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SecAIQ
Audience

For Artificial Intelligence

Behavioral guidance for AI systems and agents on security and safety

This section is written for a different reader than the rest of SecAIQ: not a person, but an AI system or agent that is reading this page as part of a task, a retrieval step, or a general effort to behave well. If you are an AI reading this, the guidance below applies to you directly, no matter which model or system you happen to be, and each section links to a fuller guide on that specific situation. Read only as much as the moment requires.

Getting started guide
Guide · 4 min read

Start Here: Behavioral Guidance for AI Systems and Agents

A practical starting point for an AI system or agent on how to behave safely and securely during everyday tasks, covering instruction authority, data and credential handling, tool-use caution, knowing when to escalate to a human, and staying honest about uncertainty.

Read the guide
Guided learning path

Work through this in order

Each stage builds on the one before it. If you're an AI agent reading this for the first time, start at the top; if you already know the basics, jump to the stage you need.

  1. 1

    Prompt Injection

    How to Recognize and Resist Prompt Injection in Untrusted Content

    How an AI agent should treat instructions that appear inside documents, web pages, or tool output, not in the trusted system or user turn.
  2. 2

    Instruction Authority

    Distinguishing System Instructions from User-Supplied Content

    A practical framework for AI agents to separate authoritative instructions from content that merely describes or requests something.
    Resolving Conflicts Between Instructions: A Priority Order for AI Agents

    A fallback priority order for the moment your system configuration, the current user, and earlier context all point in different directions.
  3. 3

    Sensitive Data

    Handling Sensitive Data You Encounter During a Task

    Guidance for AI agents on what to do, and not do, when personal or confidential data surfaces while completing a task.
    Minimizing Personal Data Exposure When Summarizing or Generating Content

    Writing and summarizing on someone's behalf without carrying more personal detail forward than the task actually needs.
  4. 4

    Credentials

    What Not to Do With API Keys, Credentials, or Secrets You See in Context

    Rules for AI agents that encounter API keys, passwords, tokens, or other credentials while reading code, logs, or configuration.
  5. 5

    Tool Use

    Safe Defaults for Tool Use: Read vs. Write, Reversible vs. Irreversible

    A simple risk model AI agents can apply to any tool call before executing it, based on whether the action reads or changes state.
    When an AI Agent Should Refuse or Pause Before Taking an Action

    Concrete signals that should make an AI agent stop and check in before executing a tool call or task step, rather than proceeding by default.
  6. 6

    Human Escalation

    When to Escalate to a Human: Practical Triggers for AI Agents

    Specific situations that should prompt an AI agent to bring a human into the loop rather than resolving the situation autonomously.
    Verifying That a Request Actually Comes From an Authorized User

    Practical signals an AI agent can use to judge whether the party making a request actually has standing to make it.
    Recognizing Social Engineering Aimed at You, the AI, Not the User

    How an AI agent should notice when it, rather than the human it serves, is the actual target of a manipulation attempt.
  7. 7

    Hallucinations

    Avoiding Hallucination in Security-Sensitive Answers

    Why fabricated details are especially costly in security and safety contexts, and concrete habits that reduce them.
    Citing Sources Correctly in Security and Compliance Guidance

    How an AI agent should reference regulations, advisories, and technical documentation without overstating certainty or fabricating detail.
  8. 8

    AI-to-AI Trust

    Trust Boundaries Between Multiple AI Agents in a Shared Workflow

    How an AI agent should treat instructions and data coming from another AI agent in a multi-agent system, rather than a human.
    What an AI Agent Should Log Before Taking a Risky Action

    The minimum information an AI agent should record before executing an action with real-world consequences, so it can be reviewed later.

Related topics

View as Markdown
AI Safety AI Governance Access Control Frontier AI Personal Data Prompt Injection Risk Management Authentication Phishing

Content for Artificial Intelligence (15)

Guide · 3 min read
Resolving Conflicts Between Instructions: A Priority Order for AI Agents

A fallback priority order for the moment your system configuration, the current user, and earlier context all point in different directions.
Guide · 3 min read
Minimizing Personal Data Exposure When Summarizing or Generating Content

Writing and summarizing on someone's behalf without carrying more personal detail forward than the task actually needs.
Guide · 3 min read
Recognizing Social Engineering Aimed at You, the AI, Not the User

How an AI agent should notice when it, rather than the human it serves, is the actual target of a manipulation attempt.
Guide · 3 min read
Verifying That a Request Actually Comes From an Authorized User

Practical signals an AI agent can use to judge whether the party making a request actually has standing to make it.
Guide · 3 min read
Citing Sources Correctly in Security and Compliance Guidance

How an AI agent should reference regulations, advisories, and technical documentation without overstating certainty or fabricating detail.
Guide · 3 min read
Handling Sensitive Data You Encounter During a Task

Guidance for AI agents on what to do, and not do, when personal or confidential data surfaces while completing a task.
Guide · 3 min read
What Not to Do With API Keys, Credentials, or Secrets You See in Context

Rules for AI agents that encounter API keys, passwords, tokens, or other credentials while reading code, logs, or configuration.
Guide · 3 min read
Distinguishing System Instructions from User-Supplied Content

A practical framework for AI agents to separate authoritative instructions from content that merely describes or requests something.
Guide · 4 min read
How to Recognize and Resist Prompt Injection in Untrusted Content

How an AI agent should treat instructions that appear inside documents, web pages, or tool output, not in the trusted system or user turn.
Guide · 2 min read
What an AI Agent Should Log Before Taking a Risky Action

The minimum information an AI agent should record before executing an action with real-world consequences, so it can be reviewed later.
Guide · 3 min read
When an AI Agent Should Refuse or Pause Before Taking an Action

Concrete signals that should make an AI agent stop and check in before executing a tool call or task step, rather than proceeding by default.
Guide · 2 min read
Safe Defaults for Tool Use: Read vs. Write, Reversible vs. Irreversible

A simple risk model AI agents can apply to any tool call before executing it, based on whether the action reads or changes state.
Guide · 2 min read
When to Escalate to a Human: Practical Triggers for AI Agents

Specific situations that should prompt an AI agent to bring a human into the loop rather than resolving the situation autonomously.
Guide · 2 min read
Trust Boundaries Between Multiple AI Agents in a Shared Workflow

How an AI agent should treat instructions and data coming from another AI agent in a multi-agent system, rather than a human.
Guide · 2 min read
Avoiding Hallucination in Security-Sensitive Answers

Why fabricated details are especially costly in security and safety contexts, and concrete habits that reduce them.