BLA traps AI reverse engineers with decoys

BLA is a clever response to agentic reverse engineering: attack the analyzer’s budget and confidence instead of relying solely on obfuscation. Its weakness is that protection depends on attackers sharing predictable parser limits, while decoy payloads increase artifact size and complexity.

• –Uses honey metadata, fake clues, shadow state machines, and decoy control flow to mislead LLM-based analyzers
• –Deliberately triggers documented limits for formats such as ASAR, WASM, SQLite, JavaScript, Safetensors, and GGUF
• –Adds self-sealing and cross-artifact entanglement to make decoy stripping or isolated patching harder
• –The project reports 14/14 runtime-equivalent benchmark targets, but those results remain vendor-reported
• –Defensive use cases are strongest for proprietary desktop apps, SDKs, models, and build artifacts exposed to autonomous coding agents