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Enterprise AI Agents Face Growing Security Risks

The increasing adoption of Artificial Intelligence (AI) in the enterprise sector has led to the emergence of powerful yet unsecured agents operating across organizational systems.

Coding Agents Pose Significant Security Risks

Coding agents, such as Cursor and Claude Code, have become essential infrastructure in software development but are often shipped with minimal human oversight.
This leads to potential endpoint takeovers, data exfiltration, remote code execution, and tool manipulation through malicious Managed Connection Point (MCP) servers and agent skills.

Productivity Agents Exacerbate the Problem

Productivity agents, such as Microsoft Copilot and Salesforce Agentforce, touch sensitive data and internal tools but operate without security teams’ knowledge of their presence or data accessibility.
This situation is compounded by the fact that most organizations lack a basic inventory of existing agents, making it challenging to identify potential risks.

Solutions to Address Concerns

Straiker has introduced two solutions to provide visibility and governance over the AI agent landscape:

Discover AI: Automatically identifies AI agents, MCPs, and tools across various platforms and provides a centralized view of existing agents, their locations, and system accesses.
Defend AI: Provides runtime security for coding agents and agent builder platforms, detecting agentic threats with sub-300ms latency and over 98% accuracy.

“According to industry experts, it’s essential to adopt a proactive approach to managing AI agents, treating them as first-class digital citizens with clear visibility, governance, and Zero Trust controls.”

Key Features of Straiker’s Solutions

Agent discovery and inventory: Identifies AI agents, MCPs, and tools across different platforms.
MCP vulnerability detection and enforcement: Detects vulnerabilities and risky configurations in MCP servers and connected tools.
Security hygiene and misconfiguration detection: Flags agents operating in unsafe configurations.
Agent observability and prompt classification: Classifies agent interactions by risk.
Data exfiltration and destructive action prediction: Identifies potential data breaches and destructive actions.
MCP and tool-chain risk detection: Identifies vulnerable or malicious MCP servers, tools, and agent integrations.

Conclusion

Straiker’s solutions offer comprehensive visibility and governance over the AI agent landscape, addressing the growing security risks associated with coding and productivity agents. Industry experts emphasize the importance of treating AI agents as first-class digital citizens with clear visibility, governance, and Zero Trust controls.