to manage and secure AI across their entire organization.

Atlas stands alone as a platform that addresses the complete AI security process — from spotting and managing security, to ongoing protection and adherence — within a unified solution. It integrates with any AI system an organization utilizes: including cloud-based AI platforms, uniquely designed LLMs, agent frameworks, chatbots, and built-in AI. Crucially, Atlas leverages the Varonis Data Security Platform, granting it data-awareness beyond what standalone AI security tools can offer.

“AI is revolutionizing enterprise security. Instead of people manually using interfaces, agents directly access data — emphasizing the importance of data and AI security,” stated Yaki Faitelson, CEO and Co-founder of Varonis. “If you lack visibility into your AI systems and their access to sensitive information, you cannot safely utilize AI. Varonis Atlas provides organizations with the quickest route to secure and dependable AI.”

AI agents, copilots and LLMs are now integrated into standard procedures. They can access, modify, and use info efficiently. However, many companies aren’t aware of the specifics of the AI systems they use, the level of accessibility of those systems, and the degree of regulatory compliance.

Gartner® published a report entitled, The Future of AI Security is in Securing Agent Actions, Not Prompts, where researchers suggest that over half of survey respondents have already committed to deploying AI agents.

The report predicts 30% of organizations will leverage AI security platforms to reinforce agent development in artificial intelligence-native software engineering, due to the growing use of automated coding tools that rely on agentic coding tools.

As autonomous and agent-driven AI implementation proliferates, risk is rising:

• Agents write, read, create, and modify information constantly and quickly
• Data access is often broadly given and is incompletely understood
• Minor configuration mistakes quickly turn into significant info breaches or statutory fines

This is why AI security needs to be centered in data protection, which is why Varonis Atlas has been created. Atlas secures everything you create and run using AI. Let’s dig into these essential features.

Varonis Atlas gives you continual discovery of AI across your organization, including sanctioned assets, specific agent developments, inherent AI, and “shadow” AI used outside formalized approval streams. With scans of cloud accounts, code repositories, AI platforms, and SaaS use, Atlas generates a constantly updated directory that indicates AI presences, their connectivity and accessibility, and the permissible actions — creating the base for every sort of AI security control.

• Go beyond surface discovery: Atlas inventories agents, models, tools, MCP servers, dependencies, and supporting infrastructure — not just LLM endpoints or chat apps.
• Uncover shadow AI with context: Discovered AI assets are tied to users, data access, and activity context, making shadow AI immediately actionable instead of just visible.

Atlas AI Security Posture Management is continuous evaluation of AI systems, searching for potential issues, exposure of sensitive information, misconfigurations, and agent-related danger in the AI stack. It researches code, prompts, dependencies, models, set-ups, and brings to light tangible security risks, as well as directly aligning those risks with relevant AI assets and their corresponding data. This comprehensive structure provides the ability to mitigate danger before AI systems reach wide use.

• Data-aware posture, not just model checks: Findings are enriched with data sensitivity and access context from the Varonis Data Security Platform, exposing real business risk.
• Built for enterprise scale: AI-SPM spans cloud platforms, agent frameworks, custom models, and third-party AI — not a single development environment or use case.

Atlas proactively puts AI systems to the test with dynamic assaults and adversarial prompts aimed at live LLM endpoints. Dynamic analysis brings issues to light – simulated attacks like jailbreaks, prompt injections, or attempts to go around policy. They’re recorded as security discoveries joined directly to affected agents, set-ups, and models.

• Live, dynamic testing: Pen tests run against real production endpoints, not offline simulations or static rule checks.
• Downstream enforcement: Pentest results directly inform runtime guardrails and posture policies, closing the loop from testing to protection.

Atlas applies real-time guardrails through an AI Gateway in the live request path, watching prompts, outputs, and agent actions prior to reaching the model or supporting systems. The AI Gateway protects against leakage of sensitive info, halts poor or criminal behavior, and establishes alerts without altering AI or its application.

• AI-aware blocking and policy enforcement: Guardrails understand execution flow, agent tools, and indirect leakage paths — not just simple pattern matching.
• Customer-owned data plane: Prompts, responses, and telemetry stay inside the customer’s environment, supporting data residency and sovereignty requirements.

Atlas operationalizes AI regulation when it traces regulatory frameworks, mapping to structures like the EU AI Act and the NIST AI RMF. Turning adherence from a single event to evidence-backed process, it provides audit-geared reports, remains with transparency and lineage items, and keeps track of remediation position and danger assessments.

• Built on real system evidence: Compliance reporting is grounded in live AI inventory, lineage graphs, activity logs, and security findings — not questionnaires alone.
• Unified with security controls: Governance is directly connected to discovery, posture, pen testing, and runtime enforcement, avoiding fragmented GRC tooling.

Varonis Atlas continues AI security, including the models, services, and platforms sourced from their supply networks and third-parties organizations use. It monitors third-party AI vendors by mixing AI inventories or Bills of Materials (AIBOM) with the vendor questionnaire responses to understand AI systems outside of the organization’s ownership handle data and risk caused by specific dependencies.

This is how organizations detect, trace, and repair risk from third-party AI and keep it into the AI security life cycle.

• Continuous, not point in time: Third-party AI risk is continuously reassessed as vendor inputs, dependencies, or behaviors change, rather than relying on static reviews.
• Integrated with AI inventory: Third-party AI systems are tracked alongside internal AI assets, providing automated risk analysis and visibility.

Atlas AI Activity Monitoring gives view of AI’s actions by capturing actions of prompts, outputs, agents, data and guardrail decisions. Control can be obtained by safety teams and governance using user-owned observability and simple dashboards. These help users figure out AI behavior, including issues, and investigations of incidents over flows of models, agents, and tools.

• Full execution visibility: Monitoring spans prompts, responses, agent tool calls, and data access—not just user chat logs or model outputs.
• Customer-owned telemetry: All AI activity logs remain within the customer’s environment, supporting auditability, data residency, and forensic investigation.

Real-time alerts generated by Varonis Atlas deliver AI Detection and Response (AIDR) by discovering criminal actions or unsafe non-compliant AI operations along the models, resources, agents, and flow of data. In the event that actions that can be threatened like jailbreak attempts are detected, AI may block activity when needed and integrate with resources to maintain fast detection and reaction.

• AI-native threat detection: AIDR understands AI-specific attack techniques and agentic behavior rather than relying on traditional application security signals.
• Unified with data security: Detections are enriched with data sensitivity and access context, enabling teams to prioritize incidents based on real business impact.

AI security must work in silos. It takes the help of a unified process which connects with data needed by AI. The greater amount of AI used, the greater amount of vulnerability there is. The only way forward is security that understands the behavior of AI, in addition to reaching data.

“Most AI security tools are fragmented and data-blind. They can inventory your AI systems or monitor prompts, but they can’t see what sensitive data AI is accessing or control what it does with that data. That’s the real risk, and is exactly what Atlas and the Varonis Data Security Platform solve together.”

Ron Bennatan, VP of AI & Data Security Strategy at Varonis, co-founder of AllTrue.ai, creator of Guardium (bought by IBM) and jSonar (bought by Imperva)

Varonis Atlas is ready now. Check out Atlas features like inventory, posture management, continuous security testing, runtime guide rails, and obedience and reporting using this demo or a free trial.

Sponsored and written by Varonis.