Sébastien Bardin

Looking for submitting your latest research at SAS 2026? Good news, submission deadline is extended to May 7, yet you still need paper registration by May 1 AoE (still some time left)

@Montyly Another major breakthrough by @Montyly !!

Today I am releasing IsItVulnerable: a new tool I’ve been working on for the past several months: github.com/montyly/isItVu… It builds on recent LLM progress and over a decade of experience building security tools. I developed a new technique that combines abstract interpretation with machine learning The key insight is that this method abstracts the intelligence away entirely. I call it Abstract Intelligence, or AI The result is a major breakthrough in program analysis: IsItVulnerable finds all bugs with 100% recall Yes, all bugs. Fully guaranteed I have tested it extensively, and it has never failed. The results are honestly incredible April 1, 2026 marks a turning point for security, and the industry will never be the same My DMs are open for investors. Entry ticket starts at $500k.

A special workshop celebrating Thomas Ball's 60th birthday and extraordinary impact in PL, SE, and formal methods will be held on June 16th at PLDI'26! There is a great line up of speakers who will reflect on his work and lasting influence. Don't miss it! pldi26.sigplan.org/home/tb-60-2026

The Static Analysis Symposium (SAS) is taking place as a part of SPLASH/ISSTA this year! Consider submitting a paper, deadline *May 1st*, with special topics including Static Analysis and AI, and Static Analysis and Education: #Call-for-Papers" target="_blank" rel="nofollow noopener">conf.researchr.org/home/splash-is…

@Blackhoodie_RE will be at #BSidesLuxembourg, on May 6th with a training on Linux memory forensics 😍 Thank you to BSides Luxembourg and the Luxembourg House of Cyber for hosting us! Registration is now open blackhoodie.re/BSidesLuxembou…

Finding backdoors in software is like hunting for a needle that’s actively trying to hide. 🪡🕵️ Check out our @fosdem talk with @plumtrie on using fuzzing to automate the search! 📺 Watch: mirrors.dotsrc.org/fosdem/2026/ub… 📜 ICSE Paper: binsec.github.io/assets/publica…

Terence Tao: Formal Verification Breaks the Trust Barrier in Mathematics Formal verification is transforming mathematical collaborations — enabling anonymous contributions, machine-checked proofs, and radically more precise scientific discussion.

RIP Tony Hoare. 😢 I only met him a couple times many years ago at MSR and was not accomplished enough at the time to have much useful to say, but he sure cast a long shadow over the field...

In case you're interested in AI for Math and don't already recognize Leonardo de Moura's name below.... he invented Lean at MSR a decade ago. Give him a follow.

Last week, we wrapped up the #NDSSSymposium2026. While we’re sad it’s over, we couldn’t be happier with how it went. This year we had: 🌏 600+ attendees representing 30+ countries 🧑‍🏫 10 amazing workshops 📝 190+ papers presented We can’t wait to see you again next year!

Breaking news from NDSS26: it seems that we have won a Distinguished Paper Award for "Decompiling the Synergy: An Empirical Study of Human-LLM Teaming in Software Reverse Engineering" A giant thank you to my amazing co-authors and everyone who participated in the experiment!

UPDATE: our work won a best paper award 🏆 @NDSSSymposium! Check out our work on establishing the first measurements for understanding how LLMs are changing reverse engineering. Shout out to the whole team from @SCAI_ASU, @EURECOM, and @UniPadova

Open source has allowed everyone from hobbyists to major companies to build software. But its ecosystem is getting overwhelmed. Dr. William Enck broke down unique vulnerabilities of the software supply chain & shared how researchers can help developers build safer software.

This morning's keynote speaker, @danwallach, broke down how DARPA’s TRACTOR: Translating All C to Rust program is taking an all-hands-on-deck approach to solve the Internet's persistent and stubborn memory safety problem, once and for all. #NDSSSymposium2026

The NDSS Symposium 2026 is only two days away!! As we gear up for this year’s event, we’re throwing it back to last year’s symposium. Check it out!

Excited to attend @NDSSSymposium and BAR workshop next week. Especially interested these days in automated fault injection analysis, exploitability analysis & vulnerability triage, side channels & PQC, and looking for collaborations on these topics.

The BAR workshop 2026 edition is next week @NDSSSymposium San Diego, featuring two awesome keynotes by @perribus and @pinkflawd together with 10 technical talks. Hoe to see you there! ndss-symposium.org/ndss2026/co-lo…

Sometimes your friend has such a crazy idea that it just might work... Send your best AI-generated cybersecurity research to @synsec_ai

SOAP 2026 is now accepting paper submissions! Submit your experiments, tools, and ideas on program analysis by March 4, 2026 (soap26.hotcrp.com). More info: pldi26.sigplan.org/home/SOAP-2026 #SOAP2026 #CallForPapers #ProgramAnalysis Co-located with #PLDI2026 in #Boulder

LLMs vs the Halting Problem. (Why, what, where going.) We recently released a paper on this; link to follow. A few comments here for context. Why? With LLM "reasoning" excitement, we thought: why not try LLMs on the first ever code reasoning task, the halting problem. Turing's proof of undecidability established fundamental limits. Fun bit: no matter how "superintelligent" AI becomes, this is a problem it can never perfectly solve. Where to get data to measure? SVCOMP. Verification researchers have through their insight and hard work, curated several thousand example C programs. They run dedicated tools over this dataset in an annual competition. This is in a sense the home turf of symbolic. We didn't know how LLMs would do, and in particular were aware of results of @rao2z , @RishiHazra95 and others showing that LLMs trail symbolic on "easier" decidable problems (SAT, propositional planning). The surprise: LLMs are competitive on halting—where they often trail on "easier" problems. Why? Hypothesis: LLMs are heuristic approximators; in undecidability, heuristic approximation isn't just a workaround—it's often the only way forward. Broader context: Penrose claimed undecidability proved AI is impossible (but didn't show humans can solve the undecidable). Turning the tables: undecidability is an ideal target for heuristic LLMs. Instead of using "already crushed" logic problems to show LLM limits, let's look at uncrushed problems where LLMs might actually help.