AI Security Operations (AISecOps)

AISecOps (AI Security Operations) is the emerging practice of applying security operations principles to AI systems. Just as SecOps protects IT infrastructure, AISecOps defends AI models—especially those deployed in production—from a growing array of adversarial threats, compliance risks, and runtime failures.

This discipline sits at the intersection of MLOps, cybersecurity, and AI governance. It includes:

• Threat detection: Identifying adversarial inputs, prompt injection, model extraction, or poisoning attempts.
• Policy enforcement: Blocking disallowed content, enforcing user access rules, or limiting model behavior.
• Incident response: Triggering alerts, rollbacks, or mitigations in response to attacks or misuse.
• Audit and reporting: Capturing forensic records of model decisions, prompts, and outputs for compliance and investigation.

AISecOps must operate at runtime—monitoring models continuously and responding dynamically to emerging risks. It requires specialized tools that understand AI behavior, context, and sensitivity.

As AI becomes part of customer support, healthcare, financial decisions, and autonomous systems, security expectations grow. Attacks on AI are evolving, and so must the operational defenses.

AISecOps teams work closely with DevSecOps, compliance teams, and data scientists to ensure models remain safe, aligned, and transparent. The practice is increasingly aligned with MITRE ATLAS, OWASP LLM Top 10, and regulatory frameworks like the NIST AI RMF.

How PointGuard AI Addresses This:
PointGuard AI delivers a complete AISecOps platform, monitoring AI systems in real time and enforcing configurable protections. From prompt injection to sensitive data leakage, PointGuard provides runtime controls, incident response workflows, and unified visibility across deployed models—helping teams operationalize AI security and compliance at scale.

AISecOps: The Next 'Shift Left' for Securing AI Applications