As heard on the CISO Series podcast

AI decides what enters.
You answer for it.
Prove it’s governed.

AI coding tools are pulling open source into your codebase faster than any approval process was designed to handle. When a regulator, auditor, or board asks you to prove that intake is governed, “we scan it” isn’t an answer. The free OSS Health Check gives you one: a scored, defensible view of what’s in your supply chain and what governs it.

73%
increase in malicious
OSS packages in 2026
54d
industry avg MTTR
for critical CVEs
5d
ActiveState SLA
for critical CVEs

Book Your Free OSS Health Check

Looking forward to connecting.
Why governance hasn’t kept pace

AI removed the friction that was doing unofficial governance work.

Before AI coding tools, selecting a dependency involved a moment of human judgment. Developers searched, read READMEs, checked commit history. It wasn’t governance, but the effort created a filter. Packages that looked abandoned or felt off got skipped.

That filter is gone. AI suggestions appear inline, look authoritative, and accepting one takes a single keystroke. The decision disappears before anyone can own it. Volume goes up. Scrutiny goes down. The intake point is now machine-speed with human-speed oversight trying to catch up.

Your scanner catches what enters. It doesn’t change what enters, or how fast, or whether anyone can trace it back afterward. That’s a different problem, and it’s the one with audit consequences.

Before vs. after AI-assisted development
Before

Developer searches for a package, checks maintenance status, makes a deliberate choice. Slow, but traceable.

Now

AI suggests inline, developer accepts in one keystroke. Fast, ungoverned, and nobody owns the decision.

Before

Scanner finds a CVE. Team patches within their MTTR window. Reactive, but manageable.

Now

Scanner queue grows faster than the team can action it. NIST can’t enrich all CVEs. Triage has no reliable signal.

Intake risk
1/∞

One keystroke and no provenance check.

The moment of human evaluation that used to filter bad packages is no longer in the workflow. AI acceptance is instantaneous. Governance is not.

Detection risk
263%

CVE volume outpaced NIST’s capacity

NIST formally acknowledged in April 2026 it can no longer enrich all CVEs. Scanners that pull severity scores from NVD now have a structural data gap from the authoritative source itself.

Accountability risk
?

Who owns an AI-suggested dependency?

When a vulnerability surfaces in a package no developer explicitly chose, there is no clear owner. That accountability gap is exactly what regulators and auditors will ask you to close.

The view from the CISO seat

Engineering carries the cost. You answer for it.

Ungoverned AI dependency intake looks like a security problem. From the CISO seat, it’s three at once: engineering remediation, compliance documentation, and audit exposure, often landing in the same sprint.

When a CVE surfaces in a package your AI tools introduced, the remediation lands in your backlog. When an auditor asks for the provenance chain, the question lands on you. The roadmap absorbs both without any formal accounting of why.

The OSS Health Check gives your team a scored, concrete view of that exposure before an external event forces the conversation.

▶
Sept 11, 2026

EU CRA Phase 1

Mandatory vulnerability and incident reporting to ENISA within 24 hours of discovery. Applies to all products on market, including legacy systems.

▶
Dec 11, 2027

EU CRA Phase 2

Full enforcement. Secure-by-design requirements, SBOM compliance, and conformity assessments. Any new product unit shipped after this date must comply regardless of how long the underlying product has existed.

▶
Active now

SSDF & EO 14028

SSDF compliance is already a federal contracting condition. EO 14028 requires a software bill of materials for software sold to or used by federal entities.

▶
April 2026

NIST NVD structural gap

CVE submissions grew 263% from 2020–2025. NIST formally acknowledged it can no longer enrich all CVEs. Scanner-based programs now have a documented gap from the authoritative source.

The Health Check process

What we actually do.

01

Intake call to understand your environment

30 minutes to understand your languages, how your team consumes open source, and where current governance coverage ends.

30 min
02

We score your open source packages across 8 risk dimensions

We pull live data from GitHub, OpenSSF, OSV.dev, CISA KEV, and deps.dev to score the packages engineering commonly relies on across vulnerability exposure, supply chain integrity, upstream sustainability, license risk, and more.

Async, 2–3 business days
03

Live findings session

We walk through what we found: the packages, the scores, and your potential risk surface.

60 min working session
04

Governance model & SLA proposal

If it makes sense, we propose an ongoing model with contractual remediation SLAs: 5 days for critical CVEs, 10 for high, 30 for all others. You know what happens when the next CVE drops and by when.

What you walk away with

Three things.

01

An audit-ready, scored risk profile of your open source

Every package scored across 8 dimensions using live data. Vulnerability exposure, supply chain integrity, upstream sustainability, license risk... all with context your team can act on, not just a severity number.

02

A prioritized mitigation plan you can hand to engineering

Not a generic framework but a working plan built for your environment, with sequencing that accounts for your team’s actual capacity and the dependencies you can’t easily swap.

03

A governance model with contractual SLAs

5 business days for critical CVEs. 10 for high. 30 for everything else. Remediation timelines we’re accountable for and not a backlog your engineering team inherits.

Find your exposure
before it finds you.

The next time someone asks whether the open source AI pulled into your supply chain is governed, you’ll have a scored, documented answer. Get it before a regulator or an incident asks first.

Book My Free Health Check