Secure AI-Assisted Development with Context-Rich SCA

SCA, but with reachability analysis that cuts 92% of noise at

Moody's

Sensitive financial and risk-related data needs more than superficial scanning. Noisy findings and confusing user interfaces make managing vulnerabilities harder than it has to be. Endor Labs prioritizes function-reachable vulnerabilities, and provides specific evidence needed to fix what (actually) matters.

How it works

1

Identify all dependencies

Go beyond checkbox SCA to discover all direct and transitive dependencies, including AI models and services.

2

Prioritize by danger

Combine reachability and EPSS to determine which vulnerabilities are the most critical, so you can remediate those first.

3

Fix faster

Identify upgrades that can be performed without risk of breaking changes and help engineering plan for the hard ones.

Securing code written by humans and AI at:

We have been pleasantly surprised about the lack of friction when trying new features outside, like container scanning, that are outside the traditional SCA scope. It took us just five minutes to set up a CircleCI job and give it a container from our registry, and we were immediately seeing results."

SCA | Josiah Bruner | Jellyfish

Josiah Bruner

Sr Security Engineer, Jellyfish

Get an accurate inventory

Identify

Know exactly what's in Moody's code.

If you're accelerating development with a growing mix of open source, internal services, and AI-generated components, Endor Labs gives you the deep visibility needed to govern this evolving software supply chain with confidence.

We use an unparalleled knowledge base of open source libraries, code relationships, and AI-related components to produce a complete, accurate view of your third-party dependencies, whether they come from traditional packages, AI-generated code, or AI services integrated into Moody’s applications.

AI Security Code Review

Get the context and precision to secure code at Moody's, no matter who (or what) wrote it.

AI Code Security Review uses 3 expert agents: Developer, Architect, and AppSec to review pull requests with the context and care of a real team. It surfaces material changes to your security architecture, like modifications to authentication methods, database schema, or cryptography, and flags pull requests that warrant human review.

AI Security Code Review
Benchmarking Endor Labs vs. Snyk

Fewer False Positives

Better signal-to-noise ratio for AppSec teams at Moodys.

As AI-generated code development continues to rise, your attack surface changes quickly, and traditional SCA tools struggle to keep up. Tools like Snyk often flag thousands of theoretical vulnerabilities with little context, pushing AppSec teams into constant triage mode. Endor Labs eliminates that noise. Our reachability-based analysis identifies whether a vulnerable package is actually invoked by your application. No invocation? No alert.

AppSec for The Software Development Revolution