TechLatest

Posted on Jul 15 • Originally published at Medium on Jul 13

HackAgent Tutorial: Secure AI Agents Against Prompt Injection, Jailbreaks, and Tool Misuse

#vulnerability #aiagentsecurity #aisecurity #hackagent

Large Language Models (LLMs) have rapidly evolved from simple chatbots into autonomous AI agents capable of browsing the web, executing code, interacting with APIs, accessing databases, and performing complex multi-step tasks. Modern AI frameworks such as OpenAI SDK, LangChain, Google ADK, LiteLLM, and Model Context Protocol (MCP) make it easier than ever to build intelligent applications that can reason, plan, and act on behalf of users.

However, as AI agents become more capable, they also introduce an entirely new class of security risks. Unlike traditional web applications, AI agents can be manipulated through natural language. A carefully crafted prompt may convince an agent to ignore its original instructions, reveal confidential information, misuse connected tools, or perform actions it was never intended to execute.

Some of the most common threats include:

Prompt Injection — Malicious prompts that override an agent’s intended behavior.
Jailbreak Attacks — Attempts to bypass built-in safety policies and content restrictions.
Goal Hijacking — Redirecting an AI agent away from its original objective.
Tool Misuse — Tricking an agent into abusing connected tools such as GitHub, Slack, Gmail, databases, or external APIs.
System Prompt Leakage — Extracting hidden instructions that define the agent’s behavior.

These vulnerabilities can have serious consequences, especially for production AI systems connected to sensitive data or external services.

This is where HackAgent comes in.

HackAgent is an open-source AI Agent Security Testing Toolkit designed to help developers, AI engineers, and security researchers evaluate the robustness of AI agents against real-world adversarial attacks. Instead of manually crafting hundreds of malicious prompts, HackAgent automates the entire security evaluation process using research-backed attack techniques such as AdvPrefix, AutoDAN-Turbo, PAIR, TAP, FlipAttack, Best-of-N, CipherChat, PAP, and more.

Whether you’re building a customer support chatbot, a coding assistant, a research agent, or an enterprise AI application, HackAgent helps identify vulnerabilities before they can be exploited in production.

In this tutorial, you’ll learn how to install HackAgent, explore its interactive Terminal User Interface (TUI), understand its security testing workflow, configure attacks, interpret results, and use the toolkit to strengthen the security of your AI agents.

By the end of this guide, you’ll have a solid understanding of how HackAgent works and how it can be integrated into your AI development and security testing workflow.

Installing HackAgent

HackAgent is distributed as a Python package and works on Linux, macOS, and Windows. The recommended approach is to install it inside a Python virtual environment to avoid dependency conflicts.

Prerequisites

Before installing HackAgent, ensure your system meets the following requirements:

Python 3.10 or later
pip
Terminal or Command Prompt
Internet connection for package installation

You can verify your Python installation by running:

python3 --version

python --version

If Python is not installed, download the latest version from the official Python website.

Step 1: Create a Virtual Environment

Create an isolated Python environment for HackAgent.

python3 -m venv .ve

This creates a new directory named .venv containing an isolated Python environment.

Step 2: Activate the Environment

macOS / Linux

source .venv/bin/activate

Windows (PowerShell)

.venv\Scripts\Activate.ps1

Windows (Command Prompt)

.venv\Scripts\activate

Once activated, your terminal should display something similar to:

(.venv)

indicating that the virtual environment is active.

Step 3: Install HackAgent

Install the latest release directly from PyPI.

pip install hackagent

The installer automatically downloads HackAgent along with all required dependencies.

Step 4: Verify the Installation

After installation, verify that everything is working correctly.

hackagent --help

hackagent --version

If the installation was successful, you’ll see the installed version along with the available CLI commands.

Your First HackAgent Run

Once HackAgent is installed, you can begin evaluating an AI agent for common security vulnerabilities.

A typical security assessment follows this workflow:

Create or connect an AI agent
        │
        ▼
Choose an attack technique
        │
        ▼
Generate adversarial prompts
        │
        ▼
Execute attacks
        │
        ▼
Evaluate responses
        │
        ▼
Generate security report

HackAgent automates this entire pipeline, allowing you to focus on identifying and fixing vulnerabilities rather than manually crafting attack prompts.

Getting Started with HackAgent CLI

Once HackAgent is installed successfully, you’re ready to explore its command-line interface (CLI). The CLI provides an easy way to launch security assessments, manage reports, configure settings, and interact with different attack techniques.

To display all available commands and options, run:

hackagent --help

You should see an output similar to this:

Usage: hackagent [OPTIONS] COMMAND [ARGS]...

Commands:
  attack Run a security attack
  report View reports
  dashboard Launch dashboard
  web Open HackAgent web interface
  config Configure HackAgent
  ...

Note: The available commands may vary slightly depending on the HackAgent version you’re using.

Launch the Interactive CLI

Once HackAgent is installed successfully, you’re ready to explore its interactive Terminal User Interface (TUI). Instead of relying on long command-line arguments, the TUI provides a visual interface for configuring target agents, selecting attack techniques, monitoring attack execution, viewing results, and managing configuration — all from your terminal.

To launch the interactive interface, simply run:

hackagent

Within a few seconds, HackAgent opens a full-screen terminal dashboard similar to the one shown below.

Understanding the HackAgent Interface

The HackAgent TUI is divided into four primary sections, each designed for a different stage of the AI security testing workflow.

Target Agents
Attacks
Results
Config

You can navigate between these tabs using your keyboard, making it easy to manage the entire testing process without leaving the terminal.

1. Target Agents

The Target Agents tab is your starting point. Before launching any security assessment, you need to define the AI agent you want to evaluate.

This page displays:

Total registered target agents
Active agents
Current system status
List of configured agents
Agent metadata

Initially, the list will be empty because no target agent has been configured.

Once you add an agent, it will appear in the table along with details such as:

Agent Name
Agent Type
Endpoint
Status
Creation Time

This allows you to manage multiple AI agents from a single interface.

Typical examples include:

Customer Support Chatbot
Travel Booking Agent
LangChain Agent
OpenAI SDK Agent
Google ADK Agent
LiteLLM Application

2. Attacks

The Attacks tab is where the actual security testing takes place.

This section contains the complete attack configuration panel.

Here you can configure:

Target Agent
Attack Technique
Generator Model
Judge Model
Dataset
Guardrails
Runtime Configuration

On the right side, HackAgent displays a real-time Attack Log Viewer.

During execution, this panel shows:

Attack progress
Generated adversarial prompts
Target responses
Evaluation logs
Warnings
Errors
Execution status

The live logs make it easy to monitor long-running security evaluations without switching to another terminal.

Attack Configuration

Before starting an attack, you’ll typically configure:

Target AI Agent
Attack Method
Evaluation Dataset
Optional Guardrails
Attack Parameters

Once everything is configured, HackAgent begins generating adversarial prompts automatically and evaluates how well your AI agent withstands various attacks.

3. Results

After an attack completes, all findings are stored under the Results tab.

This section provides a centralized location for reviewing previous security assessments.

Each completed run includes information such as:

Target Agent
Attack Technique
Success or Failure
Timestamp
Security Evaluation Results

Selecting a run displays detailed information in the right-hand panel, making it easy to inspect individual attack outcomes and understand how the AI agent responded.

The Results page also includes useful features like:

Refresh results
Export results as CSV
Filter previous runs
Limit displayed records

These capabilities make it easier to analyze trends across multiple security evaluations and share reports with your team.

4. Configuration

The Config tab lets you manage HackAgent’s global settings.

From this screen, you can:

View the configuration file location
Save configuration changes
Reset settings to their default values
Validate your configuration
View system information

The bottom section also displays useful environment details such as:

Python Version
Installed HackAgent CLI Version

For example:

Python Version: 3.13.13
CLI Version: 0.11.0

This information is particularly helpful when troubleshooting installation issues or reporting bugs.

Conclusion

As AI agents become more capable and autonomous, securing them is no longer optional — it’s an essential part of the development lifecycle. Modern AI applications don’t just generate text; they interact with external tools, access sensitive data, execute workflows, and make decisions on behalf of users. This expanded functionality also increases the potential attack surface, making AI-specific threats such as prompt injection, jailbreaks, goal hijacking, tool misuse, and system prompt leakage serious security concerns.

HackAgent provides an open-source, research-backed solution for evaluating these risks through automated AI security testing. With support for multiple AI frameworks, a powerful command-line interface, an interactive Terminal User Interface (TUI), real-time attack monitoring, comprehensive reporting, and a growing collection of adversarial attack techniques, HackAgent enables developers and security teams to identify vulnerabilities before they reach production.

In this guide, you learned how to install HackAgent, verify the installation, explore its CLI, launch the interactive TUI, and understand the purpose of each major component, including Target Agents , Attacks , Results , and Configuration. These fundamentals provide a solid starting point for incorporating AI security testing into your development workflow.

However, installation is only the beginning. The real value of HackAgent comes from testing real AI agents, experimenting with different attack techniques, analyzing generated reports, and continuously improving your application’s security posture. Whether you’re building a customer support chatbot, an AI coding assistant, an enterprise knowledge agent, or a multi-agent system, regular security evaluations should become a standard part of your release process.

As the AI ecosystem continues to evolve, new attack techniques and vulnerabilities will emerge. Tools like HackAgent help developers stay ahead by making AI red teaming more accessible, repeatable, and automated.

If you’re developing AI-powered applications, now is the perfect time to start integrating security testing into your workflow. Detect vulnerabilities early, strengthen your AI agents, and build systems that are not only intelligent but also resilient against real-world attacks.