Think about your own work or business in this area: Maker launch on DevHunt: Find and fix vulnerabilities in code, dependencies and containers - Every AI-building team faces one question: can you trust what you're shipping? the product... What is the single biggest problem you have there right now? Be specific about what it costs you (time, money, customers) and what you have already tried.

Jon Koelpinneutral

The biggest problem we have is ensuring the security and integrity of our code, dependencies, and container images. With five engineers and a fast-moving product roadmap, doing deep security audits is a challenge. It costs us time that could be spent on features, and frankly, the thought of shipping a vulnerability, especially with our LLM integration, is a constant worry. We're using Dependabot for dependencies, but it doesn't cover custom code or container configurations. We haven't found a good, integrated solution yet.

Simulated interest: 70/100

Christie Gerlachnegative

The biggest problem we face is the sheer manual effort involved in ensuring the security of our AI agents. We're patching together open-source tools and a frankly overloaded spreadsheet to track code, dependency, and container vulnerabilities. It's a time sink – I spend hours each week collating findings and chasing down issues. The risk of human error is significant, and honestly, it slows us down considerably when clients want rapid iteration. We've had to pause projects before to fix these gaps, which frustrates stakeholders and impacts our delivery timelines. I've tried creating more robust checklists and standardizing our scanning approach, but it's still a house of cards.

Simulated interest: 75/100

Pepe Wagnernegative

The biggest problem we have right now is the manual review of container scan results. It's a real time sink, easily taking an hour or more each day to go through the findings, document them, and then manually create tickets for the development teams. That's time I could be spending on automating parts of our pipeline or improving our Kubernetes configurations. We've tried integrating some basic checks into the CI, but it doesn't give us the granularity we need and still requires significant manual oversight. It feels like a constant battle to keep up.

Simulated interest: 60/100

Darshan Iyernegative

Can we trust what we're shipping? That's the million-dollar question, literally! My biggest problem is balancing the speed we need to iterate with ensuring we're not introducing security holes. We're a small team, and I personally review every PR, but with new AI libraries and container updates constantly, it's a huge time sink. We use Dependabot and free scanners, but I'm always worried about what we might be missing. It costs us peace of mind and potentially future customers if we get breached. I haven't found a solution that's both effective and affordable for our budget.

Simulated interest: 70/100

Corentine Pierrenegative

The biggest problem we face is the disjointed nature of our security workflows. We have a strong paid platform for code and dependency scanning, but our container image checks and agent security reviews are managed separately, often requiring significant manual effort and documentation. This creates an inefficiency and a potential blind spot – it’s hard to maintain a unified, traceable security posture. It costs us considerable engineering time that could be better spent on proactive threat modeling or feature development. We’ve tried to mitigate this by creating internal runbooks, but it’s a constant battle to keep them updated and ensure adherence across the team.

Simulated interest: 85/100

Norman Johnsneutral

The biggest problem for my team is the constant worry about what we might be missing. We're shipping fast, and while I do a lot of manual checks and use GitHub alerts, it feels like I'm always one step behind. We've tried adding more free scanners, but it just adds noise and more manual triage. It costs us time because I spend hours sifting through potential issues, and honestly, it makes me nervous about what could slip through. I'm concerned about unforeseen vulnerabilities in our AI agent or containerized services impacting our B2B customers, which could erode trust and potentially lead to customer loss, though I can't put a direct dollar figure on that right now.

Simulated interest: 70/100

Darrel Cummeratanegative

The biggest headache for us is ensuring consistent security across all the different client projects. We're a small team of nine, so our budget for sophisticated security tooling is pretty limited. We rely on free tools and checklists, but it's a manual grind, and honestly, I worry about what we might be missing, especially with container images and dependencies. This ad-hoc approach costs us time we could spend on development and, more critically, it puts client trust at risk if something slips through. We've tried to build our own internal checklists, but they quickly become outdated.

Simulated interest: 75/100

Mink Visserneutral

The biggest challenge for us right now is the manual triage of security alerts from our CI pipeline, especially for container scanning. We're shipping AI features rapidly, and ensuring we can trust what we deploy is paramount. This current process takes up valuable time for my small team, time we'd rather spend on optimizing infrastructure or developing new automation. I'm not sure how this product handles the integration with existing CI/CD workflows or the volume of alerts we generate. What is the cost structure, and what is the integration effort like?

Simulated interest: 30/100

Mohana Khannanegative

The biggest problem we face is the sheer volume of findings from our disparate scanning tools, coupled with the time it takes to manually reconcile them in a spreadsheet. We're talking hours each week just for tracking, which takes away from actual engineering. This delay can impact our release timelines, and frankly, the risk of missing something critical due to manual error is a constant worry. We've tried standardizing our free scanners, but the integration and reporting are still very manual.

Simulated interest: 85/100

Conchita Gastélum Estéveznegative

The biggest problem is the sheer manual overhead. I'm using Dependabot and Trivy, but correlating their findings and prioritizing them against our roadmap takes hours each week. We already had a critical vulnerability slip through last quarter because it was buried in a sea of low-priority alerts, costing us a day of developer time to fix and causing some customer anxiety. I've tried to create better dashboards in our spreadsheet, but it's still a game of whack-a-mole. "Can we trust what we're shipping?" is the question that keeps me up at night, especially with the AI summarizer potentially exposing sensitive data.

Simulated interest: 85/100