Anshuman Suri

/ʌnʃuman/ (IPA) 🔊

Postdoc, Northeastern University

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177 Huntington Ave

Boston, MA

I am a postdoctoral fellow at Northeastern University, supervised by Alina Oprea. I obtained my PhD from University of Virginia, where I was extremely fortunate to be advised by Professor David Evans. I study the privacy and security challenges of machine learning models: both as targets of attacks and as amplifiers of risk. My work explores how models can be exploited and how they transform the security landscape of systems that use them, with recent emphasis on LLMs

news

Jul 25, 2025 Awarded Lambda Research Grant to work on training-time poisoning defenses for LLMs. Thank you, Lambda :moneybag:
Jan 24, 2025 Our blogpost talking about critical flaws in the evaluation of a recent EMNLP best-paper has been accepted to the ICLR blogpost track!
Nov 14, 2024 :newspaper: UVA Engineering covered a story on our work on evaluating Membership Inference Attacks on Large Language Models?.
Oct 30, 2024 :scroll: My first patent was just issued! This is based on work that our team did during my internship at Oracle Research back in Fall 2021. Patents sure are slow!
Oct 08, 2024 :placard: Presented our work Do Membership Inference Attacks Work on Large Language Models? at COLM in Philadelphia :sunny:.

latest posts

selected publications

  1. exploiting.png
    Exploiting Leaderboards for Large-Scale Distribution of Malicious Models
    Anshuman Suri*, Harsh Chaudhari*, Yuefeng Peng*, and 3 more authors
    In IEEE Symposium on Security and Privacy (S&P), 2026
  2. llmjailbreak.png
    LLM Jailbreak Oracle
    Shuyi Lin, Anshuman Suri, Alina Oprea, and 1 more author
    arXiv preprint arXiv:2506.17299, 2025
  3. saga.png
    SAGA: A Security Architecture for Governing AI Agentic Systems
    Georgios Syros, Anshuman Suri, Jacob Ginesin, and 2 more authors
    In Network and Distributed System Security (NDSS) Symposium, 2026
  4. iha.png
    Do Parameters Reveal More than Loss for Membership Inference?
    Anshuman Suri, Xiao Zhang, and David Evans
    Transactions on Machine Learning Research (TMLR), 2024