CAD for Assurance of Electronic Systems


By: Embedded Security Group, Max Planck Institute for Security and Privacy, Germany

Stage: Gate-Level


HAL [/hel/] is a comprehensive netlist reverse engineering and manipulation framework.

Virtually all available research on netlist analysis operates on a graph-based representation of the netlist under inspection. At its core, HAL provides exactly that: A framework to parse netlists of arbitrary sources, e.g., FPGAs or ASICs, into a graph-based netlist representation and to provide the necessary built-in tools for traversal and analysis of the included gates and nets.

Our vision is that HAL becomes the hardware-reverse-engineering-equivalent of tools like IDA or Ghidra. We want HAL to enable a common baseline for researchers and analysts to improve reproducibility of research results and abstract away recurring basic tasks such as netlist parsing etc.


HAL Team

Input/Output Interface

  • Input: A netlist to analyze
  • Output: Whatever your analysis plugins can provide


Since HAL is under active development dependencies can change over time.
Please check our git repo to find the most recent information.

Licensing Info

MIT License


Fyrbiak, Marc; Wallat, Sebastian; Swierczynski, Pawel; Hoffmann, Max; Hoppach, Sebastian; Wilhelm, Matthias; Weidlich, Tobias; Tessier, Russell; Paar, Christof

HAL—The Missing Piece of the Puzzle for Hardware Reverse Engineering, Trojan Detection and Insertion Journal Article

In: IEEE Transactions on Dependable and Secure Computing, vol. 16, no. 3, pp. 498-510, 2019, ISSN: 1941-0018.

Abstract | Links | BibTeX

Wallat, Sebastian; Albartus, Nils; Becker, Steffen; Hoffmann, Max; Ender, Maik; Fyrbiak, Marc; Drees, Adrian; Maaßen, Sebastian; Paar, Christof

Highway to HAL: Open-Sourcing the First Extendable Gate-Level Netlist Reverse Engineering Framework Proceedings Article

In: Proceedings of the 16th ACM International Conference on Computing Frontiers, pp. 392–397, Association for Computing Machinery, Alghero, Italy, 2019, ISBN: 9781450366854.

Abstract | Links | BibTeX


  • This work was partially supported by ERC Advanced Grant No. 695022

User Guide Link can be found at this link