Enterprise AI Security
Defending Against Prompt Injection & Jailbreaks: Indirect Attacks & Guardrails
Protect your enterprise AI agents from direct and indirect prompt injections, adversarial suffixes, and untrusted user input.
Direct vs Indirect Prompt Injection
Direct injections come from malicious user prompts. Indirect injections hide inside scraped web pages, emails, or PDFs read by the AI agent to hijack its tool-calling privileges.
Mitigation requires strict separation of data and instruction channels, input sanitization, and output boundary verification.
Related Technical Guides
Deepen your understanding with these closely related production architectures and tutorials:
NVIDIA NeMo Guardrails: Programmable Dialog Rails, Safety Policies & Colang
Enforce safety boundaries on LLM outputs using NVIDIA NeMo Guardrails: input rails, dialog flow constraints, and output validation.
PII Masking & Privacy-Compliant AI: Microsoft Presidio & Real-Time Redaction
Anonymize credit cards, government IDs, and health data before sending prompts to external LLMs using Microsoft Presidio and reversible tokenization.
OWASP Top 10 for LLMs: Comprehensive Defense Strategies for 2026
A deep dive into OWASP LLM vulnerabilities: Insecure Output Handling, Excessive Agency, Model Denial of Service, and Supply Chain Risks.