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Even though this is a reversing challenge, I thought I’d try to do the least amount of work and use Angr. Because this was labeled as an
easy challenge, writing the angr solve script was also
- Solved after the CTF ended :(
- I needed to see this post sooner…
- One of the answers includes an arithmetic version of left and right shift.
- I need to practice more crypto…
A little while ago, after I passed my candidacy exam, I had a small burst of confidence. Because of this, I ended up trying to install Arch Linux for the first time since 2014 (when I was in my math undergrad program). Below is the steps I had to take to get there!
I think this was one of the more easier reversing challenges from PlaidCTF. Regardless, I think it would still be beneficial for me to make this write-up as it is the first time I really used Ghidra instead of IDA on a task.
Did I say I passed my Candidacy Exam? ..well, I passed my Candidacy Exam.
MOV* (Intel Sytnax) has been driving me crazy for a little bit…
This was another simple reverse engineering task. It can also be found on the CTF hosts website linked in the last post). Lucky for me, I have been trying to learn and incorporate angr more into my workflow.
I participated in AUCTF 2020, which was hosted by Auburn University Ethical Hacking Club (AUECH). It was designed to be friendly towards new CTFers so I thought I’d take a crack at it over the weekend as part of a smooth transition. I made a team (something to do with coffee) of one and tried some challenges.
It has really been a while since I have played in a CTF seriously. Really, since starting graduate school, I feel like I have been playing “catch-up” (for various reasons). But, having become much more comfortable and confident in my ability to conduct research and because of the current stay-at-home situation due to COVID-19, I have decided to spend some weekends playing (or reviewing) CTFs.
This is a short post that serves as the extension of the previous fuzzing post.
What is fuzzing?
Simply put, fuzzing is a technique for testing programs with randomly generated input. This randomization helps us find bugs by providing potentially invalid and corner-case inputs for the target program.
Besides coffee, I have been obsessed with all things workstations (such as desks and chairs). This also includes computer peripherals, my favorite of which being mechanical keyboards.