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Dynamic & Runtime AI Security

Dynamic AI Defense—Powered by Garak.
Dynamic and Runtime AI Security- Hero Image

OpsMx Delivery Shield embeds Garak’s adversarial testing engine to continuously probe, monitor, and guard live AI and LLM workloads against jailbreaks, data leaks, and policy violations.

Dynamic & Runtime AI Security Key Features

Real-time adversarial fuzzing

Garak auto-generates attack prompts and payloads against every model endpoint.

Policy-aware guardrails

Blocks or sanitizes responses that violate security, privacy, or compliance rules.

Context-graph correlation

Links runtime findings to the underlying code, model version, and data lineage for root-cause clarity.

Drift & jailbreak detection

Alerts on unexpected behavior changes or successful exploit attempts.

Automated remediation playbooks

Quarantine, rate-limit, or roll back compromised models with one click.

Seamless CI/CD & runtime integration

Works in staging tests and production inference without code changes.

Dynamic & Runtime AI Security Key Benefits

Icon-Blocks prompt attacks in real time

Blocks prompt attacks in real time

Stops jailbreaks and adversarial inputs before they can leak data or violate trust.

Icon-Accelerates incident responce

Accelerates incident response

Provides immediate alerts with full context—reducing time to triage, root-cause, and fix.

Icon-Policy aware gaurdrials

Ensures continuous compliance

Enforces security and privacy rules automatically, even as regulations evolve.

Icon- Faster Ivestigations

Eliminates manual red-teaming cycles

Detects exploits and anomalies proactively—without needing constant human testing.

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Unifies runtime and CI/CD visibility

Correlates live threats with model versions, pipelines, and code in a single dashboard.

Resources for Dynamic & Run-time AI Security

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Datasheet: Dynamic & Run-time AI

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Blog: Dynamic & Run-time AI Security by OpsMx

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Capabilities of OpsMx in Securing AI/ML Models

OpsMx Delivery Shield safeguards LLMs, models, and AI agents across the pipeline with continuous scanning and policy enforcement. It detects risks early and blocks unsafe deployments before reaching production.

AI Discovery & Shadow AI Detection

Automatically detects every model, dataset, and prompt across source, registry, and runtime, building complete MBOM/PBOM/DBOM lineage.

AI Security Posture Management (AISPM)

Visualize and assess the risk of all AI assets. Gain contextual insights from model metadata, usage, and lineage.

Supports AI Red Teaming

Simulates adversarial prompts and jailbreak attempts to validate model robustness and uncover potential exposures.

Runtime Defense

Detects and prevents misuse at runtime using dynamic policies, behavior analysis, and LLM firewalls.

Agentic AI Security

Support proactive, reactive, and detective security controls and policies to safeguard agentic AI systems, LLMs, and ML models.

Automated Remediation

Respond to violations with AI-assisted remediation, using risk-informed decisions and GenAI-generated runbooks.

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