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AI Code AI Detection in Development
Bridge the gap between security and dev by uncovering where and when AI code is used and take action to ensure proper security controls are in place - without slowing software delivery.
Benefits of AI Discovery
Find AI-generated code
Legit provides a full view of the development environment, including code derived from AI-generated coding tools (e.g., GitHub Copilot).
Gain Full Visibility
By gaining a full view of the application environment, including repositories using LLM, MLOps services, and code generation tools, Legit’s platform offers the context necessary to understand and manage an application’s security posture.
Enforce Policies
Legit Security detects LLM and GenAI development and enforces organizational security policies, such as ensuring all AI-generated code gets reviewed by a human.
Real-Time Alerts
Legit can immediately notify security teams when users install AI code-generation tools, providing greater transparency and accountability.
Stop Vulnerabilities
Legit’s platform provides guardrails to prevent the deployment of vulnerable code to production, including that delivered via AI tools.
Stop Unknown Vulnerabilities
AI-generated code may contain unknown vulnerabilities or flaws that put the entire application at risk.
Avoid Legal Risk
AI-generated code can introduce legal issues if copyright restrictions are in place.
Prevent Data Exposure
Legit helps prevent improper implementation of AI features, which can lead to data exposure.
Related Resources
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Read Nowwhite papersThe Top 6 Unknown SDLC Risks Legit Uncovers
Find out the unknown SDLC risks we most often unearth, and how to prevent them.
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Read NowblogsLegit Discovers "AI Jacking" Vulnerability in Popular Hugging Face AI Platform
Our research revealed how attackers could leverage Hugging Face, the popular AI development and collaboration platform, to carry out an AI supply chain attack that could impact tens of thousands of developers and researchers.
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Read NowblogsThe Risks of Being Blind to AI in Your Own Organization
As artificial intelligence (AI) and large language models (LLMs) like GPT become more entwined with our lives, it is critical to explore the security implications of these tools, especially the challenges arising from a lack of visibility into AI-generated code and LLM embedding in applications.