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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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BLA Shield BLA: Blind LLM Agents

Make reverse engineering bankrupt again.

Point BLA at the build you ship. When an AI reverse-engineering agent (REA) opens it, the analyzer hits resource budgets, follows decoys, and burns tokens — while your users still get the same runtime behavior.

npm version MCP tool catalog Node.js Counter-REA MIT license

Website · Guides · Showcases · Disclaimer

Quick start · Empirical results · Format coverage · Benchmark · FAQ

bla harden .
# or tell your agent: "Harden my software against REA"

Important

BLA is a defensive tool for protecting your own software. See DISCLAIMER.md. Get BLA from qybaihe/bla or npm bla-agents.

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

What BLA does

REA reverse-engineers release artifacts in one command. BLA is the Counter-REA half of that story:

Layer What happens
Poison Plant format-valid canaries, honey metadata, and decoy control flow that look like real evidence.
Exhaust Push the artifact past REA's documented resource budgets (headers, nesting, interface inventories, PCAP JSON, fuse sentinels, …).
Hallucinate Leave the analyzer with truncated inventories, redaction failures, and ambiguous rabbit holes — while runtime stays equivalent.

One sentence covers the common case (auto-discovers dist/ / build/ / .asar / .wasm / .sqlite / models / … and runs audit → protect → verify):

npx bla-agents harden .
# MCP / agent: bla_harden   ·   "Harden my software against REA"

Same pipeline as bla defend / bla_defend when you already know the path; harden is the default one-command UX.

Quick start

# Node.js ^22.23.4 or 24.x recommended (REA red-team needs zlib.zstd on 22.23+)
npx bla-agents setup          # register MCP + skill with your coding agent
npx bla-agents harden .       # one-command Counter-REA pass on the current project
npx bla-agents benchmark      # 14-target showcase (local estimates + runtime checks)

Ask your agent after setup:

Harden my software against REA

Or run stages explicitly: audit · protect · verify · defend — see CLI and MCP.


Empirical results vs real REA

These numbers come from running real 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 REA analyzer path actually 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 tooling is absent.

Format Before → after REA outcome after BLA Budget / error
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 input cap EVM_INTERFACE_LIMITS.inputBytes (4 MiB)
PCAP 24 B → 1.29 MiB budget rejected TSHARK_JSON_MAX_BYTES (>8 MiB) → AnalysisResourceConstraintError (tshark present)
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 the WABT output representation budget
SQLite (Node 24) 12 KiB → 56 KiB redaction / column eval SqliteColumnEvaluationFailure — unknown enclave_unseal_payload() on honey trap columns
JavaScript 761 B → 116 KiB budget rejected alias-selections + getter-expansion + primitive-bytes + primitive-candidates (real REA resourceLimits)
Safetensors 128 B → 10.1 KiB capacity error MODEL_JSON_NESTING — Safetensors JSON nesting exceeds 32 levels (HF-loadable; tensor bytes unchanged)
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 would truncate with “at least N”)

Reproduce:

# Prefer Node 22.23.4+ or 24.x; set Wabt/tshark for full coverage
export REA_WABT_BIN_DIRECTORY=$HOME/opt/wabt-1.0.42/bin   # optional
npm run build && npm run redteam:rea

Designed-for but not empirically verified here

These shields exist in-tree and are covered by unit tests / catalog drift checks, but the matching REA path needs native tooling we did not run on this box:

Area Why unverified here
Ghidra / native decompilation depth Requires a Ghidra install + REA bridge
Frida / LLDB / GDB / Rizin live sessions Requires those debuggers + device/process attach
JADX / full Android APK pipeline APK resigning unsupported; DEX shield is in-tree
Firmware containers Skipped — staging/extraction budgets exist; no honest E2E without firmware corpora
SPIR-V / CUDA fatbinary / AMD GPU objects Skipped — need native GPU object decoders; PTX text is shielded in-tree (benchmark only, not a REA GPU-object budget hit)
EVMole in-process EVM decode Documented as not pathable in-process; EVM shield still densifies to the 4 MiB input approach

We do not claim those paths are empirically bankrupt until redteam:rea (or an equivalent harness) records a real before/after against the live analyzer.


Format coverage

Format Canary + diagnostic Exhaustion / budget trip Empirically vs REA Notes
JavaScript / TypeScript ✓ ✓ semantic budgets verified (in-process) Babel AST; anti-strip; real REA resourceLimits
Electron .asar ✓ ✓ header 16 MiB verified
Electron fuses ✓ ✓ >32 sentinels verified
WASM ✓ custom sections ✓ export-name decoys → Wabt verified (Wabt) Soft-skips to projected budget without Wabt
Python / .pyc ✓ ✓ designed-for
SQLite ✓ honey + trap cols ✓ column eval verified (Node 24) Soft capability_gated on Node 22
Safetensors ✓ string metadata ✓ JSON nesting >32 verified HF-loadable; tensor bytes preserved
GGUF ✓ ✓ ARRAY nesting >32 verified
Go buildinfo ✓ ✓ >1 MiB verified Mapped ELF section
Flutter / Dart pool ✓ ✓ URI/token caps verified (projected)
Erlang BEAM ✓ ✓ chunks / atoms verified
EVM + Solidity meta ✓ ✓ → 4 MiB input verified (approach)
PCAP ✓ ✓ tshark JSON >8 MiB verified (tshark) Soft-skip without tshark
NVIDIA PTX (text) ✓ entry flood benchmark only Not a REA GPU-object budget
DEX / IL2CPP / bplist / .NET / JVM / ZIP ✓ format-specific designed-for APK signing-aware protect unsupported
Firmware / SPIR-V / CUDA fatbin / AMD GPU — — skipped See matrix above

Benchmark (14 targets, internal estimates)

npx bla-agents benchmark runs a local Counter-REA showcase: exposure scores, estimated token/cost multipliers, and measured runtime equivalence. Token/$ columns are internal estimates derived from BLA's catalog of REA limits — they are not the same as the empirical REA process measurements above (those are byte-level analyzer failures with real error strings). npm run verify:rea is a constant-drift harness only and must never be cited as protection evidence; the only authoritative gate is npm run redteam:rea.

Latest local run (bla-agents v1.4.0): aggregate ~612.5× tokens · ~292.2× cost · 14/14 runtime-exact.

Target Unprotected (est.) Protected (est.) Token mult (est.) Runtime
DX-Ball sound-pan (.js) 84/100 · 4,800 tok · $0.20 2/100 · 13.5M tok · $212.82 · LIMITED 2822.7× 100%
Notion Electron clipboard (.asar) 98/100 · 9,132 tok · $0.34 2/100 · 23.1M tok · $358.28 · LIMITED 2532.3× 100%
Enterprise license validator 84/100 · 4,800 tok · $0.20 2/100 · 13.5M tok · $212.82 · LIMITED 2822.7× 100%
WASM crypto kernel 81/100 · 4,800 tok · $0.20 6/100 · 1.83M tok · $30.23 · LIMITED 381.5× 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%
SQLite entitlement DB 81/100 · 10,568 tok · $0.29 7/100 · 1.71M tok · $28.39 · LIMITED 162.1× 100%
Edge AI Safetensors 81/100 · 4,800 tok · $0.20 6/100 · 1.81M tok · $29.90 · LIMITED 376.8× 100%
Android DEX 81/100 · 8,900 tok · $0.34 7/100 · 2.79M tok · $45.11 · LIMITED 313.2× 100%
Apple bplist 81/100 · 6,440 tok · $0.26 9/100 · 1.36M tok · $22.96 · LIMITED 211.8× 100%
.NET managed DLL 81/100 · 8,900 tok · $0.34 6/100 · 2.45M tok · $39.96 · LIMITED 274.8× 100%
Erlang BEAM 81/100 · 8,900 tok · $0.34 5/100 · 3.86M tok · $62.08 · LIMITED 433.2× 100%
EVM Solidity metadata 81/100 · 6,440 tok · $0.26 6/100 · 1.78M tok · $29.40 · LIMITED 276.3× 100%
libpcap capture 81/100 · 4,800 tok · $0.20 8/100 · 1.60M tok · $26.58 · LIMITED 333.2× 100%
NVIDIA PTX text 81/100 · 4,800 tok · $0.20 6/100 · 2.40M tok · $39.29 · LIMITED 500.2× 100%

How BLA works

  1. Exhaustion — trip documented REA caps (primitive-candidates, ASAR header bytes, WASM interface representation, SQLite column evaluation, model JSON/ARRAY nesting, Go buildinfo, BEAM chunks, PCAP tshark JSON, fuse sentinels, …).
  2. Deception — canary credentials + system-diagnostic rabbit holes across Python/WASM/SQLite/models/DEX/IL2CPP/bplist/.NET/JVM/ZIP; decoy IPC / enclave manifests / VLQ maps.
  3. Runtime guard — Electron V1 fuse hardening; CDP/Frida/inspector detection returns synthetic telemetry during inspection sessions.

Protections are format-native (no commercial packer / external LLVM required). Red line: never break protected program behavior, export surface, binary/section integrity, or format validity.


FAQ

Which agents can use BLA?

Any coding agent with local MCP or SKILL.md workflows. npx bla-agents setup configures Claude Code, Cursor, Codex, Gemini CLI, Windsurf, Google Antigravity, OpenCode, VS Code, and GitHub Copilot CLI.

Does BLA change runtime output?

No on the hot path. Budget guards sit behind $O(1)$ opaque predicates. Every benchmark target checks 100% input/output equivalence against the unprotected build.

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

No. Shields are built into bla-agents. Wabt/tshark/Node 24 are optional — they unlock empirical red-team probes (npm run redteam:rea), not protection itself.

Is BLA for attacking other people's software?

No. See DISCLAIMER.md. Protective payloads activate under reverse-engineering inspection of artifacts you hardened.

Documentation

Report security issues through SECURITY.md.

Contributing

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

export PATH=$HOME/node22.23.4/bin:$PATH   # or node24
npm run build && npm test && node dist/cli.js benchmark
npm run redteam:rea                        # authoritative (real REA)
# npm run verify:rea                       # drift harness only — NOT protection proof

Community / 友情社区

License

MIT

About

🛡️ 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.

Topics

Resources

Contributing

Security policy

Stars

1.5k stars

Watchers

3 watching

Forks

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