SCW 트러스트 에이전트: AI

AI 생성 코드에 대한 완벽한 가시성과 제어.빠르고 안전하게 혁신하세요.

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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.

확장 가능하고 매력적인

Observability

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

확장 가능하고 매력적인

Governance

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

확장 가능하고 매력적인

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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    Trust agent
    자주 묻는 질문 (FAQ)

    자주 묻는 질문 (FAQ)

    SDLC에서 AI/LLM 생성 코드의 위험에 신경을 써야 하는 이유는 무엇인가요?

    개발자들이 AI 코딩 도구를 점점 더 많이 활용함에 따라 SDLC에 중요한 새로운 위험 계층이 도입되고 있습니다.설문조사에 따르면 현재 개발자의 78% 가 이러한 도구를 사용하고 있는 것으로 나타났지만, 연구에 따르면 AI로 생성된 코드의 50% 가 보안 결함을 포함하고 있는 것으로 나타났습니다.

    이러한 거버넌스의 부재와 개발자 지식과 코드 품질 간의 단절은 안전하지 않은 AI 생성 구성 요소 하나하나가 조직의 공격 표면을 가중시켜 위험을 관리하고 규정 준수를 유지하기 위한 노력을 복잡하게 만들기 때문에 빠르게 통제 불능 상태가 될 수 있습니다.

    이 백서에서 자세한 내용을 읽어보십시오. AI 코딩 어시스턴트: 차세대 개발자를 위한 보안 안전 내비게이션 가이드

    트러스트 에이전트: AI가 탐지하는 모델과 도구는 무엇인가요?

    트러스트 에이전트: AI는 GitHub Copilot, Cline, Roo Code 등과 같은 AI 어시스턴트와 에이전트 코딩 도구와 이를 구동하는 LLM으로부터 신호를 수집합니다.

    현재 우리는 OpenAI, 아마존 베드락, 구글 버텍스 AI 및 깃허브 코파일럿에서 제공하는 모든 모델을 감지합니다.

    트러스트 에이전트: AI는 어떻게 설치되나요?

    Visual Studio Code에 수동으로 설치할 수 있는.vsix 파일을 제공할 예정이며, Intune, Jamf 및 Kanji용 모바일 장치 관리 (MDM) 스크립트를 통한 자동 배포도 곧 제공될 예정입니다.