AI model risk analysis

Learn how to stay two steps ahead of security risks and vulnerabilities in AI-generated code.

Challenges

Is AI for application development too risky?

While AI models can save developers precious time and significantly accelerate the release of products, they also come with heavy new security considerations.

Increased vulnerability risk

AI models often depend on open source code libraries and packages to create their output, which may potentially introduce more vulnerabilities–especially if the dependencies are not always up to date.

Decreased visibility

Security teams can’t tell what AI models were used for application development, leaving them blind to potential security threats tied to these models.

Licensing headaches

AI models come with their own set of licensing concerns that security teams are unable to manage due to blind spots when using AI.

Opportunities

Gain visibility and control

Support security teams as they find AI-related security risks, licensing concerns, and versioning challenges.

Identify AI tools

Discover which generative AI coding tools are being used in your devs’ workflows to detect AI code snippets within your code base.

Hugging Face coverage

If you want to see what AI models are being used in your applications, you need to be able to track the 350k-plus AI models indexed in Hugging Face.

Stay up to date

Maintaining control over AI model dependencies requires knowledge of each AI model’s current version and update information.

The solution

Mend AI

Mend AI identifies AI models used in your code base, helping security professionals stay ahead of outdated dependencies and licensing issues.

Identifies AI-generated code

Pre-trained model indexing

AI-BOM

Protection against outdated dependencies

Ensures compatibility and compliance

MTTR

“One of our most indicative KPIs is the amount of time for us to remediate vulnerabilities and also the amount of time developers spend fixing vulnerabilities in our code base, which has reduced significantly. We’re talking about at least 80% reduction in time.”

Andrei Ungureanu, Security Architect
Read case study
Fast, secure, compliant

“When the product you sell is an application you develop, your teams need to be fast, secure and compliant. These three factors often work in opposite directions. Mend provides the opportunity to align these often competing factors, providing Vonage with an advantage in a very competitive marketplace.”

Chris Wallace, Senior Security Architect
Read case study
Rapid results

“The biggest value we get out of Mend is the fast feedback loop, which enables our developers to respond rapidly to any vulnerability or license issues. When a vulnerability or a license is disregarded or blocked, and there is a policy violation, they get the feedback directly.”

Markus Leutner, DevOps Engineer for Cloud Solutions
Read case study

Start building a proactive AppSec program

Recent resources

How Do I Protect My AI Model?

Learn essential strategies to secure your AI models from theft, denial of service, and other threats, covering copyright issues, risk management, and secure storage practices

Read more

What Existing Security Threats Do AI and LLMs Amplify? What Can We Do About Them?

Learn about the existing security threats that AI and LLMs amplify and how to protect against them.

Read more

OWASP Top 10 for LLM Applications: A Quick Guide

Discover the OWASP Top 10 for LLM Applications in this comprehensive guide. Learn about vulnerabilities, & prevention techniques.

Read more