Ring Around The Regex: Lessons learned from fuzzing regex libraries (Part 1)
- https://secret.club/2024/06/30/ring-around-the-regex-1.html
- https://secret.club/2024/06/30/ring-around-the-regex-1.html
secret club
Ring Around The Regex: Lessons learned from fuzzing regex libraries (Part 1)
Okay, if you’re reading this, you probably know what fuzzing is. As an incredibly reductive summary: fuzzing is an automated, random testing process which tries to explore the state space (e.g., different interpretations of the input or behaviour) of a program…
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ARVO: Atlas of Reproducible Vulnerabilities for Open Source Software - https://arxiv.org/pdf/2408.02153
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RISCVuzz: Discovering Architectural CPU Vulnerabilities via Differential Hardware Fuzzing - https://ghostwriteattack.com/riscvuzz.pdf
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Syzkaller got snapshot-based mode - https://x.com/dvyukov/status/1821543202585022910?t=A5hsdcyoiN48qFNeOUAJoQ&s=03
X (formerly Twitter)
Dmitry Vyukov (@dvyukov) on X
syzkaller, our award-winning kernel fuzzer
https://t.co/fHjR40rzU8
got snapshot-based mode
https://t.co/YIY1gR3617
It's not very fast but based 100% on stock qemu: savevm/loadvm+ivshmem
Significantly improves reproducibility for corpus&crashes but we just…
https://t.co/fHjR40rzU8
got snapshot-based mode
https://t.co/YIY1gR3617
It's not very fast but based 100% on stock qemu: savevm/loadvm+ivshmem
Significantly improves reproducibility for corpus&crashes but we just…
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Fuzzing scripting languages' interpreters' native functions using AFL++ to find memory corruption and more - https://joshua.hu/aflplusplus-fuzzing-scripting-languages-natively
Joshua.Hu Joshua Rogers’ Scribbles
Fuzzing scripting languages’ interpreters’ native functions using AFL++ to find memory corruption and more
Fuzzing applications needs no introduction, and I have written about some interesting problems related to fuzzing in the past [0][1][2][3]. At scale, fuzzing has traditionally focused on compiled binaries and detecting crashes and other memory corruption…
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Overcoming State: Finding Baseband Vulnerabilities by Fuzzing Layer-2 - https://i.blackhat.com/BH-US-24/Presentations/US24-Goos-Overcoming-State-Finding-Baseband-Vulnerabilities-Thursday.pdf
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Meta Bug Bounty — Fuzzing “netconsd” for fun and profit - part 1 - https://blog.fadyothman.com/meta-bug-bounty-fuzzing-netconsd-for-fun-and-profit-part-1-6ffe96eb1419
Medium
Meta Bug Bounty — Fuzzing “netconsd” for fun and profit - part 1
Hello everyone,
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Meta Bug Bounty — Fuzzing “netconsd” for fun and profit — part 2 - https://blog.fadyothman.com/meta-bug-bounty-fuzzing-netconsd-for-fun-and-profit-part-2-52bf188cc877
Medium
Meta Bug Bounty — Fuzzing “netconsd” for fun and profit — part 2
Hey Everyone,
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Fuzzing µC/OS protocol stacks, Part 1: HTTP server fuzzing - https://blog.talosintelligence.com/fuzzing-uc-os-protocol-stacks-part-1/
Cisco Talos Blog
Fuzzing µC/OS protocol stacks, Part 1: HTTP server fuzzing
Any vulnerability in an RTOS has the potential to affect many devices across multiple industries.
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Fuzzing µCOS protocol stacks, Part 2: Handling multiple requests per test case - https://blog.talosintelligence.com/fuzzing-ucos-protocol-stacks-part-2/
Cisco Talos Blog
Fuzzing µCOS protocol stacks, Part 2: Handling multiple requests per test case
This time, I’ll discuss why this approach is more challenging than simply substituting a socket file descriptor with a typical file descriptor.
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Fuzzing µC/OS protocol stacks, Part 3: TCP/IP server fuzzing, implementing a TAP driver - https://blog.talosintelligence.com/fuzzing-uc-os-protocol-stacks-part-3/
Cisco Talos Blog
Fuzzing µC/OS protocol stacks, Part 3: TCP/IP server fuzzing, implementing a TAP driver
This is the final post in the three-part series that details techniques I used to fuzz two µC/OS protocol stacks: µC/TCP-IP and µC/HTTP-server.
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Blackbox-Fuzzing of IoT Devices Using the Router TL-WR902AC as Example - https://tsmr.eu/blackbox-fuzzing.html
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No Peer, no Cry: Network Application Fuzzing via Fault Injection - https://mschloegel.me/paper/bars2024fuzztructionnet.pdf
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TROOPERS24: Fuzzing at Mach Speed: Uncovering IPC Vulnerabilities on MacOS - https://www.youtube.com/watch?v=tZmollb8NXk
YouTube
TROOPERS24: Fuzzing at Mach Speed: Uncovering IPC Vulnerabilities on MacOS
Talk by Dillon Franke - June 26th, 2024 at TROOPERS24 IT security conference in Heidelberg, Germany hosted by @ERNW_ITSec
#TROOPERS24 #ITsecurity
https://troopers.de/troopers24/talks/lb9pjt
More impressions:
https://twitter.com/WEareTROOPERS
https://t…
#TROOPERS24 #ITsecurity
https://troopers.de/troopers24/talks/lb9pjt
More impressions:
https://twitter.com/WEareTROOPERS
https://t…
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Introducing Java fuzz harness synthesis using LLMs - https://blog.oss-fuzz.com/posts/introducing-java-auto-harnessing/
OSS-Fuzz blog
Introducing Java fuzz harness synthesis using LLMs
Introducing LLM-based harness generation for Java OSS-Fuzz projects.
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WuppieFuzz v1.0.0: A coverage-guided REST API fuzzer developed on top of LibAFL - https://github.com/TNO-S3/WuppieFuzz
GitHub
GitHub - TNO-S3/WuppieFuzz: A coverage-guided REST API fuzzer developed on top of LibAFL
A coverage-guided REST API fuzzer developed on top of LibAFL - TNO-S3/WuppieFuzz
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Icicle: Icicle is an experimental fuzzing-specific, multi-architecture emulation framework. - https://github.com/icicle-emu/icicle-emu
GitHub
GitHub - icicle-emu/icicle-emu: Core emulator components for Icicle
Core emulator components for Icicle. Contribute to icicle-emu/icicle-emu development by creating an account on GitHub.
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Sanitize your C++ containers: ASan annotations step-by-step - https://blog.trailofbits.com/2024/09/10/sanitize-your-c-containers-asan-annotations-step-by-step/
The Trail of Bits Blog
Sanitize your C++ containers: ASan annotations step-by-step
AddressSanitizer (ASan) is a compiler plugin that helps detect memory errors like buffer overflows or use-after-frees. In this post, we explain how to equip your C++ code with ASan annotations to find more bugs. We also show our work on ASan in GCC and LLVM.…
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Look Ma, No Input Samples! Mining Input Grammars from Code with Symbolic Parsing - https://dl.acm.org/doi/10.1145/3663529.3663790
ACM Conferences
Look Ma, No Input Samples! Mining Input Grammars from Code with Symbolic Parsing | Companion Proceedings of the 32nd ACM International…
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Reasons for the unreasonable success of fuzzing - https://docs.google.com/presentation/d/1vw9lywrMnNojiOIu-xU5KXZz7WzE0MYNQF6V7n6vyY8/edit#slide=id.g2768ca7ef44_0_65
Google Docs
The unreasonable success of Fuzzing
Reasons for the unreasonable success of fuzzing Does ML’s “bitter lesson” apply to bug discovery?
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