Sysdig announced runtime security detections for AI coding agents on March 23, 2026 at the RSA Conference in San Francisco, providing organizations with real-time visibility into AI agent behavior within development environments. The product addresses a critical gap: as AI agents like Claude Code, OpenAI’s Codex, and Google’s Gemini CLI execute code autonomously across repositories and systems, traditional security tools designed for human developers fall short.

The Attack Surface AI Agents Create

AI coding agents operate fundamentally differently from static code generators. According to Sysdig’s analysis, modern agents can execute commands directly on user systems, read and modify files across repositories, access environment variables and credentials, and interact with repository APIs—all at machine speed and with minimal human intervention. They operate with the same system permissions as a developer, making them attractive targets for attackers or vulnerable to misconfiguration.

“AI agents are among the greatest innovations and security risks of our generation. Today, they help us write code faster, but tomorrow they’ll be running our most critical business operations,” said Loris Degioanni, Founder and CTO of Sysdig, in the press release.

The risks are concrete: remote code execution triggered by malicious repositories, credential theft from configuration files, malicious code inserted into pull requests, data leakage through prompts, and supply chain attacks targeting CI/CD workflows.

How the Runtime Layer Works

Sysdig’s detections build on its Falco framework and are constructed by Sysdig’s Threat Research Team. The system identifies AI coding agent installations and monitors specific behaviors in real time:

  • Agent discovery: Detection of installed agents (Claude Code, Codex, Gemini CLI) so security teams know where tooling is deployed
  • Risky behavior flagging: Unauthorized attempts to access sensitive files, configuration directory manipulation, command-line arguments that weaken protections
  • Execution layer enforcement: Alerts on reverse shells, binary tampering, persistence mechanisms, and other high-risk activity within developer environments

The detections are designed to distinguish between legitimate AI-assisted activity and suspicious behavior that could signal compromise or misconfiguration.

The Timing: Security Response to Adoption Wave

The announcement comes as enterprises rapidly deploy coding assistants. According to Stack Overflow’s 2025 survey cited by Sysdig, nearly 65% of developers are already using AI coding tools weekly. The announcement also follows DefenseClaw’s January 2026 open-source release (which provided static analysis of agent code) and earlier reporting on agent security vulnerabilities published by Futurism and security researchers.

Sysdig frames runtime visibility as complementary to static code analysis—catching not just what code looks like, but what an agent does when it executes.

“Organizations that want to take advantage of AI-assisted development must ensure they have visibility into what AI agents are actually doing inside their environments,” Sysdig stated in accompanying guidance.

What This Means for Builders

For teams deploying coding agents, this marks the emergence of a new security category: agent behavior monitoring. The product sits between static code analysis (DefenseClaw) and execution monitoring, filling a visibility gap that regulatory bodies and enterprises have flagged as critical as autonomous tools proliferate.

The question builders face now is whether runtime monitoring alone is sufficient—or whether the permission model and sandboxing of agents themselves need to change. Sysdig’s approach assumes agents will be deployed in standard development environments; it flags what they do there rather than restricting what they can do beforehand.