SCW Trust Agent: IA

Visibilidad y control totales sobre el código generado por IA. Innovar de forma rápida y segura.

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The Era of AI

Improving Productivity, But Increasing Risk

The widespread adoption of AI coding tools presents a new challenge: a lack of visibility and governance over AI-generated code.

84%

of developers use or plan to use AI tools in their development process.

Stack Overflow

45%

of AI-generated code contains security vulnerabilities.

Veracode

81%

of security teams lack visibility into AI usage in their codebase.

Cycode

The Benefits of Trust Agent: AI

The new AI capabilities of SCW Trust Agent provides the deep observability and control you need to confidently manage AI adoption in your secure software development lifecycle (SDLC) without sacrificing security.

Escalable y atractivo

Observability

Gain deep visibility into AI-assisted development, including which developers are using which AI/LLM models and on what code bases.

Escalable y atractivo

Governance

Automate policy enforcement to ensure AI-enabled developers meet secure coding standards before their contributions are accepted in critical repos.

Escalable y atractivo

Risk Metrics and Benchmarking

Connect AI-generated code to developer skill levels, vulnerabilities produced, and actual commits to understand true security risk being introduced.

The Challenge of AI in Your SDLC

Without a way to manage AI usage, CISO’s, AppSec and engineering leaders are exposed to new risks and questions they can not answer. A few concerns include:

  • Lack of visibility into which developers are using which unapproved models.
  • Uncertainty around the security proficiency of developers using AI.
  • No insights into what percentage of contribution code is AI-generated
  • Inability to enforce policy and governance to manage AI tool risk.
AI UI

A Unique Combination of Signals

SCW empowers organizations to embrace the speed of AI-driven development without sacrificing security. AI Signals is the first solution to provide visibility and governance by correlating a unique combination of three key signals to understand AI-assisted developer risk at the commit level.

  • AI Coding Tool Usage: Insights into who is using what AI tools, which LLM models on which code bases.
  • Captured in real-time: Trust Agent: AI intercepts AI-generated code on the developer’s computer and IDE.
  • Developer secure coding skills: We provide a clear understanding of a developer’s secure coding proficiency, which is the foundational skill required to use AI responsibly.
A Unique Combination of Signals

AI Usage Visibility

Get a full picture of AI coding assistants and agents, as well as the LLMs powering them. Discover unapproved tools and models. No more “shadow AI.”

AI Usage Visibility

Observability into AI-Assisted Commits by Developer and Code Base

Gain deep visibility into AI-assisted software development, including which developers are using which LLM models and on which code bases.

Observability into AI Assisted Commits

Integrated Governance and Control

Connect AI-generated code to actual commits to understand the true security risk being introduced. Automate policy enforcement to ensure AI-enabled developers meet secure coding standards before their contributions are accepted.

Trust Score
How it works

Discover AI Insights

Trust Agent: AI gives companies visibility over the risks introduced by developers using LLM-backed, code-generating tools. The solution does this in three steps:

  • Inspect AI-Generated Code Traffic: Trust Agent: AI is deployed as a simple IDE plugin or endpoint agent that intercepts and monitors the code generated by AI coding tools, such as GitHub Copilot, ChatGPT, Google Gemini or Cursor.
  • Enrich with Developer Skill Level: The final step involves enriching this data with the contributing developer’s secure coding proficiency, as measured by SCW’s industry-leading Secure Code Learning product.

By correlating these key signals, Trust Agent: AI provides actionable information to security and engineering teams including unsanctioned LLM model use and identification of developers with limited secure coding knowledge who are committing AI-generated code.

How it works

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    Preguntas frecuentes (FAQ)

    Preguntas frecuentes (FAQ)

    ¿Por qué deberían preocuparme los riesgos del código generado por IA o LLM en mi SDLC?

    A medida que los desarrolladores aprovechan cada vez más las herramientas de codificación de IA, se está introduciendo un nuevo nivel de riesgo crítico en los SDLC. Las encuestas muestran que el 78% de los desarrolladores utilizan ahora estas herramientas, pero los estudios revelan que hasta el 50% del código generado por la IA contiene fallos de seguridad.

    Esta falta de gobierno y la desconexión entre el conocimiento de los desarrolladores y la calidad del código pueden salirse de control rápidamente, ya que cada componente inseguro generado por la IA aumenta la superficie de ataque de la organización, lo que complica los esfuerzos por gestionar el riesgo y mantener el cumplimiento.

    Lea más en este documento técnico: Asistentes de codificación de IA: una guía para una navegación segura para la próxima generación de desarrolladores

    ¿Qué modelos y herramientas detecta Trust Agent: AI?

    Agente de confianza: la IA recopila señales de los asistentes de IA y las herramientas de codificación de agencias, como GitHub Copilot, Cline, Roo Code, etc., y de los LLM que las impulsan.

    Actualmente detectamos todos los modelos proporcionados por OpenAI, Amazon Bedrock, Google Vertex AI y Github Copilot.

    ¿Cómo se instala Trust Agent: AI?

    Le proporcionaremos un archivo.vsix para la instalación manual en Visual Studio Code, y pronto estará disponible la implementación automatizada mediante scripts de administración de dispositivos móviles (MDM) para Intune, Jamf y Kanji.

    ¿Cómo me registro en AI Insights?

    AI Insights se encuentra actualmente en fase beta cerrada. Si está interesado, inscríbase en nuestra lista de espera.