Securing the Agent Loop
ModSecOps for real-time AI systems that think, act, and remember.
Agents don't commit code — they act.
Bypassing CI/CD
Agentic workflows operate outside traditional development pipelines, making conventional security checks ineffective.
Post-Commit Blindness
Static analysis and post-commit scanning can't catch real-time decisions made by autonomous agents.
Unpredictable Behavior
AI agents create emergent behaviors that traditional security tools aren't designed to handle.
The Agent Loop with ModSecOps
See how ModSecOps integrates security controls at each step of the agent's decision-making process.
Control the cognition, not just the container.
Prompt Loop Validation
Continuous monitoring and validation of agent decision-making processes in real-time.
Toolchain Gating
Advanced sandboxing and permission controls for agent tool usage and execution.
Memory Boundaries
Strict enforcement of role-based memory access and context limitations.
Behavioral Gating Framework
Traditional DevSecOps
- Static PoliciesRule-based controls and static analysis
- CVE ScanningVulnerability-based security checks
- Post-DeploymentReactive monitoring and response
ModSecOps for Agents
- Behavioral TestingContinuous simulation and validation
- Real-time GatesDynamic decision validation
- Risk ScoringMission-based adaptation
Govern Autonomous AI — Before It Thinks
See how Crystal Tower brings ModSecOps to your AI agent framework.
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