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Secure AI Development Environment
Secure AI notebooks from secrets, vulnerabilities, and compliance drift automatically.
OpsMx Delivery Shield embeds NBDefense to harden Jupyter and VS Code notebooks against secrets exposure, PIIs, malicious code, and compliance drift—creating a secure-by-default AI development workspace.
Secure AI Development Key Features
Secrets & credential scanning
Flags API keys, tokens, and passwords in code cells or outputs before they hit Git.
Vulnerability detection
Detects unsafe packages, shell escapes, and exploitable commands inside notebooks.
Policy-driven linting
Enforces pre-built or custom rules (e.g., HIPAA, GDPR) at save or commit.
Automated cell sanitization
Redacts sensitive outputs and rewrites risky code patterns automatically.
Context-graph linkage
Links notebook findings to associated repos, models, and pipelines for traceability.
Seamless IDE integration
Works out-of-the-box with JupyterLab, VS Code, Colab, and other cloud notebooks.
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Secure AI Development Key Benefits
Prevents credential leaks
Detects and removes secrets at the earliest point in the SDLC.
Accelerates secure coding
Offers real-time, in-editor feedback and auto-fix suggestions.
Simplifies audits & compliance
Continuously enforces policies and captures evidence trails.
Reduces rework & incidents
Blocks insecure code before it reaches training or production.
Unifies Dev & Sec workflows
Centralized dashboards show notebook risks alongside pipeline health.
Resources for Secure AI Development Environment
Datasheet: Secure AI Development Environment
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Blog: Secure AI Development Environment with OpsMx
Read NowCapabilities 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.
Built on Leading Open Source Security Tools
