A new open-source tool called Hamza has emerged on Hacker News, offering developers a way to filter out secrets and personally identifiable information (PII) before those contents reach AI coding assistants like Claude Code or OpenAI's Codex.

Why This Matters for Developer Workflows

As more engineers delegate code review, debugging, and even feature development to large language models hosted by Anthropic and OpenAI, the question of data security becomes increasingly fraught. Sending a codebase containing API keys, database credentials, or customer PII to an external AI service means trusting that provider with information you'd rather keep private—regardless of their privacy policies. Hamza appears designed as a preprocessing bridge: scan your input before it leaves your machine, redact sensitive patterns, and only then hand off to the LLM.

What We Know About the Implementation

The project, hosted at github.com/softcane/hamza by user softcane, was submitted to Hacker News on July 28, 2026 as a 'Show HN' post. The tool reportedly intercepts content headed for Claude Code and Codex, applies pattern-matching or rule-based redaction, and passes sanitized text forward instead. Specific detection logic—whether it relies on regex patterns for common secret formats, named-entity recognition for PII, or something else entirely—would require a deeper look at the repository itself.

Early Community Reception

The Show HN post received modest engagement with a score of 6 points as of publication time, suggesting early-stage interest from the developer community rather than viral adoption. Zero comments were visible on the Hacker News thread at submission time, indicating the project is still in its infancy or hasn't yet attracted detailed technical discussion.

Key Takeaways

  • Hamza targets developers using Claude Code and Codex who want to prevent accidental secret/PII leakage
  • The tool acts as a preprocessing filter that sanitizes input before it reaches external AI services
  • Open-source availability on GitHub means community auditability, though security-critical tools demand thorough review before production use

The Bottom Line

This is the kind of tooling the ecosystem needed yesterday. As AI-assisted development moves from novelty to standard practice, the attack surface around data exfiltration via prompt injection and accidental context leakage grows proportionally. Hamza won't solve every threat model, but it's a solid step toward making 'just ship it to the LLM' less of a liability gamble.