Screenshots 5
Sentrint
Summary
You built the app with Claude, shipped it, and only later discovered your API keys were sitting in plain text inside a public repo — because nobody ran a security scan before you clicked deploy.
Sentrint takes the GitHub URL of an AI-generated app and runs it through a four-category security engine: hardcoded secrets, database access rules, dependency vulnerabilities, and dangerous code paths where user input reaches a command. An AI layer then filters the results, discarding findings the engine flagged but that are not actually exploitable, so you are not chasing noise. What comes back is a score out of 100, every finding written in plain English, and a fix prompt already rewritten for the specific LLM platform that built the app — paste it in, scan again, watch the grade move. The ceiling appears fast: no API access, no CI integration, no self-hosting, and no way to automate scans without a human clicking through the interface each time.
Bottom line: Sentrint fits the developer who vibe-coded an app on a weekend and needs to know whether it is safe to share the link — it breaks down the moment a team wants scans running automatically on every pull request.
Community Performance Report Card
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Pros
Sign in to edit- AI-filtered results strip out findings that are not actually exploitable, so you spend time fixing real vulnerabilities instead of chasing false alarms that a raw static analysis tool would dump on you.
- Fix prompts are rewritten for the specific LLM platform that built the app — Claude, Gemini, or any of the 16 supported platforms — so a non-technical builder can paste the output directly back into their coding agent without translating a security finding into an instruction.
- Plain-English explanations of every finding mean a product manager or solo indie developer can read the report and understand what is broken, without needing a security engineer to interpret CVE IDs or stack traces.
- Score-over-time tracking across multiple scans gives you a visible signal that fixes are landing — not just a one-time snapshot, but a trend line that confirms the grade is actually climbing.
Cons
Sign in to edit- There is no API and no CI/CD integration, so every scan requires a human to initiate it manually through the interface — any team that wants scans running automatically on pull requests or blocking a deployment on a failing grade hits this wall immediately and has to move to a tool like Snyk or Semgrep that exposes pipeline hooks.
- The scan covers four fixed categories: secrets, access rules, dependencies, and code paths. Teams whose apps have security concerns outside those categories — authentication logic, rate limiting, business-logic flaws — get no coverage and no signal, with no way to extend the engine.
- No self-hosted option means every repository you scan is processed on Sentrint's infrastructure — teams under data-residency requirements or working with proprietary codebases they cannot send to a third-party service cannot use the tool at all.
About
- Platforms
- Web
- API Available
- No
- Self-Hosted
- No
- Last Updated
- 2026-09-09T03:38:43.605Z
Best For
Who it's for
- Non-technical builders using AI coding agents
- Indie developers shipping vibe-coded apps
- Teams needing plain-English security reports
What it does well
- Scan AI-generated app repositories for security flaws
- Generate platform-specific fix prompts for detected issues
- Track security score trends across multiple scans
Integrations
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Sign Up to ContributeFrequently Asked Questions
- Is Sentrint free?
- Sentrint has a permanent free tier alongside paid upgrades. You can keep using a baseline version indefinitely without paying.
- Is Sentrint open source?
- No — Sentrint is a closed-source tool. Source code is not publicly available.
- What platforms does Sentrint support?
- Sentrint is available on: Web.
Curated lists that include this category
API keys left in public repos after shipping AI-built apps
You built the app with Claude, shipped it, and only later discovered your API keys were sitting in plain text inside a public repo because nobody ran a security scan before you clicked deploy.
Sentrint takes the GitHub URL of an AI-generated app and runs it through a four-category security engine: hardcoded secrets, database access rules, dependency vulnerabilities, and dangerous code paths where user input reaches a command. An AI layer then filters the results, discarding findings the engine flagged but that are not actually exploitable, so you are not chasing noise. What comes back is a score out of 100, every finding written in plain English, and a fix prompt already rewritten for the specific LLM platform that built the app.
Use cases and features
Scan AI-generated app repositories for security flaws. Generate platform-specific fix prompts for detected issues. Track security score trends across multiple scans. The vendor states the tool supports GitHub plus 16 platforms including Cursor, Windsurf, Claude Code, Lovable, Bolt, and v0.
AI-filtered results strip out findings that are not actually exploitable, so you spend time fixing real vulnerabilities instead of chasing false alarms that a raw static analysis tool would dump on you. Fix prompts are rewritten for the specific LLM platform that built the app so a non-technical builder can paste the output directly back into their coding agent.
Who it is for / who should skip it
Non-technical builders using AI coding agents, indie developers shipping vibe-coded apps, and teams needing plain-English security reports will find the plain language and targeted prompts useful. Teams that want scans running automatically on pull requests or covering authentication logic, rate limiting, or business-logic flaws should skip it, as there is no API or CI/CD integration and coverage stays limited to four fixed categories.