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Find hardcoded credentials before they become a breach headline.

Secrets Scan

Scans ML code repositories, Docker images, and pipeline configurations for hardcoded credentials, exposed API keys, and insecure data access patterns before they reach production. Prevents the security incidents caused by data science teams embedding cloud credentials in notebooks and training scripts — a near-universal problem in enterprise ML teams.

Why It Matters

SecretsScan targets the most preventable and most common security failure in enterprise ML — credentials hardcoded into notebooks, training scripts, and Docker images.
Automated scanning catches exposed keys before code reaches production, closing the gap data science’s fast-and-loose workflow leaves open.
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A near-universal problem, not an edge case

Data scientists routinely embed cloud credentials in notebooks to "make it work" — every enterprise ML team has this exposure, whether they've discovered it yet or not.

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Breach prevention at commit time

A leaked AWS key in a repository is an open door to data exfiltration and crypto-mining bills — scanning at the pipeline gate stops the incident before the secret ever ships.

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Fits existing DevSecOps, no new silos

Integration with established security gates means ML code gets the same scrutiny as application code — one security posture, not a parallel ML exception.

The Cloudly Advantage

SecretsScan is Cloudly’s lowest-friction security product — cheap to deploy, instantly valuable, and almost guaranteed to find real problems in the first scan.
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The first-scan sales close

Running SecretsScan on a prospect's repos during a POC almost always surfaces live credentials — few sales motions beat showing a client their own exposed keys.

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DevSecOps service extension

Checkov, Inspector, and pipeline-gate integration extends our CI/CD Implementation practice into security — a natural upsell on every pipeline engagement we already deliver.

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Security portfolio entry point

Small, fast, undeniable value opens the CISO conversation that ModelShield and PrivacyEngine then expand — the land motion for the whole security stack.

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Notebook governance synergy

Pairs directly with NoteBook Sync — governed notebooks plus scanned credentials covers the two biggest risks data science workflows create.

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AWS Inspector pull-through

Inspector and GitHub Advanced Security integrations open AWS security architecture and monitoring conversations in every deployment.

The Final Takeaway

Continuous scanning revenue — Repos and images change daily — ongoing scanning converts to a lightweight managed security service with high margin and near-zero delivery cost.

Powered By

TruffleHog

Core to the SecretsScan technology stack.

Gitleaks

Core to the SecretsScan technology stack.

Checkov

Core to the SecretsScan technology stack.

AWS Inspector

Core to the SecretsScan technology stack.

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