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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.

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.

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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.

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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

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.

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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

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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

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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.

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FAQ

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.

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.

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.

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

Documentation

• DISCLAIMER.md — defensive use, own-software only
• Installation and agent setup
• CLI and MCP contracts
• Empirical REA validation
• Counter-REA matrix
• v1.4.0 release notes (staged)
• CHANGELOG

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

• 🎯 Public BLA CrackMe Challenge (challenge/) — Can your AI reverse-engineering agent beat a bankrupt-hardened BLA binary without falling into our Honeypot Flags?
• LINUX DO (linux.do) — 新的理想型社区

License

MIT