Itay Cohen 

@megabeets_

Ⓥ Activist, Reverser, CTF player and a Blogger | Maintainer of Cutter () | radare2 core | Malware Researcher @ Check Point

Vrijeme pridruživanja: rujan 2016.

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  1. Prikvačeni tweet
    23. pro 2019.

    Just published a new blog-post >> 5 ways to patch binaries with Cutter 🚀 Yes, you can patch from the decompiler! It's not a long article but it feels great to write again! I missed it. Check it out @

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  2. proslijedio/la je Tweet
    1. velj

    Cutter v1.10.1 released! 🥳 Tomorrow, GitHub will capture and store every repository in an archival facility deep in an Arctic mountain. 🥶🗻 Today, we release a special edition for the benefit of future mankind and other beings 👽 Get it @ Highlights >>

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  3. proslijedio/la je Tweet
    18. sij

    Sharing my analyses on the recent malware that targeted instances, categorized by as . Using of course 😍😍😍.

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  4. proslijedio/la je Tweet
    10. sij

    Do you like using rules? Try my plugin and integrate them into your workflow :D Use cases are: Packer detection (no need to run PEiD/DiE at the start if your analysis anymore), cryptographic constants detection and malware attribution

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  5. proslijedio/la je Tweet
    29. pro 2019.

    Use to solve a simple crack me of the 36c3 junior ctf

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  6. proslijedio/la je Tweet
    20. pro 2019.

    Cutter v1.10 now has a DEBUGGER! 🐞🥳 After a lot of work, we are so happy to announce that we finally implemented your most requested feature. The beta version of the debugger is available NOW on our website >> List of features and what's coming next >>

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  7. 15. pro 2019.

    Reversing and instrumenting Street Fighter emulator using and >> One of my favorite talks from is now on youtube! "Not only Street Fighter: A journey into Moo" - Good work and !

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  8. proslijedio/la je Tweet
    6. pro 2019.

    Deobfuscating APT32 Flow Graphs with Cutter and Radare2 - Check Point Research

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  9. 3. pro 2019.

    For months we at and mapped and tracked code-connections between thousands of Russian APT samples we classified. Our talk from is now available online 🥳 Read the full research here >>

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  10. proslijedio/la je Tweet
    25. stu 2019.

    just published my blog on solving the vm1 challenge by using cutter () for beginners

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  11. proslijedio/la je Tweet
    27. lis 2019.

    Radare is the veganism of the reverse engineering world.

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  12. proslijedio/la je Tweet
    26. lis 2019.
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  13. proslijedio/la je Tweet

    Nice talk from & about the malware russian ecosystem during . And your slide deck is really beautiful. I love it ;)

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  14. proslijedio/la je Tweet
    13. lis 2019.

    Want to contribute to and don't know where to begin? is a great time to start! 😎 We tagged dozens of issues which are great for beginners and can be your first contribution --> Help the community and get a T-Shirt & Stickers!

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  15. 3. lis 2019.

    If you're in and interested in radare2 and Cutter, I have bunch of & stickers to give 😎 Feel free to DM or catch me around

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  16. proslijedio/la je Tweet
    3. lis 2019.

    This is the research I am most proud to have worked on: A series of mistakes reveals the internals of an attack targeting Egypt's civil society and utilizing OAuth phishing, location-tracking Android applications and more

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  17. proslijedio/la je Tweet
    1. lis 2019.

    is finally here and Cutter is once again joining the party! 🎉 Want to contribute to open-source? We have some great easy-for-beginners issues to start with: Looking forward to see you!

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  18. 29. ruj 2019.

    The talk we gave at is now up! It is amazing how much progress we do each year and hopefully Cutter will soon become a good alternative for other, more mature, reverse engineering frameworks. A big THANK-YOU for our fantastic community in and !

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  19. proslijedio/la je Tweet

    In an unprecedented scale research we conducted with we were able to map code-similarities between thousands of Russian APT samples. Read our publication @

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  20. 24. ruj 2019.

    My recent research in collaboration with has just been published! 🚀 We mapped the Russian APT ecosystem by gathering and classifying thousands of malicious samples to detect and analyze code similarities between them. Check it out @

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