AI Security Hub
02AI Security Pillar

Input Security Checks

Inspect information before it reaches the model or influences an AI workflow.

Business focus

Inspect before processing

Why it matters

Security starts with a defined business boundary

Input security checks look for malicious instructions, unsafe formats, sensitive information, and suspicious files before the AI processes them.

Business risk

An AI system may receive instructions from users, documents, websites, email, or connected applications. If every input is trusted equally, an attacker or compromised source can influence the workflow.

What this pillar covers
  • Prompt-injection screening
  • Jailbreak-attempt detection
  • Personal and confidential data detection
  • Malware and suspicious file patterns
Launch reading list

Start with these practical guides

Each pillar begins with one anchor guide and two supporting articles. Published guides become active automatically as they enter the blog.

Publishing soon

What Is Prompt Injection? A Business Guide to Protecting AI Workflows

Understand how malicious instructions can enter through users or third-party content.

Part of the launch series
Publishing soon

LLM Input Validation: What to Check Before Data Reaches the Model

Apply format, content, authorization, and failure checks across input paths.

Part of the launch series
Publishing soon

Prompt Jailbreaking: What It Means for Business AI Security

Recognize attempts to make an AI system ignore its intended safety rules.

Part of the launch series

Questions for leadership

  • Which input channels can influence the AI?
  • How does the workflow handle a rejected or suspicious request?
  • Who reviews repeated attack patterns or false positives?
  • Are file and data checks applied before retrieval and tool use?
Practical control checklist

Put the pillar into practice

  1. 1List every user, file, retrieval, and application input path.
  2. 2Treat external content as data rather than trusted instructions.
  3. 3Validate file type, size, structure, and malware status.
  4. 4Screen for restricted or sensitive information before processing.
  5. 5Log blocked requests and define an escalation owner.
Review a real workflow

Turn this pillar into operating controls

Map the data, access, approvals, monitoring, and evidence around one important AI use case before expanding it.

Explore the diagnostic