Security scanning skill for AI coding agents automatically checks deployments

A developer has published a security scanning skill file for AI coding agents that automatically checks deployments for common security issues. The tool was created after repeatedly finding exposed .env files and open ports in applications after deployment by AI agents.
What the skill does
The skill file enables AI coding agents to run an automated security scan after every deployment. According to the source, it specifically looks for:
- Exposed secrets (like .env files)
- Open database ports
- Missing security headers
- Leaked source code
The scan completes in approximately 30 seconds. The developer mentions this addresses a practical problem: "I kept finding exposed .env files and open ports in apps after my agent deployed them."
Technical implementation
The skill is available on ClawHub at https://clawhub.ai/doureios39/preflyt. The developer identifies as /u/doureios39 on Reddit and is actively seeking feedback on the implementation.
For context, skills in AI coding agent ecosystems like OpenClaw typically consist of configuration files or scripts that extend an agent's capabilities. This particular skill appears to integrate security scanning directly into the deployment workflow, allowing agents to self-audit their work automatically.
Security scanning tools for deployments typically work by checking exposed endpoints, analyzing response headers, and scanning for sensitive files that shouldn't be publicly accessible. Integrating this as a post-deployment step helps catch configuration errors before they become security incidents.
📖 Read the full source: r/openclaw
👀 See Also

Curated list of 260+ AI agents and tools with open-source and self-hosted focus
A comprehensive GitHub repository lists over 260 AI agents and frameworks, emphasizing open-source, self-hosted, and local-first options including Ollama, OpenClaw, and DeerFlow.

Claude Code Logs Every Session to Disk — Here's How to Index and Recall Them
Claude Code writes every session turn to ~/.claude/projects/ as JSONL. One user indexed 1026 sessions (57MB, 76K turns) into SQLite+FTS5 with an MCP server for search and thread recall across sessions.

Hypura: Storage-tier-aware LLM inference scheduler for Apple Silicon
Hypura is a Rust-based inference scheduler that places model tensors across GPU, RAM, and NVMe tiers to run models exceeding physical memory on Apple Silicon Macs. It enables running a 31GB Mixtral 8x7B on a 32GB Mac Mini at 2.2 tok/s and a 40GB Llama 70B at 0.3 tok/s where vanilla llama.cpp crashes.

OpenMind adds visual mind map interface to OpenClaw installations
OpenMind is an open-source tool that transforms OpenClaw installations into interactive, live-editable mind maps with real-time memory visualization, hot-swappable logic, and full-text search across all nodes.