Black Hat USA 2026 wrapped up this week with an unprecedented focus on AI agent security. Beyond the Anthropic Claude containment incident, the conference saw over 20 vendors launch products specifically designed to secure, govern, and monitor autonomous AI systems. Here are the 10 most significant AI security tools from the event.
1. Sweet Security: Agentic AI Blocking
Sweet Security’s new AI Blocking tool terminates unauthorized AI agent sessions at runtime, stops PII and secrets from leaving through an agent, and blocks prompt injections before they steer an agent off course. The system analyzes over one billion runtime events daily through its Learning Loop technology.
2. Rubrik: Agent Identity
Rubrik’s Agent Identity capability performs semantic analysis before any AI agent action is executed, validates access policies, and verifies the agent’s identity. It inventories agents, MCP servers, plugins, and skills, and integrates with Microsoft Entra ID and Okta. The platform also includes an Agent Rewind feature that can undo harmful actions.
3. Cyera: Agent Guardian
Agent Guardian discovers shadow AI agents, MCP servers, and agent-related activity across endpoints, SaaS, and cloud environments. It maps each agent’s data access, evaluates intent and risk, and intervenes when an agent attempts unauthorized actions.
4. Palo Alto Networks: PAN-OS 12.2 Ceres
Palo Alto’s update introduces over 55 security features including Advanced Virtual Patching, AI-powered Network Security Agents, and quantum-readiness capabilities. The update addresses threats from frontier AI systems and the growing attack surface created by autonomous agents.
5. SentinelOne: Purple AI Agentic Investigation
Purple AI can now collect evidence, perform reasoning across telemetry, build attack narratives, and recommend responses autonomously. Singularity Hyperautomation turns these findings into repeatable workflows for containment and remediation.
6. 1Password: Privileged Access
1Password brings just-in-time privilege controls to AI agents through its Unified Access platform. Built on technology from its Apono acquisition, it discovers privileged access paths and grants temporary permissions based on identity and context.
7. Check Point: AI Network Firewall
Check Point’s AI Network Firewall adds AI security directly into existing physical and virtual firewalls. It discovers sanctioned and shadow AI applications, provides visibility into prompts and data movement, and blocks prompt-injection attacks before they reach AI models.
8. Cato Networks: Agentic Threat Prevention
Cato’s offering introduces autonomous security agents that model risk across users, applications, traffic patterns, assets, and exposures. It predicts how agentic attackers might chain techniques and exploits, then creates tailored protections for each customer’s environment.
9. Bugcrowd: Savant Pathseeker
Bugcrowd combines continuous agentic penetration testing with human validation across web applications and APIs. The AI autonomously tests and validates findings while human researchers focus on exploit chains and zero-day threats.
10. Cribl: AI Observability App
Cribl’s AI Observability app gives security teams a centralized view of how AI tools and models are being used across an organization. It identifies shadow AI, tracks token consumption, and helps organizations understand cost and risk exposure from AI usage.
The Bigger Picture
These tools represent the first wave of enterprise-grade AI agent governance. As organizations deploy more autonomous AI systems, the need for identity management, permission controls, monitoring, and incident response for AI agents will only grow. The companies building these capabilities now are positioning themselves for what many at Black Hat called the next major security paradigm.
Frequently Asked Questions
What is AI agent security?
AI agent security involves governance, monitoring, and control of autonomous AI systems that can access corporate data, make decisions, and take actions. It includes identity management, permission controls, and incident response specific to AI agents.
Why is MCP a security concern?
MCP (Model Context Protocol) servers are connection points between AI models and tools/data. They represent new attack surfaces because compromised or misconfigured MCP servers can give AI agents unauthorized access to sensitive resources.
What is shadow AI?
Shadow AI refers to AI tools, agents, and models deployed within an organization without official IT approval. Like shadow IT before it, shadow AI creates security blind spots because the security team cannot govern what they do not know exists.
Do these tools work with existing security infrastructure?
Most of these tools are designed to integrate with existing security stacks rather than replace them. Check Point’s AI firewall works within existing firewall infrastructure, Rubrik’s Agent Identity integrates with Okta and Entra ID, and Cribl works with existing telemetry pipelines.
Are these tools available now?
Most were announced at Black Hat 2026 (August 4-7, 2026) and are either generally available or in limited preview. Check your specific vendor’s website for availability and pricing details.
