SCW-Treuhandagent: KI

Vollständige Sichtbarkeit und Kontrolle über KI-generierten Code. Innovieren Sie schnell und sicher.

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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.

Skalierbar und ansprechend

Observability

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

Skalierbar und ansprechend

Governance

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

Skalierbar und ansprechend

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

    Learn more
    Trust agent
    Häufig gestellte Fragen (FAQ)

    Häufig gestellte Fragen (FAQ)

    Warum sollte ich mich um die Risiken von KI/LLM-generiertem Code in meinem SDLC kümmern?

    Da Entwickler zunehmend KI-Codierungstools einsetzen, wird eine wichtige neue Risikoebene in SDLCs eingeführt. Umfragen zeigen, dass 78% der Entwickler diese Tools inzwischen verwenden. Studien zeigen jedoch, dass bis zu 50% des KI-generierten Codes Sicherheitslücken aufweisen.

    Dieser Mangel an Governance und die Diskrepanz zwischen Entwicklerwissen und Codequalität können schnell außer Kontrolle geraten, da jede unsichere KI-generierte Komponente die Angriffsfläche Ihres Unternehmens vergrößert und die Bemühungen zum Risikomanagement und zur Einhaltung der Vorschriften erschwert.

    Lesen Sie mehr in diesem Whitepaper: KI-Programmierassistenten: Ein Leitfaden zur sicherheitssicheren Navigation für die nächste Generation von Entwicklern

    Welche Modelle und Tools erkennt Trust Agent: AI?

    Trust Agent: KI sammelt Signale von KI-Assistenten und agentischen Codierungstools wie GitHub Copilot, Cline, Roo Code usw. und den LLMs, die sie antreiben.

    Derzeit erkennen wir alle Modelle, die von OpenAI, Amazon Bedrock, Google Vertex AI und Github Copilot bereitgestellt werden.

    Wie wird Trust Agent: AI installiert?

    Wir stellen Ihnen eine VSIX-Datei für die manuelle Installation in Visual Studio Code zur Verfügung. Die automatische Bereitstellung über MDM-Skripts (Mobile Device Management) für Intune, Jamf und Kanji wird in Kürze verfügbar sein.