The Broken Economics of Open Source Security—and How to Fix Them

Modern software isn’t written from scratch—it’s assembled. Developers build applications using a patchwork of open-source libraries and frameworks, now accelerated by AI-powered coding assistants. This shift has fueled rapid innovation, but it’s also introduced hidden risks that security teams are struggling to manage.

The Perfect Storm: AI, Open Source, and Security Debt

The way we build software has fundamentally changed:

• AI-assisted development is accelerating open-source adoption—without scrutiny. AI tools often suggest unfamiliar libraries that developers adopt quickly, without understanding their security or licensing implications.
• Outputs are non-deterministic. Two teams building the same feature may end up with entirely different dependency stacks, creating fragmented ecosystems inside a single company.
• Dependencies pile up without maintenance. Developers add open-source packages to move faster, but rarely prioritize upgrades or patching—leaving software exposed to known vulnerabilities.

At the same time, the burden on security has become unsustainable. In 2024, the average AppSec engineer was responsible for securing more than 2 million lines of code. By 2026, that number is projected to triple—an impossible scale for today’s manual, alert-driven processes.

Why AppSec Economics Don’t Work

The problem isn’t just technical—it’s economic. Today’s model is misaligned across stakeholders:

• Security teams are accountable for risk but lack control over the code.
• Developers bear the cost of fixing issues but receive little recognition or incentive.
• Business units absorb the fallout—lost productivity, reputational damage, and regulatory penalties.

With no one responsible for proactively managing open-source dependencies, security debt accumulates quietly until it becomes a crisis. By then, the cost and disruption of remediation skyrockets.

This is the core challenge organizations face:

• Open-source usage is exploding.
• Security accountability is rising.
• Resources, control, and influence aren’t keeping pace.

Rethinking the Problem: From Prioritization to Fixing

For years, the security industry has tried to solve open-source risk with prioritization. Tools scan codebases, generate long lists of vulnerabilities, and then attempt to rank them by severity. The result? Developers still face massive backlogs, security debt continues to grow, and organizations spend more time debating what to fix than actually fixing anything.

At Heeler, we believe this model is upside down. The real bottleneck isn’t deciding which problems matter—it’s that teams don’t have the capacity to fix them. That’s why we start with fixing, not prioritizing.

By automating safe, validated upgrades, Heeler can immediately resolve 70–80% of open-source vulnerabilities without human intervention. This dramatically reduces the backlog and clears away the noise, so security teams can focus on the smaller subset of issues that truly require engineering expertise.

Once the easy fixes are gone, prioritization becomes sharper and more actionable. Instead of weighing thousands of findings, teams can make targeted decisions about the handful of risks that genuinely matter to the business.

This shift—from prioritization-first to fixing-first—changes the economics of AppSec. It means faster remediation, less developer toil, and a scalable approach to open-source risk management in an AI-accelerated world.

Patchwork Isn’t Progress

Many tools try to address this with backported patches or compensating controls. These are stopgaps, not solutions. They allow unmaintained libraries to linger, entrenching tech debt that will later demand a high-interest payoff. Others generate "automated PRs"—but these are often blind version bumps that ignore breaking changes and lack understanding of actual usage. Developers don’t merge them because doing so requires hours of work to validate, with no guarantee of success.

And so they sit. More backlog.

How Heeler Works: The Four Pillars

Heeler is built around four pillars that transform open-source management into a sustainable, proactive practice:

1. Fixability

Heeler calculates the optimal upgrade path based on least amount of developer effort paired with greatest security impact and analyzes impact across the entire dependency graph.

2. Remediation

Heeler generates fully validated pull requests. Each PR includes compilation checks, unit test validation, and context on fixability. Ownership is assigned automatically, SLAs are enforced, and resolution is tracked end-to-end.

3. Guardrails

Policies are enforced at the pull request level, combining vulnerability signals with hygiene checks (e.g., OpenSSF Scorecard, compromised packages, unapproved licenses). This stops risky dependencies from ever being merged—without slowing down developers.

4. Exploitability

Heeler prioritizes based on true risk, not theoretical risk. Using runtime threat modeling, we analyze how code runs in production—factoring in internet exposure, service-to-service relationships, runtime mitigations, and business criticality. A vulnerability with a “medium” CVSS may become high-priority if actively exploited in your environment.

Why Heeler Is Different

Ditch SCA and fix instead. Traditional SCA tools start with noise and try to layer on prioritization. Heeler flips the model: we start with fixing. By automating safe upgrades, we eliminate 70–80% of the backlog up front, then help teams focus on the small subset of complex issues that require engineering judgment.

The Future of Open Source Security

As AI accelerates software development, the gap between code creation and security capacity will only widen.

Heeler is rebalancing the equation. By automating fixes, embedding guardrails, and prioritizing based on real-world exploitability, we’re giving developers time back and enabling security teams to scale with confidence.

In short: we’re changing the economics of AppSec—turning open-source management from an endless liability into a resilient, automated system for modern software development.

‍