# BLA: Protect Software from AI Reverse-Engineering Agents This repository profile is provided by osrepos.com, an open source repository discovery platform. Source: osrepos.com Repository profile: https://osrepos.com/repo/qybaihe-bla Generated for open source discovery and AI-assisted research. BLA is a TypeScript CLI and MCP tool that hardens binaries, Electron apps, JavaScript bundles, Python, and WebAssembly against AI reverse-engineering agents. It uses decoys and analysis-budget exhaustion to hinder inspection while aiming to preserve runtime behavior. GitHub: https://github.com/qybaihe/bla OSRepos URL: https://osrepos.com/repo/qybaihe-bla ## Summary BLA is a TypeScript CLI and MCP tool that hardens binaries, Electron apps, JavaScript bundles, Python, and WebAssembly against AI reverse-engineering agents. It uses decoys and analysis-budget exhaustion to hinder inspection while aiming to preserve runtime behavior. ## Topics - typescript - security - cli - mcp-server - llm-security - reverse-engineering-defense ## Repository Information Last analyzed by OSRepos: Tue Nov 03 2026 10:13:26 GMT+0000 (Western European Standard Time) Detail views: 3 GitHub clicks: 1 ## Safety Notice OSRepos shares public repositories for knowledge and discovery only. Review source code, dependencies, licenses, and security implications before running or installing anything. ## Content ## Overview BLA (Blind LLM Agents) is a TypeScript defensive tool for software authors who want to make their shipped artifacts harder for AI reverse-engineering agents (REAs) to analyze. It protects binaries, Electron apps, JavaScript bundles, Python, WebAssembly, and other supported formats by adding decoys and pushing analyzers toward documented resource limits, with the stated goal of preserving normal runtime behavior. The project provides a CLI and MCP integration for coding agents. Its framing is specifically defensive: harden software you own, rather than use it to attack someone else’s artifacts. The README distinguishes results tested against a real REA from internal benchmark estimates and formats that are supported in code but not empirically verified against that analyzer. ## Key Features - One-command hardening flow that discovers likely build artifacts and runs audit, protection, and verification steps. - Format-specific canaries, decoy metadata, and control-flow distractions intended to mislead automated analysis. - Resource-exhaustion techniques that target analyzer limits in formats including ASAR, WASM, SQLite, model files, and Go build information. - CLI and MCP tools, with setup instructions for several coding-agent environments. - Verification and benchmark commands that check runtime behavior; the README reports exact runtime equivalence for its benchmark targets. - Optional empirical red-team tests against a real REA, with the README identifying which results were verified and which require native tooling or remain untested. ## Use Cases - A developer shipping an Electron application can harden its ASAR package and test whether inspection triggers documented analyzer limits. - A team distributing JavaScript, WebAssembly, Python, or supported binary artifacts can add analysis friction before publishing a build. - A coding-agent user can set up the MCP integration and ask the agent to run BLA’s hardening workflow on a project. - A security engineer can reproduce the project’s real-REA tests on supported formats, while keeping unverified formats separate from demonstrated outcomes. ## Our Take BLA is an unusually explicit counter-analysis tool for software publishers, but it is very new and its results vary by artifact format and test environment. **Good fit if:** - You ship software you own in one of BLA’s supported formats and want a defensive layer aimed at AI-assisted reverse engineering. - Your workflow uses Node.js and you want CLI or MCP-based hardening with runtime checks. - You can evaluate the empirical evidence format by format instead of treating local token estimates as proof of protection. **Look elsewhere if:** - You need protection demonstrated against native tools or REA paths that the README says were not tested. - Your deployment cannot use the required Node.js versions or you need a tool that does not depend on a JavaScript runtime. - You need established project history or broadly distributed maintainership: the project is newly created, changes rapidly, and most contributions come from one person. ## Project Health | Signal | Value | |---|---| | Status | **New**: less than six months old and changing fast | | Last commit | 2026-11-03 (today) | | Commits, last 90 days | 100+ | | Releases, last 12 months | 23 (latest bla-agents-2.0.0, 2026-11-03) | | Contributors | 5 (top contributor: 92% of commits) | | Issues closed, last 90 days | 16 (typically closed in 1 day) | | Pull requests merged, last 90 days | 38 (typically merged in 0 days) | | Project age | 9 days | Checked on 2026-11-03 with the GitHub API. ## Project Facts - Language: TypeScript - License: MIT - Stars: 2k - Forks: 275 - Topics: adversarial-ai, claude-code, cursor, electron-security, llm-security, mcp, mcp-server, obfuscation - Website: https://bla.tools - Archived: no ## What You Need Detected in the repository: - Node.js ^22.23.4 || >=24.0.0 (from package.json) - A test suite and automated checks on GitHub Actions ## Getting Started ```bash npx bla-agents setup npx bla-agents harden . ``` The README covers supported formats, agent setup, verification, and empirical test requirements. ## License in Plain Words **MIT** (permissive). - Commercial use: yes - Modify and redistribute: yes - You must keep: the copyright and license notice - Share your changes: no A summary, not legal advice: the LICENSE file is what applies. ## Considerations - The project is marked new and has a short track record, despite frequent recent commits and releases. Its contributor base is small and highly concentrated, so maintenance depends heavily on one person. - Node.js `^22.23.4 || >=24.0.0` is required. Wabt, tshark, and Node 24 enable some empirical probes, but the README says they are not required for protection itself. - Empirical results apply only to the tested REA analyzer paths and environments. Ghidra, debugger sessions, full Android APK processing, firmware containers, and several GPU formats are listed as unverified or skipped. - The benchmark’s token and cost multipliers are internal estimates, not measurements of a real REA process. The README identifies the real-REA red-team command, rather than the drift harness, as the authoritative evidence gate. - The project describes itself as defensive and directs users to harden only their own software. Review its disclaimer and use boundaries before adopting it.