Moritz Schloegel @m_u00d8
Security researcher & postdoc @ASU; PhD from @ruhrunibochum @mu00d8.bsky.social @[email protected] mschloegel.me Joined February 2019-
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Moritz Schloegel retweeted
Tenure Track @ MPIs in Computer Science (SP, SWS, INF). 🖊️ shlink.mpi-sws.org/faculty 📅 01. December 2024 mpi-sp.org/8521/tenure-tr…
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Moritz Schloegel retweeted
I appreciate SIGSAC @acm_ccs in taking a solid first step against review collusions! sigsac.org/protect.html
I appreciate SIGSAC @acm_ccs in taking a solid first step against review collusions! sigsac.org/protect.html https://t.co/hEr0H4AgD5
Moritz Schloegel retweeted
Reading tipp for the day: "Collusion Rings Threaten the Integrity of Computer Science Research" by Littman - cacm.acm.org/opinion/collus…
Moritz Schloegel retweeted
Excited to share that I'll be presenting our work (arvindsraj.com/publication/20…) about finding future vulnerabilities using fuzzing at CCS this week. 🧵 1/6
Moritz Schloegel retweeted
Excellent technical work on a good problem, and a really well written paper.
Excellent technical work on a good problem, and a really well written paper.
Moritz Schloegel retweeted
Congratulations Dr. Chlosta! 🎉
Moritz Schloegel retweeted
In the paper titled "A Binary-level Thread Sanitizer or Why Sanitizing on the Binary Level is Hard", we discuss why it is a challenging problem to apply sanitizer on the binary level. Our main insight is that ASAN is doable (and there are existing implementations), TSAN is ...
Moritz Schloegel retweeted
Our paper on ARVO, a huge (5000+) dataset of reproducible (w/PoC), recompilable vulns in open-source C/C++ projects is now up on arXiv! Awesome work by @n132XxX, @X3eRo0, Jordi Del Castillo, Haoran Xi, Abdelouahab Benchikh, & profs from NYU/ASU/UNSW arxiv.org/abs/2408.02153
Moritz Schloegel retweeted
The slides of our (CC: @m_u00d8) talk "Unleashing AI: The Future of Reverse Engineering with Large Language Models" at @reconmtl are now online. Slides: synthesis.to/presentations/… ReverserAI: github.com/mrphrazer/reve…
Moritz Schloegel retweeted
FUZZING'24 Submission website is open! 📝 fuzzing24.hotcrp.com (21 June AoE). 🔗 fuzzingworkshop.github.io (16 Sep @ Vienna). 🧑🏫 Preregistration-based publication process. ⭐ Accepted papers invited as @acm_tosem Registered Reports //@yannicnoller (RUB/SUTD) @lszekeres (Google)
Moritz Schloegel retweeted
Surprising facts about #fuzzing. A thread in slides 👇
Moritz Schloegel retweeted
This is a fantastic meta-paper if you're writing a paper on a novel fuzzing technique: mschloegel.me/paper/schloege…
Moritz Schloegel retweeted
And we also had a poster
Moritz Schloegel retweeted
... reproducibility studies at github.com/fuzz-evaluator. To guide future fuzzing evaluations, we also publish guidelines that authors and reviewers can use: github.com/fuzz-evaluator… - please let us know if you have feedback! #SP24
Moritz Schloegel retweeted
In the fuzzing session, @m_u00d8 is presenting our paper on potential pitfalls of evaluating fuzzers. We checked 150 papers published in the past six years and performed 8 case studies to show what can go wrong during an evaluation. We publish all data related to our ...
Moritz Schloegel retweeted
Great paper indeed! Hope it will help the fuzzing community, and inspire similar efforts in close areas
Very happy our work on fuzzing evaluations won a Distinguished Paper award at #SP24 Come to my talk in Session 6 starting in a few minutes or find me around to discuss how to evaluate fuzzing!
Very happy our work on fuzzing evaluations won a Distinguished Paper award at #SP24 Come to my talk in Session 6 starting in a few minutes or find me around to discuss how to evaluate fuzzing!
PhD ✅ Thanks everybody that has been part of this awesome journey - your support has been incredible ❤️
PhD ✅ Thanks everybody that has been part of this awesome journey - your support has been incredible ❤️
Moritz Schloegel retweeted
Happy to present "Unleashing AI: The Future of Reverse Engineering with Large Language Models" with @m_u00d8 at @reconmtl. We'll cover current & future RE applications, running offline models and enhancing results by merging LLMs with static analysis. recon.cx/2024/presentat…
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