From 1d8d0324b336d507388b3f9a470003b6a164858f Mon Sep 17 00:00:00 2001 From: sburuiana-snyk Date: Fri, 26 Jun 2026 13:40:28 +0000 Subject: [PATCH] chore: new aibom languages --- developer-tools/snyk-cli/cli-commands-and-options-summary.md | 2 +- developer-tools/snyk-cli/commands/README.md | 2 +- developer-tools/snyk-cli/commands/aibom.md | 2 +- .../snyk-cli/cli-commands-and-options-summary.md | 2 +- docs/developer-tools/snyk-cli/commands/README.md | 2 +- docs/developer-tools/snyk-cli/commands/aibom.md | 2 +- .../quickstart-guides-for-snyk-studio/claude-code-guide.md | 2 +- .../quickstart-guides-for-snyk-studio/gemini-cli-guide.md | 2 +- 8 files changed, 8 insertions(+), 8 deletions(-) diff --git a/developer-tools/snyk-cli/cli-commands-and-options-summary.md b/developer-tools/snyk-cli/cli-commands-and-options-summary.md index 36f826c94b16..cf9a281e4c91 100644 --- a/developer-tools/snyk-cli/cli-commands-and-options-summary.md +++ b/developer-tools/snyk-cli/cli-commands-and-options-summary.md @@ -100,7 +100,7 @@ Check an SBOM for vulnerabilities in open-source packages. ### [`snyk aibom`](commands/aibom.md) -Generates an AI-BOM for a local software project that is written in Python, to help you understand what AI models, datasets, tools, and so on are used in that project. +Generates an AI-BOM for a local software project written in Python, Java, JavaScript, or Go, to help you understand what AI models, datasets, tools, and so on are used in that project. ### [`snyk apps`](../snyk-api/using-specific-snyk-apis/snyk-apps-apis/create-a-snyk-app-using-the-snyk-cli.md) diff --git a/developer-tools/snyk-cli/commands/README.md b/developer-tools/snyk-cli/commands/README.md index e0668fa92c6b..2eff6aa28a6d 100644 --- a/developer-tools/snyk-cli/commands/README.md +++ b/developer-tools/snyk-cli/commands/README.md @@ -50,7 +50,7 @@ Generate or test an SBOM document in ecosystems supported by Snyk. ### [`snyk aibom`](aibom.md) -Generates an AIBOM for a local software project that is written in Python, to understand what AI models, datasets, tools, and so on are used in that project. +Generates an AIBOM for a local software project written in Python, Java, JavaScript, or Go, to understand what AI models, datasets, tools, and so on are used in that project. ### [`snyk aibom test`](aibom-test.md) diff --git a/developer-tools/snyk-cli/commands/aibom.md b/developer-tools/snyk-cli/commands/aibom.md index d017bc91862b..25c674c0ce3e 100644 --- a/developer-tools/snyk-cli/commands/aibom.md +++ b/developer-tools/snyk-cli/commands/aibom.md @@ -13,7 +13,7 @@ ## Description -The `snyk aibom` command generates an AI-BOM for a local software Project that is written in Python. You can use the `snyk aibom` command to identify AI models, datasets, and map the AI supply chain, including connections to external tools and services using the Model Context Protocol (MCP). +The `snyk aibom` command generates an AI-BOM for a local software Project written in Python, Java, JavaScript, or Go. You can use the `snyk aibom` command to identify AI models, datasets, and map the AI supply chain, including connections to external tools and services using the Model Context Protocol (MCP). The supported format is CycloneDX v1.6 (JSON). diff --git a/docs/developer-tools/snyk-cli/cli-commands-and-options-summary.md b/docs/developer-tools/snyk-cli/cli-commands-and-options-summary.md index f1ec7592468d..ce5fa9d5fb21 100644 --- a/docs/developer-tools/snyk-cli/cli-commands-and-options-summary.md +++ b/docs/developer-tools/snyk-cli/cli-commands-and-options-summary.md @@ -100,7 +100,7 @@ Check an SBOM for vulnerabilities in open-source packages. ### [`snyk aibom`](commands/aibom.md) -Generates an AI-BOM for a local software project that is written in Python, to help you understand what AI models, datasets, tools, and so on are used in that project. +Generates an AI-BOM for a local software project written in Python, Java, JavaScript, or Go, to help you understand what AI models, datasets, tools, and so on are used in that project. ### [`snyk apps`](../../snyk-api/using-specific-snyk-apis/snyk-apps-apis/create-a-snyk-app-using-the-snyk-cli.md) diff --git a/docs/developer-tools/snyk-cli/commands/README.md b/docs/developer-tools/snyk-cli/commands/README.md index cab7bea1dae4..1c06e4de7ef6 100644 --- a/docs/developer-tools/snyk-cli/commands/README.md +++ b/docs/developer-tools/snyk-cli/commands/README.md @@ -50,7 +50,7 @@ Generate or test an SBOM document in ecosystems supported by Snyk. ### [`snyk aibom`](aibom.md) -Generates an AIBOM for a local software project that is written in Python, to understand what AI models, datasets, tools, and so on are used in that project. +Generates an AIBOM for a local software project written in Python, Java, JavaScript, or Go, to understand what AI models, datasets, tools, and so on are used in that project. ### [`snyk aibom test`](aibom-test.md) diff --git a/docs/developer-tools/snyk-cli/commands/aibom.md b/docs/developer-tools/snyk-cli/commands/aibom.md index d017bc91862b..25c674c0ce3e 100644 --- a/docs/developer-tools/snyk-cli/commands/aibom.md +++ b/docs/developer-tools/snyk-cli/commands/aibom.md @@ -13,7 +13,7 @@ ## Description -The `snyk aibom` command generates an AI-BOM for a local software Project that is written in Python. You can use the `snyk aibom` command to identify AI models, datasets, and map the AI supply chain, including connections to external tools and services using the Model Context Protocol (MCP). +The `snyk aibom` command generates an AI-BOM for a local software Project written in Python, Java, JavaScript, or Go. You can use the `snyk aibom` command to identify AI models, datasets, and map the AI supply chain, including connections to external tools and services using the Model Context Protocol (MCP). The supported format is CycloneDX v1.6 (JSON). diff --git a/docs/integrations/snyk-studio-agentic-integrations/quickstart-guides-for-snyk-studio/claude-code-guide.md b/docs/integrations/snyk-studio-agentic-integrations/quickstart-guides-for-snyk-studio/claude-code-guide.md index 0cb2ba544f4c..ac33b71788ef 100644 --- a/docs/integrations/snyk-studio-agentic-integrations/quickstart-guides-for-snyk-studio/claude-code-guide.md +++ b/docs/integrations/snyk-studio-agentic-integrations/quickstart-guides-for-snyk-studio/claude-code-guide.md @@ -34,7 +34,7 @@ Select **View Tools** to look at all of the commands and tooling Snyk uses as pa | Tool | Description | | --------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `snyk_aibom` | Generates an AI Bill of Materials (AI-BOM) for Python software projects in CycloneDX v1.6 JSON format. This experimental feature analyzes local Python projects to identify AI models, datasets, tools, and other AI-related components. Requires an active internet connection and access to the experimental feature (available on request). The command must be run from within a Python project directory and requires the CLI from the preview release channel. | +| `snyk_aibom` | Generates an AI Bill of Materials (AI-BOM) for Python, Java, JavaScript, and Go software projects in CycloneDX v1.6 JSON format. This experimental feature analyzes local projects written in those languages to identify AI models, datasets, tools, and other AI-related components. Requires an active internet connection and access to the experimental feature (available on request). The command must be run from within a supported project directory and requires the CLI from the preview release channel. | | `snyk_auth` | Authenticate the user with Snyk. | | `snyk_code_scan` |

Performs Static Application Security Testing (SAST) directly from the Snyk MCP. It analyzes an application's source code with a SAST scan to identify security vulnerabilities and weaknesses without executing the code.

Supported languages:

Apex, C/C++, Dart and Flutter, Elixir, Go, Groovy, Java and Kotlin, Javascript, .NET, PHP, Python, Ruby, Rust, Scala, Swift and Objective-C, Typescript, VB.NET

| | `snyk_container_scan` | Scans container images for known vulnerabilities in OS packages and application dependencies. | diff --git a/docs/integrations/snyk-studio-agentic-integrations/quickstart-guides-for-snyk-studio/gemini-cli-guide.md b/docs/integrations/snyk-studio-agentic-integrations/quickstart-guides-for-snyk-studio/gemini-cli-guide.md index 45ef5026e93a..9e83ed3dea41 100644 --- a/docs/integrations/snyk-studio-agentic-integrations/quickstart-guides-for-snyk-studio/gemini-cli-guide.md +++ b/docs/integrations/snyk-studio-agentic-integrations/quickstart-guides-for-snyk-studio/gemini-cli-guide.md @@ -30,7 +30,7 @@ The list of tools installed as a part of Snyk Studio are listed below. These too | Tool | Description | | --------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `snyk_aibom` | Generates an AI Bill of Materials (AI-BOM) for Python software projects in CycloneDX v1.6 JSON format. This experimental feature analyzes local Python projects to identify AI models, datasets, tools, and other AI-related components. Requires an active internet connection and access to the experimental feature (available on request). The command must be run within a Python project directory and requires the CLI from the preview release channel. | +| `snyk_aibom` | Generates an AI Bill of Materials (AI-BOM) for Python, Java, JavaScript, and Go software projects in CycloneDX v1.6 JSON format. This experimental feature analyzes local projects written in those languages to identify AI models, datasets, tools, and other AI-related components. Requires an active internet connection and access to the experimental feature (available on request). The command must be run from within a supported project directory and requires the CLI from the preview release channel. | | `snyk_auth` | Authenticates the user with Snyk. | | `snyk_code_scan` |

Performs Static Application Security Testing (SAST) directly from the Snyk MCP. This command analyzes an application's source code with a SAST scan to identify security vulnerabilities and weaknesses without executing the code.

Snyk supports:

Apex, C/C++, Dart and Flutter, Elixir, Go, Groovy, Java and Kotlin, Javascript, .NET, PHP, Python, Ruby, Rust, Scala, Swift and Objective-C, Typescript, VB.NET

| | `snyk_container_scan` | Scans container images for known vulnerabilities in OS packages and application dependencies. |