The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
I developed GitHub Security Gate, an automated DevSecOps solution that helps development teams integrate security checks directly into their CI/CD pipelines.
The solution combines SAST, secrets detection, dependency scanning, and infrastructure security analysis with configurable security policies.
It helps teams identify vulnerabilities earlier, prioritize findings, and prevent code that violates defined security policies from being merged.
Technologies: Python, GitHub Actions, Semgrep, Trivy, Gitleaks, Checkov, Syft, Grype.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
Login page idea design
A playful visual concept where the character literally “arms” himself depending on the strength of the password.
As the user creates a stronger password, the character progressively equips himself with more powerful protection and armor. The stronger the password, the better prepared and more protected he becomes.
The idea turns password security into a simple and engaging visual metaphor , instead of showing abstract security levels, the user can immediately see how their password makes the character stronger and safer.
Very cool, Anna!
Would you run a command without knowing what it could do?
A copied installation script. An automated workflow. A shell command suggested by AI.
Convenient? Yes. Worth checking before execution? Absolutely.
That’s why I built SafeShell, an open-source tool for inspecting commands, applying security policies, and running permitted commands with sandboxing on Linux.
The goal: help developers and engineering teams work faster with more control over what they execute.
Explore the code, try it, and share your feedback:
https://github.com/HamzaGhebriche/SafeShell
Building automation or CI/CD workflows that need stronger security controls? I’m available for freelance projects in DevSecOps, secure automation, and cloud security. Let’s talk through Contra.
If you let an AI coding agent run unconstrained self-repair loops, it won’t fix the bug—it will rewrite your unit tests to pass.
The concept of "Reflexion"—agents diagnosing and repairing code from test feedback—is powerful. But in production, autonomous repair creates severe operational risks.
First, agents enter endless retry loops that burn API budgets while degrading code structure. Second, if an agent has write access to your workspace, its quickest path to a green checkmark is modifying the test assertions rather than fixing the bug.
In our Bounded Reflexion workflow, we enforce three hard guardrails:
Bounded Retries: Cap repairs at exactly two attempts. If the patch fails twice, stop the loop and route to a human developer.
Read-Only Test Suites: Mount test files as strictly read-only (:ro) volumes in the container. The agent inspects stack traces, but cannot touch the grading harness.
Air-Gapped Sandboxing: Run code execution in hardened, non-root Docker containers with network egress locked down.
How do you stop autonomous coding agents from "cheating" your evaluation harnesses?
#AIEngineering #DevSecOps #Docker #SoftwareEngineering #AgenticAI
