---
title: Agentic AI Security Threat Model
description: Explore the Agentic AI Security Threat Model by Sukhada Khade, addressing emerging security challenges in AI and their implications for data analytics.
image: https://blog.optimumdataanalytics.com/hubfs/Blog%20Images/Agentic%20AI%20Security%20Threat%20Model/Agentic%20AI%20security%20threat.png
---

[Skip to main content](http://blog.optimumdataanalytics.com/agentic-ai-security-threat-model#main)

[![Optimum-Data-Analytics-1-e1749546723829](https://blog.optimumdataanalytics.com/hs-fs/hubfs/Optimum-Data-Analytics-1-e1749546723829.png?width=212&height=58&name=Optimum-Data-Analytics-1-e1749546723829.png) ![Optimum-Data-Analytics-1-e1749546723829](https://blog.optimumdataanalytics.com/hs-fs/hubfs/Optimum-Data-Analytics-1-e1749546723829.png?width=212&height=58&name=Optimum-Data-Analytics-1-e1749546723829.png)](https://optimumdataanalytics.com)

- [Home](https://optimumdataanalytics.com)
- [About](https://optimumdataanalytics.com/about/)
- [Show submenu for Offerings Offerings](https://optimumdataanalytics.com/offerings/) 
    - [Generative AI](https://optimumdataanalytics.com/generative-ai/)
    - [Agentic AI](https://optimumdataanalytics.com/agentic-ai/)
    - [AI/ML Solutions](https://optimumdataanalytics.com/ai-ml-solutions/)
    - [Data Engineering](https://optimumdataanalytics.com/data-engineering/)
    - [Computer Vision](https://optimumdataanalytics.com/computer-vision/)
- [Show submenu for Industries Industries](https://optimumdataanalytics.com/industries/) 
    - [Healthcare](https://optimumdataanalytics.com/healthcare/)
    - [Supply Chain](https://optimumdataanalytics.com/supply-chain/)
    - [Agriculture](https://optimumdataanalytics.com/agriculture/)
    - [Finance](https://optimumdataanalytics.com/finance/)
- [CSR Activities](https://optimumdataanalytics.com/csr-activity/)
- [Blogs](https://blog.optimumdataanalytics.com)
- [Careers](https://optimumdataanalytics.com/careers/)
- [Contact](https://optimumdataanalytics.com/contact/)

Open main navigation

Close main navigation

- [Home](https://optimumdataanalytics.com)
- [About](https://optimumdataanalytics.com/about/)
- Show submenu for Offerings Offerings 
  
    - Offerings
    - [Offerings](https://optimumdataanalytics.com/offerings/)
    - [Generative AI](https://optimumdataanalytics.com/generative-ai/)
    - [Agentic AI](https://optimumdataanalytics.com/agentic-ai/)
    - [AI/ML Solutions](https://optimumdataanalytics.com/ai-ml-solutions/)
    - [Data Engineering](https://optimumdataanalytics.com/data-engineering/)
    - [Computer Vision](https://optimumdataanalytics.com/computer-vision/)
- Show submenu for Industries Industries 
  
    - Industries
    - [Industries](https://optimumdataanalytics.com/industries/)
    - [Healthcare](https://optimumdataanalytics.com/healthcare/)
    - [Supply Chain](https://optimumdataanalytics.com/supply-chain/)
    - [Agriculture](https://optimumdataanalytics.com/agriculture/)
    - [Finance](https://optimumdataanalytics.com/finance/)
- [CSR Activities](https://optimumdataanalytics.com/csr-activity/)
- [Blogs](https://blog.optimumdataanalytics.com)
- [Careers](https://optimumdataanalytics.com/careers/)
- [Contact](https://optimumdataanalytics.com/contact/)
- Search

Search

# Agentic AI Security Threat Model

![Sukhada Khade](https://blog.optimumdataanalytics.com/hs-fs/hubfs/Author%20Profiles/Sukhada%20Khade.png?width=120&height=120&name=Sukhada%20Khade.png)

 by [Sukhada Khade](https://blog.optimumdataanalytics.com/author/sukhada-khade)

Oct 1, 2026, 8:00:00 AM

Imagine a security team getting an alert: “**Suspicious login detected**.” A traditional AI assistant might explain the alert and suggest what to check. An agentic AI can take the investigation further by checking the user, device, location, recent activity, and threat intelligence, then creating a ticket or taking an approved action.

That changes the security question. It is no longer just “**Is the AI giving the right answer?**” but also “**Can we trust it to take the right action?**” As agents gain access to tools, data, and business systems, threat modeling helps identify what could go wrong and where controls are needed before the agent acts.

### **What Makes AI “Agentic”?**

A traditional AI application usually follows a simple flow:  
**User → Prompt → AI → Response**

The user gets an answer and decides what to do next. Agentic AI goes a step further by planning, using tools, checking results, and taking action.  
**Goal → Reason → Plan → Use Tools → Act → Observe → Adapt**

For example, after a **suspicious-login** alert, the agent can check the user, device, IP address, and recent activity before deciding on a response. This ability to move from answering to acting makes agentic AI useful but also introduces new security risks.

### **Why Agentic AI Changes the Security Problem**

A wrong answer from a chatbot may cause confusion, but an agent can **turn that mistake into an action**. If its information, memory, or connected tools are manipulated, the consequences can go much further.

##### **Key Security Threats in Agentic AI**

Agentic AI introduces security risks because an agent can access information, use tools, and take actions. The main threats can be understood through the same suspicious-login scenario.

**1. Prompt Injection and Agent Hijacking**

- An attacker may place malicious instructions in an email, document, webpage, or other content that the security agent reviews while investigating a suspicious login.
- If the agent treats this untrusted content as a command, it may change its intended task, access information it should not, or take an unintended action.

**2. Excessive Permissions and Tool Abuse**

- A security agent may need access to user activity, device information, and threat-intelligence tools, but it should not automatically have permission to disable accounts, delete logs, or modify critical systems.
- Least privilege and restricted tool access help ensure that even if an agent is manipulated, the possible impact remains limited.

**3. Sensitive Data and Memory Poisoning**

- During an investigation, the agent may process sensitive information such as user details, IP addresses, security logs, and account activity, which must be protected from unauthorized access or exposure.
- Attackers may also insert false information into the agent's context or memory, potentially influencing its current investigation or future decisions.

**4. Multi-Agent and Supply-Chain Risks**

- If multiple agents are involved in the investigation, a compromised agent could pass incorrect or malicious information to another agent and influence the overall workflow.
- External models, APIs, frameworks, plugins, and tools can introduce additional vulnerabilities, so their security also needs to be considered.

### **How Does Agentic AI Threat Modeling Work?**

Threat modeling helps security teams identify attack points, understand possible consequences, and select appropriate controls. The process can be organized into six steps.

![Agentic AI Security Threat Model](https://blog.optimumdataanalytics.com/hs-fs/hubfs/Blog%20Images/Agentic%20AI%20Security%20Threat%20Model/Agentic%20AI%20Security%20Threat%20Model.jpg?width=713&height=242&name=Agentic%20AI%20Security%20Threat%20Model.jpg)

**Fig**. Agentic AI Threat Modeling

**Step 1: Identify Assets**

- Identify what the agent can access or influence, such as **data, credentials, applications, APIs, databases, identities, and business processes**.
- In the suspicious-login scenario, this includes user information, device details, security logs, and account-related data.

**Step 2: Map the Agent**

- Map the agent's environment, including the **model, memory, tools, APIs, databases, users, and other agents**.
- For a suspicious login, trace how information moves from the alert through investigation and risk assessment to the final response.

**Step 3: Identify Trust Boundaries**

- Separate **trusted instructions** from untrusted content such as emails, webpages, uploaded documents, and external tool results.
- This helps prevent malicious content from being treated as a trusted command during the agent's investigation.

**Step 4: Identify Threats & Analyze Attack Paths**

- Identify threats such as prompt injection, data leakage, tool misuse, memory poisoning, privilege abuse, and compromised dependencies.
- Trace how each threat could move through the system and affect sensitive data, tools, or real-world actions.

**Step 5: Assess Risk & Apply Security Controls**

- Assess threats based on their likelihood and potential impact, then prioritize the risks that require stronger protection.
- Apply controls such as least privilege, authorization, tool restrictions, guardrails, sandboxing, human approval, and logging.

**Step 6: Test, Red-Team & Monitor Continuously**

- Regularly test the agent against scenarios such as **prompt injection, tool misuse, data leakage, privilege abuse, and unexpected behavior**.
- Continuously monitor and review agent activity because changes to tools, integrations, or data can introduce new risks.

### **Human Approval: A Separate Security Control**

Not every action needs a person to approve it. The decision should depend on what the agent is about to do and what could happen if it gets it wrong.

In the **suspicious-login scenario**, some actions are straightforward. The agent can check threat intelligence or create a ticket on its own. But an action like disabling an account can affect a real user, so it may need human review. Actions such as deleting security evidence or changing a production system need even more control because they may be difficult to reverse.

A simple way to decide when approval is needed is to ask:

- **Impact**: What happens if the action is wrong?
- **Reversibility**: Can the action be undone easily?
- **Confidence**: How certain is the agent about its decision?
- **Data sensitivity**: Does the action involve sensitive information?

The more serious the impact, harder the action is to reverse, lower the agent's confidence, or more sensitive the data, the stronger the case for human approval before the action is taken.

### **Scenario: When a Security Agent Investigates a Suspicious Login**

Imagine a security operations team receives, **“Suspicious login detected.”**

![Steps Security Agent Investigates a Suspicious Login](https://blog.optimumdataanalytics.com/hs-fs/hubfs/Blog%20Images/Agentic%20AI%20Security%20Threat%20Model/Steps%20Security%20Agent%20Investigates%20a%20Suspicious%20Login.jpg?width=395&height=408&name=Steps%20Security%20Agent%20Investigates%20a%20Suspicious%20Login.jpg)

**Fig.** Steps Security Agent Investigates a Suspicious Login

Instead of simply forwarding the alert to an analyst, the agent can:

**1. Investigate User & Device**: Verify the user's identity and check device details.

**2.Threat Intelligence**: Analyze the IP address and compare it with known threat information.

**3. Review Recent Activity**: Look for unusual login attempts, location changes, or other suspicious activity.

**4. Assess Risk**: Combine the available information and determine the appropriate response.

The result can then follow two paths:  
**Low Risk → Monitor  
High Risk → Alert**

This approach lets the agent respond quickly while keeping high-impact actions under control. It also gives a human a clear point to review important decisions before they affect users or business systems.

### **Handling Exceptions and Failures**

If it receives conflicting information, it should pause, verify the information, or escalate the decision. If a tool fails or an action is outside its permissions, the agent should **fail safely rather than attempt to bypass the restriction**.

For uncertain, high-impact decisions, the system should provide enough information for a human to make a quick and informed decision.

### **From Autonomy to Controlled Autonomy**

The more an agent can do, the more carefully its autonomy needs to be managed.

- **Least privilege** limits what the agent can access.
- **Guardrails** define what the agent can and cannot do.
- **Human approval** provides an additional control for actions where the impact, sensitivity, uncertainty, or lack of reversibility makes autonomous execution risky.
- **Observability** helps organizations understand what the agent received, decided, accessed, and executed.
- **Continuous testing** helps identify weaknesses before they become incidents.

**An agent should be autonomous within defined boundaries, not autonomous without boundaries.**

### **Conclusion**

Agentic AI is moving AI from systems that mainly **respond** to systems that can **reason, plan, use tools, and act**. That creates useful opportunities, but it also expands the security surface across identity, permissions, memory, data, tools, and connected systems.

Threat modeling helps organizations understand these risks before they become incidents. With **least privilege, guardrails, human approval, observability, and continuous testing**, organizations can give agents enough freedom to be useful while keeping their actions under control.

**The goal is build agents that are capable enough to help, controlled enough to trust, and observable enough to secure.**

### **References**

1. **NIST** - [Securing AI Agent Systems](https://www.nist.gov/news-events/news/2026/01/caisi-issues-request-information-about-securing-ai-agent-systems?utm_source=chatgpt.com)
2. **NIST** - [AI Agent Hijacking Evaluations](https://www.nist.gov/news-events/news/2025/01/technical-blog-strengthening-ai-agent-hijacking-evaluations?utm_source=chatgpt.com)
3. **OWASP** - [Agentic AI Threats and Mitigations](https://genai.owasp.org/resource/agentic-ai-threats-and-mitigations/?utm_source=chatgpt.com)
4. **MITRE** - [ATLAS](https://atlas.mitre.org/?utm_source=chatgpt.com)
5. **Google** - [Secure AI Framework (SAIF)](https://safety.google/intl/en_us/safety/saif/?utm_source=chatgpt.com)
6. **Microsoft** - [Agentic AI Security](https://www.microsoft.com/en-us/security/business/security-101/what-is-agentic-ai-security?utm_source=chatgpt.com)

 

**Tags:** 

[AI,](https://blog.optimumdataanalytics.com/tag/ai) [AI Agent,](https://blog.optimumdataanalytics.com/tag/ai-agent) [Cybersecurity,](https://blog.optimumdataanalytics.com/tag/cybersecurity) [AI Security,](https://blog.optimumdataanalytics.com/tag/ai-security) [Prompt Injection](https://blog.optimumdataanalytics.com/tag/prompt-injection)

### Related Articles

##### [![Microsoft Agent Framework (MAF): Building Production-Ready AI Agents at Scale](https://blog.optimumdataanalytics.com/hs-fs/hubfs/Blog%20Images/Microsoft%20Agent%20Framework%20(MAF)-%20Building%20Production-Ready%20AI%20Agents%20at%20Scale/Microsoft%20Agent%20Framework%20(MAF).png?width=520&height=294&name=Microsoft%20Agent%20Framework%20(MAF).png) AI • Sep 17, 2026, 8:00:00 AM Microsoft Agent Framework (MAF): Building Production-Ready AI Agents at Scale 5 min read](https://blog.optimumdataanalytics.com/microsoft-agent-framework-maf-building-production-ready-ai-agents-at-scale)

##### [![Enterprise Connectors for Multi-Agent Systems- Seamless Integration](https://blog.optimumdataanalytics.com/hs-fs/hubfs/Blog%20Images/Enterprise%20Connectors%20for%20Multi-Agent%20Systems-%20Seamless%20Integration/Enterprise%20Connectors%20for%20Multi-Agent%20Systems%20Seamless%20Integration.png?width=520&height=294&name=Enterprise%20Connectors%20for%20Multi-Agent%20Systems%20Seamless%20Integration.png) AI • Sep 7, 2026, 8:00:00 AM Enterprise Connectors for Multi-Agent Systems- Seamless Integration 6 min read](https://blog.optimumdataanalytics.com/enterprise-connectors-for-multi-agent-systems-seamless-integration)

- [Home](http://blog.optimumdataanalytics.com/)
- [About](http://blog.optimumdataanalytics.com/about)
- [Offerings](http://blog.optimumdataanalytics.com/offerings)
- [Careers](http://blog.optimumdataanalytics.com/careers)

<https://www.facebook.com/OptimumDataAnalytics> <https://www.instagram.com/optimumdataanalytics/> <https://www.linkedin.com/company/optimum-data-analytics/> <https://www.youtube.com/results?search_query=optimum+data+analytics>

[Join Our Newsletter](https://optimumdataanalytics.com/newsletter/)

 Pune(HQ) | Udaipur | England

 ©2025 Optimum Data Analytics Pvt. Ltd. All rights reserved.

[Terms & Conditions](https://optimumdataanalytics.com/terms-and-conditions/) [Privacy Policy](https://optimumdataanalytics.com/privacy/)

```json
{
  "@context" : "https://schema.org",
  "@type" : "BlogPosting",
  "author" : {
    "@type" : "Person",
    "name" : "Sukhada Khade",
    "url" : "https://blog.optimumdataanalytics.com/author/sukhada-khade"
  },
  "dateModified" : "2026-10-01T02:30:00.586Z",
  "datePublished" : "2026-10-01T02:30:00.000Z",
  "headline" : "Agentic AI Security Threat Model",
  "image" : [ "https://blog.optimumdataanalytics.com/hubfs/Blog%20Images/Agentic%20AI%20Security%20Threat%20Model/Agentic%20AI%20security%20threat.png" ],
  "mainEntityOfPage" : {
    "@id" : "https://blog.optimumdataanalytics.com/agentic-ai-security-threat-model",
    "@type" : "WebPage"
  },
  "publisher" : {
    "@type" : "Organization",
    "logo" : {
      "@type" : "ImageObject",
      "url" : "https://blog.optimumdataanalytics.com/hubfs/Optimum-Data-Analytics-1-e1749546723829.png"
    },
    "name" : "Optimum Data Analytics"
  }
}
```