Cracking Firmware with Claude: Senior-Level Skill, Junior-Level Autonomy

2026-07-08 · Source: Bishop Fox - Bishopfox.com · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cybersecurity & Data Privacy · Depth: Expert, long

Summary

Claude Code, running Sonnet 4.5, successfully reverse-engineered SonicWall's proprietary SWI firmware encryption, a task previously requiring a senior vulnerability researcher. The experiment provided Claude with an encrypted firmware image and a decrypted root filesystem from a SonicWall NSv virtual appliance. Using Binary Ninja's Model Context Protocol (MCP) integration, Claude independently identified OpenSSL's "enc" format, discovered an RSA-encrypted password on line 2 of the header, and traced the key to a HashiCorp Vault instance within the appliance. It then reconstructed Vault's master key from three Shamir secret shares embedded in a "systemd" service file, implementing GF(256) arithmetic. After one human prompt to run the Vault binary directly, Claude regenerated an expired authentication token and exported the RSA-2048 private key. Finally, it decrypted the line 2 password using OAEP SHA-256 padding and then the full firmware payload, revealing a TAR archive. This demonstrated senior-level technical skill with junior-level autonomy.

Key takeaway

For AI Security Engineers integrating advanced models into vulnerability research, recognize that current AI agents offer senior-level technical skill but junior-level autonomy. You should design workflows that trust the model's execution capabilities for methodical tasks while actively providing strategic direction and verification at critical junctures. This approach allows your expertise to scale significantly, transforming days of manual effort into focused supervision and enabling faster, more efficient reverse engineering and vulnerability discovery.

Key insights

AI agents like Claude can perform senior-level reverse engineering tasks with minimal human guidance, demonstrating deep technical knowledge but requiring judgment oversight.

Principles

• AI agents possess senior-level technical knowledge.
• Human-AI collaboration excels at critical pivots.
• Trust AI skill, supervise its judgment.

Method

An AI agent can reverse-engineer proprietary firmware by analyzing file structures, decompiling binaries, identifying embedded key management systems, reconstructing cryptographic keys (e.g., Shamir shares over GF(256)), and leveraging vendor binaries for key extraction.

In practice

• Integrate LLMs with decompilers (e.g., Binary Ninja MCP).
• Use Docker to run extracted vendor binaries.
• Provide targeted prompts for strategic impasses.

Topics

• Firmware Reverse Engineering
• AI Agents
• HashiCorp Vault
• Cryptographic Analysis
• Shamir Secret Sharing
• Binary Ninja

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Security Engineer, AI Scientist, AI Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Bishop Fox - Bishopfox.com.