Command Line Interface (CLI)

Welcome to this video presentation where we will explore the automation options available through the command line interface or CLI as part of Cisco AI defense. This session will provide an in depth understanding of how to leverage the CLI for efficient automation and cybersecurity defenses.00:04Using state of the art AI technologies, let's begin this journey into enhancing our security posture through the power of automation.00:20In this slide, we are discussing the Cisco AI defense CLI. This command line interface is designed to simplify and accelerate the process of scanning AI models and associated files for security risks. Its primary advantage lies in its developer friendly approach, which integrates seamlessly into local development environments, continuous integration pipelines.00:28And controlled evaluation settings. The CLI supports the scanning of various AI model formats without the need for initial downloads, streamlining the workflow integration process. Importantly, it outputs scan results in JSON format, facilitating easy parsing and integration into automated CICD pipelines. Per use an AI defense API.00:49PI token and base URL are required.01:09Let's discuss the supported platforms for the AI defense CLI. It is distributed for both the architectures such as AMD 64 and for MACOS. It's available for both Apple silicon based chips as well as for Intel based chips. Linux binary format is compatible with systems through methods like the Windows subsystem for Linux, WSL for Windows.01:13Those users. This versatility ensures that a broad range of users can leverage the CLI according to their platforms.01:33Let's see how to install the Cisco AI defense CLI via GitHub. Begin by cloning the GitHub repo mentioned here. Once cloned, change the directory to where it's cloned, then run the make command. This is done using the command provided. After setting up, you can use the command line help feature to explore its functionalities and capabilities. As a prerequisite, go live.01:41Line must be installed prior to installing the Cisco AI defense CLI.02:01In this segment, we'll cover how to install the Cisco AI defense CLI binary. Begin by downloading the binary from the specified Cisco software download page, once downloaded, change the permissions of the binary file to make it executable. This is done using the command provided. After setting up, you can use the command line help feature to explore its functionality.02:07These and capabilities.02:27This slide covers the critical aspect of authentication and configuration for the CLI. Successful operation requires an AI defense API token and a base URL pertinent to your environment. From a security standpoint, the protocol ensures that model files are transmitted securely to Cisco AI defense for analysis. Note that NO credentials are embedded within the binary.02:30Itself an authentication is managed through tenant scoped API tokens. This setup underpins the integrity and confidentiality of data handled during the scanning process.02:50The authentication process with a Cisco AI defense CLI involves generating and configuring an API key. You have three methods to provide credentials using environment variables, which is recommended for CICD workflows creating a configuration file such as.config.TOML or directly via command line arguments. Each method off.03:02There's flexibility depending on your operational environment and security practices. Remember to use your specific regions based URL during these configurations.03:22Now let's explore the model scan command. This command manages AI or ML model security scans, offering several capabilities. Running a local scan, triggering a cloud based scan, listing previous scans, and retrieving detailed information about specific scans. The examples demonstrate how you can execute various types of scans to suit your security assessment.03:32Needs, utilizing the flexibility of the CLI for robust and effective scanning.03:52Here, we detail what the Cisco AI defense CLI accomplishes. This tool is designed to perform local validation of model files prior to secure uploads for cloud based security analysis. Once the analysis is complete, the results are presented in JSON format as shown in this output section. This format is optimal for integration into various automated processing and reporting.03:58Systems, allowing teams to easily manage and respond to potential security risks highlighted during the scans.04:19Here, this example shows the command that we can run to perform the model scan on a repository. Once the analysis is complete, the results are presented in JSON format. This command scans all the supported files from that repository. The MCP scan command focuses on managing model context protocol server security scans.04:26This section introduces various commands available for MCP servers such as registration, deletion, running scans, and pulling detailed scan reports. Using the command, you can register and monitor MCP servers, trigger on demand scans, and manage server data securely and efficiently. These capabilities support continuous oversight of server security infrast.04:46Structure.05:06With the AI bomb command, you can manage the AI bill of materials for AI and ML applications. This functionality allows you to generate, manage, and explore AI bills of materials reports, which are crucial for maintaining an overview of all components within an AI ML application. This command suite supports component listing and provides a summary of bombs to.05:09Logistics enabling comprehensive management of AI ML projects.05:29Thank you for taking the time to engage with our presentation. We hope it provided valuable insights into using the Cisco AI defense CLI to enhance AI model security. Your attention and participation are greatly appreciated, and we look forward to addressing any further questions you might have. Please don't hesitate to reach out for more information or support.05:35Thank you once again for being part of this session.05:53