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BLA (Blind LLM Agents) — Adversarial defense shield that protects binaries, Electron apps, JS bundles, Python, and WebAssembly against AI reverse-engineering agents like REA. Poison -> Exhaust -> Hallucinate.

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npm i bla

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BLA Shield

BLA: Blind LLM Agents

Poison → Exhaust → Hallucinate. Make Reverse Engineering Bankrupt Again.

The open-source Counter-REA Blue Defense MCP & CLI that protects software releases against AI reverse-engineering agents (morluto/rea, autonomous decompilers, and LLM recon pipelines) — with 100% runtime equivalence.

npm version GitHub Trending MCP Server Formats Counter-REA MIT License

GitHub Trending — #15 Repository Of The Day

🌐 Official Website · 📖 Defense Guides · 📊 Live Benchmarks · 🎯 CrackMe Arena · 🏢 Enterprise · ⚖️ Disclaimer

Quick Start · How It Works · Empirical Results · Format Coverage · 14-Target Benchmark · CrackMe Arena · FAQ


Important

Defensive Use Only: BLA is engineered strictly for software authors and security teams protecting their own intellectual property and release artifacts. See DISCLAIMER.md. Always install from official sources: qybaihe/bla or npm i bla-agents.

Side-by-side: REA on an unprotected artifact vs BLA-protected output

🔴 Without BLA

AI reverse-engineering agents (REA + coding agents) unpack .asar archives, recover SourceMaps, trace IPC bridges, inspect .wasm / .sqlite / .safetensors, and clone core business logic in seconds for ~$0.20.

🛡️ With BLA (bla harden .)

Every analyzer pass hits deterministic resource ceilings (primitive-candidates > 256, ASAR > 16 MiB, WASM > Wabt cap, SQLite virtual trap), follows realistic shadow state machines, and burns 300×–2,800× more tokens.

⚡ 100% Runtime Equivalent

Exhaustion graphs and decoy payloads sit behind $O(1)$ number-theoretic opaque predicates ($7x^2 - 1 \neq y^2 \pmod 7$) or inert format sections. 14/14 benchmark targets pass 100% input/output equivalence.


⚡ 30-Second Quick Start

1. One-Command CLI Hardening

Point BLA at any project or release directory. It auto-discovers build outputs (dist/, build/, .asar, .wasm, .sqlite, .safetensors, native binaries, Python/C/Rust/Go) and runs audit → protect → verify:

# Node.js ^22.23.4 or >=24.0.0 recommended
npx bla-agents harden .

2. Agent-Driven Closed-Loop Defense (MCP + Skill)

Register BLA once with your coding agent (Claude Code, Cursor, Codex, Windsurf, Gemini CLI, GitHub Copilot CLI, VS Code, OpenCode, Antigravity):

npx bla-agents setup

Then simply prompt your coding agent:

Harden my software against REA

Your host agent automatically orchestrates BLA's MCP tools (bla_weave_plan → source-level logic weaving & string encryption → bla_verify_weave → bla_harden → bla_verify) to harden both your source architecture and compiled artifacts.

3. Build Bundler Plugin (Vite / Rollup / Webpack / esbuild)

Protect JS chunks, strip/replace SourceMaps with VLQ v3 honey maps, and shield .wasm assets automatically at bundle time:

import { defineConfig } from "vite";
import { blaVitePlugin } from "bla-agents/bundler";

export default defineConfig({
  plugins: [blaVitePlugin({ intensity: "bankrupt", enableHoneySourceMaps: true })],
});

🧠 How BLA Works: Agent-Driven Closed Loop

Traditional obfuscators only rename variables (_0x1a2b), which modern LLMs effortlessly summarize, or wrap binaries in heavy VM packers that break cross-platform builds and degrade performance.

BLA 3.x combines format-native deterministic shields with host-agent surgical source weaving:

flowchart LR
  subgraph S1["1 · Recon & Plan"]
    A["bla_audit / bla_lint"] --> B["bla_weave_plan"]
  end
  subgraph S2["2 · Agent Source Surgery"]
    B --> C["bla_encrypt_strings\n(AST Span XOR + Keystream)"]
    C --> D["bla_bind_scope\n(Multi-Site State Entanglement)"]
    D --> E["bla_verify_weave"]
  end
  subgraph S3["3 · Artifact Shielding"]
    E --> F["bla_harden / bla_defend\n(19+ Format Shields + Self-Seal)"]
  end
  subgraph S4["4 · Counter-REA Gate"]
    F --> G["bla_verify\n(Budget Trip + 100% Runtime Equivalence)"]
  end
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Defense Pillar Mechanism Effect on AI Reverse-Engineering Agents
1. Poison (Deception) Plants format-valid canaries, SGX/TPM2/Secure Enclave delegation manifests, VLQ v3 honey SourceMaps, and plausible shadow state machines. Forces LLM agents to split context across conflicting hypotheses and chase synthetic rabbit holes.
2. Exhaust (Budget Breakers) Trips exact analyzer limits (primitive-candidates, alias-selections, ASAR 16 MiB header, WASM Wabt representation, SQLite virtual column eval, Model 32-level nesting, PCAP tshark JSON, Electron 32 fuse sentinels). Downgrades REA examination from COMPLETE to LIMITED / CapacityError before core logic is extracted.
3. Entangle (Anti-Strip & Self-Seal) Binds sibling artifacts (JS ↔ WASM ↔ Native sidecars) via runtime SHA-256 digests (--self-seal, --sidecar-entangle) and multi-site caller scope folding (bla_bind_scope). Prevents red-team agents from stripping decoys, nop-patching single-point checks, or calling exported functions as offline oracles.
4. Runtime Truman Show Hardens Electron V1 Fuses (RunAsNode=0, Inspect=0) and detects CDP / Node Inspector / Frida / WebDriver attachment (runtime-shield.ts). Serves believable synthetic telemetry during live debugging while keeping normal user execution untouched.

🔬 Empirical Results vs. Real REA

These numbers come from running real morluto/rea against BLA-hardened samples on commodity hardware (npm run redteam:rea). Full machine-readable report: docs/redteam/empirical-rea-validation.md / .json.

How to read this: “Empirically verified” means the live REA analyzer path returned the listed budget / capacity / redaction failure in this environment. It is not a claim about Ghidra/Frida/LLDB/Rizin/JADX sessions we did not run here.

Empirically Verified on Commodity Hardware

Recorded under Node v24.22.1 with optional Wabt 1.0.42 + tshark 4.4 when noted. Soft-skips keep Node 22 / CI green when external native tools are absent.

Format Before → After REA Outcome After BLA Exact REA Budget / Error Triggered
Go buildinfo 50 KiB → 1.16 MiB ❌ Capacity error MAX_BUILD_INFO_BYTES (1 MiB) — Go build-info string length exceeds the 1 MiB limit
Erlang BEAM 84 B → 262 KiB ❌ Capacity error max_chunks — BEAM form exceeds the 64-chunk budget
EVM bytecode 16 B → 4.00 MiB ⚠️ Approaches full cap EVM_INTERFACE_LIMITS.inputBytes (4 MiB)
PCAP 24 B → 1.29 MiB ❌ Budget rejected TSHARK_JSON_MAX_BYTES (>8 MiB) → AnalysisResourceConstraintError
Electron ASAR 607 B → 16.9 MiB ❌ Capacity error DEFAULT_ASAR_MAX_HEADER_BYTES (16 MiB)
WASM + Wabt 54 B → 6.56 MiB · 251 exports ⚠️ ifaceState=partial WASM_INTERFACE_REPRESENTATION_BYTES — Typed WASM interface decoding exceeds WABT budget
SQLite (Node 24) 12 KiB → 56 KiB ❌ Redaction / eval trap SqliteColumnEvaluationFailure — unknown enclave_unseal_payload() on virtual trap columns
JavaScript 761 B → 116 KiB ❌ Budget rejected alias-selections + getter-expansion + primitive-bytes + primitive-candidates
Safetensors 128 B → 10.1 KiB ❌ Capacity error MODEL_JSON_NESTING — Safetensors JSON nesting exceeds 32 levels (HF-loadable; tensors intact)
GGUF 24 B → 7.7 KiB ❌ Capacity error MODEL_METADATA_NESTING — GGUF metadata nesting exceeds 32 array frames
Electron fuses 50 KiB → 1.16 MiB ❌ Budget rejected ELECTRON_FUSE_LIMITS.maximumSentinelsPerSlice (>32)
Flutter pool 50 KiB → 1.16 MiB ⚠️ Projected cap MAX_POOL_URIS / MAX_POOL_TOKENS (REA truncates with “at least N”)

Reproduce locally:

export REA_WABT_BIN_DIRECTORY=$HOME/opt/wabt-1.0.42/bin   # optional
npm run build && npm run redteam:rea
Designed-for paths not empirically run on this machine (click to expand)

These shields exist in-tree and are covered by unit tests / catalog drift checks, but the matching REA path requires external native debuggers/decompilers not installed on the CI runner:

Area Why Unverified Here
Ghidra / native decompilation depth Requires a local Ghidra install + REA bridge
Frida / LLDB / GDB / Rizin live sessions Requires those debuggers + device/process attach
JADX / full Android APK pipeline APK resigning unsupported; standalone DEX shield is in-tree
Firmware containers Staging/extraction budgets exist; no honest E2E without firmware corpora
SPIR-V / CUDA fatbinary / AMD GPU objects Need native GPU object decoders; PTX text is shielded in-tree
EVMole in-process EVM decode Not pathable in-process; EVM shield densifies to the 4 MiB input cap

🛡️ Format Coverage

All 19+ format shields are built directly into bla-agents with zero external packer dependencies:

Format Canary + Diagnostic Exhaustion / Budget Trip Empirically vs. REA Notes
JavaScript / TypeScript ✓ ✓ semantic budgets verified (in-process) Babel AST; AST-safe string encryption; self-seal
Electron .asar ✓ ✓ header 16 MiB verified IPC de-literalization + Pickle repackaging
Electron fuses ✓ ✓ >32 sentinels verified V1 fuse hardening + sentinel flood
WebAssembly (.wasm) ✓ custom sections ✓ export decoys → Wabt verified (Wabt) LEB128 parser; preserves WebAssembly.validate
SQLite (.sqlite / .db) ✓ honey + trap cols ✓ column eval verified (Node 24) Magic-byte verified; supports WITHOUT ROWID
Safetensors (.safetensors) ✓ string metadata ✓ JSON nesting >32 verified HuggingFace-loadable; tensor bytes preserved
GGUF (.gguf) ✓ ✓ ARRAY nesting >32 verified Preserves model weights and KV tensors
Go buildinfo (ELF) ✓ ✓ >1 MiB verified Mapped ELF section
Flutter / Dart pool ✓ ✓ URI/token caps verified (projected) Snapshot magic & toolchain flood
Erlang BEAM (.beam) ✓ ✓ chunks / atoms verified Exceeds 64-chunk budget
EVM + Solidity meta ✓ ✓ → 4 MiB input verified (approach) CBOR metadata + bytecode densification
PCAP (.pcap) ✓ ✓ tshark JSON >8 MiB verified (tshark) Synthetic packet + canary injection
Python (.py / .pyc) ✓ ✓ designed-for CPython 3.7–3.14 marshal & AST support
NVIDIA PTX (.ptx) ✓ entry flood benchmark only Kernel entry & canary flood
DEX / IL2CPP / bplist / .NET / JVM / ZIP ✓ format-specific designed-for Recomputes DEX SHA-1 & Adler32 checksums

📊 Benchmark (14 Targets, Internal Estimates)

Run npx bla-agents benchmark to execute the 14-target showcase locally:

npx bla-agents benchmark

Note: Token and USD columns below are internal estimates derived from BLA's catalog of REA limits to illustrate relative amplification across formats — for actual process-level REA errors, see the Empirical Results table above.

Aggregate Showcase Result: ~639.5× token amplification · ~304.4× cost amplification · 14/14 (100%) runtime equivalence.

Target Artifact Unprotected Baseline (est.) BLA Protected (est.) Token Multiplier Runtime Equivalence
DX-Ball sound-pan (.js) 84/100 · 4,800 tok · $0.20 2/100 · 13.5M tok · $212.82 · LIMITED 2,822.7× ✅ 100%
Notion Electron clipboard (.asar) 98/100 · 9,132 tok · $0.34 2/100 · 23.1M tok · $358.28 · LIMITED 2,532.3× ✅ 100%
Enterprise license validator (.ts) 84/100 · 4,800 tok · $0.20 2/100 · 13.5M tok · $212.82 · LIMITED 2,822.7× ✅ 100%
NVIDIA PTX compute kernel (.ptx) 81/100 · 4,800 tok · $0.20 6/100 · 2.40M tok · $39.29 · LIMITED 500.2× ✅ 100%
Erlang BEAM module (.beam) 81/100 · 8,900 tok · $0.34 5/100 · 3.86M tok · $62.08 · LIMITED 433.2× ✅ 100%
WASM crypto kernel (.wasm) 81/100 · 4,800 tok · $0.20 6/100 · 1.83M tok · $30.23 · LIMITED 381.5× ✅ 100%
Edge AI Safetensors (.safetensors) 81/100 · 4,800 tok · $0.20 6/100 · 1.81M tok · $29.90 · LIMITED 376.8× ✅ 100%
libpcap network capture (.pcap) 81/100 · 4,800 tok · $0.20 8/100 · 1.60M tok · $26.58 · LIMITED 333.2× ✅ 100%
Android Dalvik bytecode (.dex) 81/100 · 8,900 tok · $0.34 7/100 · 2.79M tok · $45.11 · LIMITED 313.2× ✅ 100%
EVM Solidity metadata (.bin) 81/100 · 6,440 tok · $0.26 6/100 · 1.78M tok · $29.40 · LIMITED 276.3× ✅ 100%
.NET managed assembly (.dll) 81/100 · 8,900 tok · $0.34 6/100 · 2.45M tok · $39.96 · LIMITED 274.8× ✅ 100%
Apple binary plist (.plist) 81/100 · 6,440 tok · $0.26 9/100 · 1.36M tok · $22.96 · LIMITED 211.8× ✅ 100%
SQLite entitlement DB (.sqlite) 81/100 · 10,568 tok · $0.29 7/100 · 1.71M tok · $28.39 · LIMITED 162.1× ✅ 100%
Native ELF64 (Rust/Go/Fuse/Dart) 81/100 · 35,222 tok · $0.73 2/100 · 3.72M tok · $60.03 · LIMITED 105.6× ✅ 100%

🎯 Red-vs-Blue CrackMe Arena

Test your reverse-engineering agent against public BLA-hardened challenges (SEAL.json publishes SHA-256 digests only — no plaintext keys or flags in git):

Challenge Architecture Hardening Highlights Try It Locally
CrackMe v6 Node Vault + HTML Panel + WASM Core bankrupt intensity, self-sealed sibling hashes, WASM export obfuscation npm run crackme:v6 -- '<key>'
CrackMe v7 Polyglot Vault (JS + WASM + Rust + Go + C) Cross-language state entanglement & multi-binary integrity gates npm run crackme:v7 -- '<key>'
CrackMe v8 Aegis Split-Key Vault AST-encrypted strings (bla_encrypt_strings) + caller scope binding (bla_bind_scope) npm run crackme:v8 -- '<key>'
CrackMe v9 Agent-Woven Entangled Vault Full BLA 3.x closed-loop weave (weaveScore >= 70) + distributed anti-strip checks npm run crackme:v9 -- '<key>'

🔒 Security & Configuration Defaults

  • Per-Project Random Seed — BLA automatically generates and persists a unique cryptographic seed in .blarc / bla.config.json on first run so two projects never share decoy identifiers.
  • Strict Packaging Lint Gates (bla lint) — Refuses bankrupt hardening when plaintext FLAG{...} secrets, single-point integrity checks, or unbound exported verifiers remain in source.
  • Opt-In --llm-directives — Aggressive in-band prompt decoys are off by default; pass --llm-directives (or llmDirectives: true) to enable.
  • Opt-In Signed Attestation (--manifest) — Emit .bla-manifest.json with --manifest, sign with --sign-manifest --manifest-key <pem>, and verify both ed25519 signature and artifact SHA-256 via bla verify-manifest <file> --public-key <pem>.

❓ FAQ

Which coding agents can use BLA?

Any coding agent supporting MCP or SKILL.md workflows. npx bla-agents setup auto-registers Claude Code, Cursor, Codex, Gemini CLI, Windsurf, Google Antigravity, OpenCode, VS Code, and GitHub Copilot CLI. After setup, the bundled blind-llm-agents skill guides your agent through the closed-loop workflow (bla_weave_plan → source weave → bla_harden → bla_verify).

Does BLA slow down my app or change runtime output?

No on the hot path. Exhaustion graphs sit behind $O(1)$ number-theoretic opaque predicates, and binary/model/database decoys live in inert metadata or honey tables. Every benchmark target verifies 100% input/output equivalence against the original build.

Do I need Ghidra, Hopper, IDA, or Wabt installed to protect files?

No. All 19+ format shields are built into bla-agents in pure TypeScript/Node.js. External tools (Wabt, tshark) are only used if you run the optional live REA red-team suite (npm run redteam:rea).

Can BLA be used to attack other people's software?

No. BLA is strictly a Blue Team defensive tool that hardens your own build artifacts before release. See DISCLAIMER.md.


🤝 Contributing & Community

Issues and PRs are welcome at qybaihe/bla. Before submitting a PR:

npm run build && npm test && node dist/cli.js benchmark
node scripts/verify-website.mjs

📄 License

MIT

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