Logic locking (based on our CCS ’17 paper): https://github.com/DfX-NYUAD/CCS17/blob/master/README.md
Split manufacturing (based on our DAC ’16 paper): https://github.com/seth-tamu/network_flow_attack
Sparse prime implement attack: https://github.tamu.edu/hardwaresecurity/SPI_attack
New vulnerabilities detected by our first hardware fuzzer, TheHuzz (USENIX Security ’22 paper): https://seth.engr.tamu.edu/software-releases/thehuzz CVEs: CVE-2021-40506, CVE-2021-40507, CVE-2021-41612, CVE-2021-41614, and CVE-2021-41613.
New vulnerabilities detected by our second hardware fuzzer, HyPFuzz (USENIX Security ’23 paper): https://seth.engr.tamu.edu/software-releases/hypfuzz/ CVEs: CVE-2022-33021 and CVE-2022-33023.
For the source code or any other details about TheHuzz (USENIX Security ’22 paper) or HyPFuzz (USENIX Security ’23 paper), please email us at jv.rajendran@tamu.edu and ahmad.sadeghi@trust.tu-darmstadt.de, cc’ing your advisor.
Artifacts for our state-of-the-art RL-based technique for detecting hardware Trojans, DETERRENT (DAC ’22 paper): https://github.com/gohil-vasudev/DETERRENT
Artifacts for our RL-based hardware Trojan insertion tool, ATTRITION (CCS ’22 paper), that evades two classes of detection techniques: https://github.com/gohil-vasudev/ATTRITION
Artifacts for our RL-based adversarial example generation technique, AttackGNN (USENIX Security ’24 paper), that successfully thwarts GNNs for IP Piracy, hardware Trojan localization and detection, reverse engineering, and circuit obfuscation: https://github.com/gohil-vasudev/AttackGNN
We highly appreciate your comments and feedback on our releases. Our students will also answer your questions if you have any.