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Marcel Böhme👨‍🔬 Profile picture
@mboehme_
Aug 22 • 5 tweets • 2 min read • Read on X
Before we announce the exciting keynotes for #FUZZING'24, we found some time to upload the recordings for the last two years by Abhishek Arya (@infernosec), @AndreasZeller, Cristian Cadar (@c_cadar), and Kostya Serebryany (@kayseesee).

//@lszekeres, @baishakhir, @yannicnoller.
FUZZING'22 Keynote by Abhishek Arya (Google) on "The Evolution of Fuzzing in Finding the Unknowns"
FUZZING'22 Keynote by Andreas Zeller (CISPA & Saarland U) on "Fuzzing: A Tale of Two Cultures"
FUZZING'23 Keynote by Cristian Cadar (Imperial College London) on "Three Colours of Fuzzing: Reflections and Open Challenges"
FUZZING'23 Keynote by Kostya "KCC" Serebryany (Google) on "Rich Coverage Signal and the Consequences for Scaling"

• • •

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More from @mboehme_

Marcel Böhme👨‍🔬 Profile picture
May 29
Surprising facts about #fuzzing. A thread in slides 👇 Image
Whitebox fuzzing is most effective because it can, in principle, *prove* the absence of bugs.

"Partition-based Regression Verification": mboehme.github.io/paper/ICSE13.p…
Image
In contrast, blackbox fuzzing cannot prove anything.

Djikstra's EWD249: cs.utexas.edu/users/EWD/tran…
Image
Read 23 tweets
Marcel Böhme👨‍🔬 Profile picture
May 12
Recently modified code and sanitizer instrumentation seem to be among the most effective heuristics for target selection in directed #fuzzing according to this recent SoK by Weissberg et al. LLMs show much promise for target selection, too.

📝 mlsec.org/docs/2024c-asi…
Image
More info about those two heuristics:
🦠 Sanitizer-guided Greybox Fuzzing:
♻️ Regression Greybox Fuzzing: usenix.org/system/files/s…
mboehme.github.io/paper/CCS21.pdf
But in an interesting twist, the authors find that choosing functions by their complexity might be even better at retrieving functions that contained vulnerabilities in the past.
Read 5 tweets
Marcel Böhme👨‍🔬 Profile picture
Mar 28, 2023
After oracles for memory-safety, what's next?

- generic correctness prop.
- dataflow based properties
- "unusually large" resource consumptions

* Program-specific vs generic oracles
* One input (e.g., crash) vs distribution (e.g. performance)
* Ref implementation(s)

#Dagstuhl
- Human artifacts (documentation) as oracles.
- How to infer oracles, e.g. from JavaDoc comments? What about false pos? Consider them as signal for user.
- Oracle problem impacts how good deduplication works.
- Metamorphic testing. Explore in other domains, e.g. perf. testing!
- Mine assertions and use them in a fuzzer feedback loop
- Assertions are the best way to build oracles into the code
- hyperproperties are free oracles (differential testing)
- ML to detect vuln patterns. Use as oracles
- Bugs as deviant behavior (Dawson)
Read 5 tweets
Marcel Böhme👨‍🔬 Profile picture
Mar 28, 2023
Peter O'Hearn (@PeterOHearn12) on "Hits and Misses from a decade of program analysis in industry".

#Dagstuhl
- Bi-abductive symbolic execution
- Infer ran "symbolic execution" on changed part of every commit/diff
- Post-land analysis versus diff-time analysis changed fix rate from 0% to 70%. Why?
* Cost of context switch
* Relevance to developer
- Deploying a static analysis tool is an interaction with the developers.
- Devs would accept false positives and work with the team to "fit" the tool to the project rather.
- Audience matters!
* Dev vs SecEng
* Speed tolerance
* FP/FN tolerance
Read 5 tweets
Marcel Böhme👨‍🔬 Profile picture
Mar 28, 2023
Anna Zaks on "From Bug Detection to Mitigation and Elimination".

- Static and dynamic analysis.
- Hard to ensure coverage at scale!

#Dagstuhl
Security tooling
- ideal solution mitigates entire classes of bugs
- performance is important.
- adoption is critical!
- works with the ecosystem
Rewriting in memory-safe language (e.g. Swift)
- View new code as green islands in a blue ocean of memory-unsafe code.
- Objective: Turn blue to green.
- We need solutions with low adoption cost.
Read 4 tweets
Marcel Böhme👨‍🔬 Profile picture
Mar 28, 2023
Anders Møller (@amoellercsaudk) on "Dependencies Everywhere".

#Dagstuhl
Motivation
- Keeping dependencies up2date is not easy.
- Breaking changes are problematic for dependants.
- Informally specified and difficult to check against your project
- general tools don't assist with changes.
Research challenges
- we fully trust the dependencies ecosystem.
- supply chain is reported to be full of vulnerabilities, how does a maintainer interpret this? 95% false positives?
Read 5 tweets

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