🔒 Password Attacks
Crack passwords and create wordlists.
John the Ripper (https://github.com/magnumripper/JohnTheRipper)
C
Linux/Windows/macOS
John the Ripper is a fast password cracker.
hashcat (https://github.com/hashcat/hashcat)
C
Linux/Windows/macOS
World's fastest and most advanced password recovery utility.
Hydra (https://github.com/vanhauser-thc/thc-hydra)
C
Linux/Windows/macOS
Parallelized login cracker which supports numerous protocols to attack.
Zero Trust Hackers (https://t.me/zerotrusthackers)
Tg
Linux/Windows/macOS/Mobile
Shares with you daily resources in the Cyber Security EcoSystem.
ophcrack (https://gitlab.com/objectifsecurite/ophcrack)
C++
Linux/Windows/macOS
Windows password cracker based on rainbow tables.
Ncrack (https://github.com/nmap/ncrack)
C
Linux/Windows/macOS
High-speed network authentication cracking tool.
WGen (https://github.com/agusmakmun/Python-Wordlist-Generator)
Python
Linux/Windows/macOS
Create awesome wordlists with Python.
SSH Auditor (https://github.com/ncsa/ssh-auditor)
Go
Linux/macOS
The best way to scan for weak ssh passwords on your network.
Top Hacker Tools: https://t.me/zerotrusthackers/47
SQL Injection Tools: https://t.me/zerotrusthackers/58
Cryptography Tools: https://t.me/zerotrusthackers/59
More Resources Here
https://whatsapp.com/channel/0029VaxVv551iUxRku094918
Crack passwords and create wordlists.
John the Ripper (https://github.com/magnumripper/JohnTheRipper)
C
Linux/Windows/macOS
John the Ripper is a fast password cracker.
hashcat (https://github.com/hashcat/hashcat)
C
Linux/Windows/macOS
World's fastest and most advanced password recovery utility.
Hydra (https://github.com/vanhauser-thc/thc-hydra)
C
Linux/Windows/macOS
Parallelized login cracker which supports numerous protocols to attack.
Zero Trust Hackers (https://t.me/zerotrusthackers)
Tg
Linux/Windows/macOS/Mobile
Shares with you daily resources in the Cyber Security EcoSystem.
ophcrack (https://gitlab.com/objectifsecurite/ophcrack)
C++
Linux/Windows/macOS
Windows password cracker based on rainbow tables.
Ncrack (https://github.com/nmap/ncrack)
C
Linux/Windows/macOS
High-speed network authentication cracking tool.
WGen (https://github.com/agusmakmun/Python-Wordlist-Generator)
Python
Linux/Windows/macOS
Create awesome wordlists with Python.
SSH Auditor (https://github.com/ncsa/ssh-auditor)
Go
Linux/macOS
The best way to scan for weak ssh passwords on your network.
Top Hacker Tools: https://t.me/zerotrusthackers/47
SQL Injection Tools: https://t.me/zerotrusthackers/58
Cryptography Tools: https://t.me/zerotrusthackers/59
More Resources Here
https://whatsapp.com/channel/0029VaxVv551iUxRku094918
Top 7 FREE Courses By Udacity 👇👇
Introduction to Python Programming
https://www.udacity.com/course/introduction-to-python--ud1110
Intro to Java: Functional Programming
https://www.udacity.com/course/java-programming-basics--ud282
SQL for Data Analysis
https://www.udacity.com/course/sql-for-data-analysis--ud198
Intro to Data Analysis
https://www.udacity.com/course/intro-to-data-analysis--ud170
Developing Android Apps with Kotlin
https://www.udacity.com/course/developing-android-apps-with-kotlin--ud9012
Intro to JavaScript
https://www.udacity.com/course/intro-to-javascript--ud803
Intro to Machine Learning
https://www.udacity.com/course/intro-to-machine-learning--ud120
Free PHP Courses for Web Developer
https://t.me/webdevresourcestp/64
NVIDIA FREE AI Certification Courses
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ENJOY LEARNING 👍👍
Follow this WhatsApp Channel for More Resources
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Introduction to Python Programming
https://www.udacity.com/course/introduction-to-python--ud1110
Intro to Java: Functional Programming
https://www.udacity.com/course/java-programming-basics--ud282
SQL for Data Analysis
https://www.udacity.com/course/sql-for-data-analysis--ud198
Intro to Data Analysis
https://www.udacity.com/course/intro-to-data-analysis--ud170
Developing Android Apps with Kotlin
https://www.udacity.com/course/developing-android-apps-with-kotlin--ud9012
Intro to JavaScript
https://www.udacity.com/course/intro-to-javascript--ud803
Intro to Machine Learning
https://www.udacity.com/course/intro-to-machine-learning--ud120
Free PHP Courses for Web Developer
https://t.me/webdevresourcestp/64
NVIDIA FREE AI Certification Courses
https://tinyurl.com/5hessh3t
CISCO Free Certification Courses
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ENJOY LEARNING 👍👍
Follow this WhatsApp Channel for More Resources
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
16 Websites for Coders 📍
1. HTML & CSS:- htmlcheatsheet.com
2. JavaScript :- https://lnkd.in/dfSvFuhM
3. Jquery - https://oscarotero.com/jquery/
4. Bootstrap 5:- https://lnkd.in/dNZ6qdBh
5. Tailwind CSS:- https://lnkd.in/d_T5q5Tx
6. React:- https://lnkd.in/de55QGBg
7. Python :- https://lnkd.in/dmZa39rE
8. MongoDB:- https://lnkd.in/dBXXCQ43
9. SQL:- https://lnkd.in/dEFY_jAk
10. Nodejs :- https://lnkd.in/dwry8BKH
11. Expressjs:- https://quickref.me/express
12. Django :- https://lnkd.in/dYWQKZnT
13. PHP- https://quickref.me/php
14. Google Dork:- https://lnkd.in/dKej3-42
15. Linux:- https://lnkd.in/dCgH_qUq
16. Git:- https://lnkd.in/djf9Wc98
7 Free Courses by Udacity: https://t.me/techpsyche/633
Free PHP Courses for Web Developer
https://t.me/webdevresourcestp/64
NVIDIA FREE AI Certification Courses
https://tinyurl.com/5hessh3t
Passive Income Ideas for Developers
https://t.me/techpsyche/596
CISCO Free Certification Courses
https://bit.ly/4i9Kc9Z
ENJOY LEARNING 👍👍
Follow this WhatsApp Channel for More Resources
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
1. HTML & CSS:- htmlcheatsheet.com
2. JavaScript :- https://lnkd.in/dfSvFuhM
3. Jquery - https://oscarotero.com/jquery/
4. Bootstrap 5:- https://lnkd.in/dNZ6qdBh
5. Tailwind CSS:- https://lnkd.in/d_T5q5Tx
6. React:- https://lnkd.in/de55QGBg
7. Python :- https://lnkd.in/dmZa39rE
8. MongoDB:- https://lnkd.in/dBXXCQ43
9. SQL:- https://lnkd.in/dEFY_jAk
10. Nodejs :- https://lnkd.in/dwry8BKH
11. Expressjs:- https://quickref.me/express
12. Django :- https://lnkd.in/dYWQKZnT
13. PHP- https://quickref.me/php
14. Google Dork:- https://lnkd.in/dKej3-42
15. Linux:- https://lnkd.in/dCgH_qUq
16. Git:- https://lnkd.in/djf9Wc98
7 Free Courses by Udacity: https://t.me/techpsyche/633
Free PHP Courses for Web Developer
https://t.me/webdevresourcestp/64
NVIDIA FREE AI Certification Courses
https://tinyurl.com/5hessh3t
Passive Income Ideas for Developers
https://t.me/techpsyche/596
CISCO Free Certification Courses
https://bit.ly/4i9Kc9Z
ENJOY LEARNING 👍👍
Follow this WhatsApp Channel for More Resources
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
👍1
Forwarded from Artificial Intelligence Resources TP . AI Tools . AI Updates
How AI Search Actually Works 👆
Tableau Cheat Sheet ✅
This Tableau cheatsheet is designed to be your quick reference guide for data visualization and analysis using Tableau. Whether you’re a beginner learning the basics or an experienced user looking for a handy resource, this cheatsheet covers essential topics.
1. Connecting to Data
- Use Connect pane to connect to various data sources (Excel, SQL Server, Text files, etc.).
2. Data Preparation
- Data Interpreter: Clean data automatically using the Data Interpreter.
- Join Data: Combine data from multiple tables using joins (Inner, Left, Right, Outer).
- Union Data: Stack data from multiple tables with the same structure.
3. Creating Views
- Drag & Drop: Drag fields from the Data pane onto Rows, Columns, or Marks to create visualizations.
- Show Me: Use the Show Me panel to select different visualization types.
4. Types of Visualizations
- Bar Chart: Compare values across categories.
- Line Chart: Display trends over time.
- Pie Chart: Show proportions of a whole (use sparingly).
- Map: Visualize geographic data.
- Scatter Plot: Show relationships between two variables.
5. Filters
- Dimension Filters: Filter data based on categorical values.
- Measure Filters: Filter data based on numerical values.
- Context Filters: Set a context for other filters to improve performance.
6. Calculated Fields
- Create calculated fields to derive new data:
- Example: Sales Growth = SUM([Sales]) - SUM([Previous Sales])
7. Parameters
- Use parameters to allow user input and control measures dynamically.
8. Formatting
- Format fonts, colors, borders, and lines using the Format pane for better visual appeal.
9. Dashboards
- Combine multiple sheets into a dashboard using the Dashboard tab.
- Use dashboard actions (filter, highlight, URL) to create interactivity.
10. Story Points
- Create a story to guide users through insights with narrative and visualizations.
11. Publishing & Sharing
- Publish dashboards to Tableau Server or Tableau Online for sharing and collaboration.
12. Export Options
- Export to PDF or image for offline use.
13. Keyboard Shortcuts
- Show/Hide Sidebar: Ctrl+Alt+T
- Duplicate Sheet: Ctrl + D
- Undo: Ctrl + Z
- Redo: Ctrl + Y
14. Performance Optimization
- Use extracts instead of live connections for faster performance.
- Optimize calculations and filters to improve dashboard loading times.
Tableau Learning Plan
https://t.me/dataanalysisresourcestp/84
7 Free Data Analytics Courses👇👇
https://tinyurl.com/326exaw7
Data Analyst Checklist
https://t.me/dataanalysisresourcestp/99
Hope it helps :)
Share our channel link with your friends:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
This Tableau cheatsheet is designed to be your quick reference guide for data visualization and analysis using Tableau. Whether you’re a beginner learning the basics or an experienced user looking for a handy resource, this cheatsheet covers essential topics.
1. Connecting to Data
- Use Connect pane to connect to various data sources (Excel, SQL Server, Text files, etc.).
2. Data Preparation
- Data Interpreter: Clean data automatically using the Data Interpreter.
- Join Data: Combine data from multiple tables using joins (Inner, Left, Right, Outer).
- Union Data: Stack data from multiple tables with the same structure.
3. Creating Views
- Drag & Drop: Drag fields from the Data pane onto Rows, Columns, or Marks to create visualizations.
- Show Me: Use the Show Me panel to select different visualization types.
4. Types of Visualizations
- Bar Chart: Compare values across categories.
- Line Chart: Display trends over time.
- Pie Chart: Show proportions of a whole (use sparingly).
- Map: Visualize geographic data.
- Scatter Plot: Show relationships between two variables.
5. Filters
- Dimension Filters: Filter data based on categorical values.
- Measure Filters: Filter data based on numerical values.
- Context Filters: Set a context for other filters to improve performance.
6. Calculated Fields
- Create calculated fields to derive new data:
- Example: Sales Growth = SUM([Sales]) - SUM([Previous Sales])
7. Parameters
- Use parameters to allow user input and control measures dynamically.
8. Formatting
- Format fonts, colors, borders, and lines using the Format pane for better visual appeal.
9. Dashboards
- Combine multiple sheets into a dashboard using the Dashboard tab.
- Use dashboard actions (filter, highlight, URL) to create interactivity.
10. Story Points
- Create a story to guide users through insights with narrative and visualizations.
11. Publishing & Sharing
- Publish dashboards to Tableau Server or Tableau Online for sharing and collaboration.
12. Export Options
- Export to PDF or image for offline use.
13. Keyboard Shortcuts
- Show/Hide Sidebar: Ctrl+Alt+T
- Duplicate Sheet: Ctrl + D
- Undo: Ctrl + Z
- Redo: Ctrl + Y
14. Performance Optimization
- Use extracts instead of live connections for faster performance.
- Optimize calculations and filters to improve dashboard loading times.
Tableau Learning Plan
https://t.me/dataanalysisresourcestp/84
7 Free Data Analytics Courses👇👇
https://tinyurl.com/326exaw7
Data Analyst Checklist
https://t.me/dataanalysisresourcestp/99
Hope it helps :)
Share our channel link with your friends:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
👍1
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𝗜𝗕𝗠 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 🚀💻
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- Data Science Fundamentals
- Introduction to Cloud
- Machine Learning with Python
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Enroll For FREE & Get Certified🎓
Remote Senior iOS Developer Job at Neybox Digital Ltd. (Limassol, Cyprus, EUROPE)
Job Location: Fully Remote (Worldwide)
🛠 What's the tech stack?
* Swift
Apply Here:
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#remotejobs
Job Location: Fully Remote (Worldwide)
🛠 What's the tech stack?
* Swift
Apply Here:
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#remotejobs
Master Data Science & Machine Learning
1️⃣ Basics of Data Science
🏷 Statistics and Probability
◾️ Statistics & Probability (https://www.khanacademy.org/math/statistics-probability)
🏷 Linear Algebra
◽️ Essence of Linear Algebra
(https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab)
🏷 Unlimited Resources
◽️ https://t.me/datascienceresourcestp
2️⃣ Programming Language
🏷 Python
◾️ Learn Python 3
(https://www.codecademy.com/learn/learn-python-3)
🏷 Unlimited Resources
◽️ https://t.me/pythonresourcestp
3️⃣ Data Analysis and Manipulation
🏷 Pandas Library
◾️ Pandas Documentation
(https://pandas.pydata.org/pandas-docs/stable/)🏷 Data Preparation with Pandas
◾️ Data Wrangling with Pandas
(https://realpython.com/pandas-dataframe/)🏷 NumPy Library
◾️ NumPy Documentation
(https://numpy.org/doc/stable/)4️⃣ Data Visualization
🏷 Matplotlib and Seaborn Library
◾️ Matplotlib (https://matplotlib.org/stable/users/index.html) / Seaborn (https://seaborn.pydata.org/)
🏷Tableau Public Platform
◾️ Tableau Public
(https://public.tableau.com/app/discover)5️⃣ Principles of Machine Learning
🏷 scikit-learn Library
◾️ scikit-learn
(https://scikit-learn.org/stable/index.html)
🏷 Unlimited Resources
◽️ https://t.me/dataanalysisresourcestp
6️⃣ Learning Algorithms
🏷 Hands-On Machine Learning Book
◾️ Hands-On ML
(https://t.me/mlresourcestp/19)
🏷 Unlimited Resources
◽️ https://t.me/techpsyche
7️⃣ Deep Learning
🏷 TensorFlow Library
◾️ TensorFlow Tutorial
(https://www.tensorflow.org/tutorials)
🏷 PyTorch Library
◾️ PyTorch Documentation
(https://pytorch.org/docs/stable/index.html)
🏷 Unlimited Resources
◽️ https://t.me/mlresourcestp
8️⃣ Big Data Technologies
🏷 Spark Framework Course
◾️ Spark Course
(https://www.youtube.com/watch?v=S2MUhGA3lEw)
🏷 Unlimited Resources
◽️ https://t.me/datascienceresourcestp
9️⃣ Advanced Topics
🏷 Natural Language Processing Course in Python
◾️ NLP in Python
(https://www.datacamp.com/courses/introduction-to-natural-language-processing-in-python)
🏷 Unlimited Resources
◽️ https://t.me/airesourcestp
1️⃣ Share Your Projects on Kaggle and GitHub
🏷 Kaggle Platform
◾️ Kaggle (https://www.kaggle.com/)
🏷 GitHub Platform
◾️ GitHub (https://github.com/)
Happy Learning! 🌟
Learn DatA & AI: https://365datascience.pxf.io/Z6KDgk
Free Notes & Books to learn Data Science: https://t.me/datascienceresourcestp
Python Project Ideas: https://t.me/pythonresourcestp/74
Best Resources to learn Data Science 👇👇
Python Tutorial (http://pythontutorial.net/)
Data Science Course (http://kaggle.com/learn) by Kaggle
Machine Learning Course (http://developers.google.com/machine-learning/crash-course) by Google
Best Data Science & Machine Learning Resources (https://topmate.io/learning_resources/1406977)
Interview Process for Data Science Role at Amazon (https://t.me/datascienceresourcestp/85)
Python Interview Resources (https://t.me/pythonresourcestp/40)
Join for more free courses
https://t.me/techpsyche
Like for more ❤️
ENJOY LEARNING👍👍
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
1️⃣ Basics of Data Science
🏷 Statistics and Probability
◾️ Statistics & Probability (https://www.khanacademy.org/math/statistics-probability)
🏷 Linear Algebra
◽️ Essence of Linear Algebra
(https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab)
🏷 Unlimited Resources
◽️ https://t.me/datascienceresourcestp
2️⃣ Programming Language
🏷 Python
◾️ Learn Python 3
(https://www.codecademy.com/learn/learn-python-3)
🏷 Unlimited Resources
◽️ https://t.me/pythonresourcestp
3️⃣ Data Analysis and Manipulation
🏷 Pandas Library
◾️ Pandas Documentation
(https://pandas.pydata.org/pandas-docs/stable/)🏷 Data Preparation with Pandas
◾️ Data Wrangling with Pandas
(https://realpython.com/pandas-dataframe/)🏷 NumPy Library
◾️ NumPy Documentation
(https://numpy.org/doc/stable/)4️⃣ Data Visualization
🏷 Matplotlib and Seaborn Library
◾️ Matplotlib (https://matplotlib.org/stable/users/index.html) / Seaborn (https://seaborn.pydata.org/)
🏷Tableau Public Platform
◾️ Tableau Public
(https://public.tableau.com/app/discover)5️⃣ Principles of Machine Learning
🏷 scikit-learn Library
◾️ scikit-learn
(https://scikit-learn.org/stable/index.html)
🏷 Unlimited Resources
◽️ https://t.me/dataanalysisresourcestp
6️⃣ Learning Algorithms
🏷 Hands-On Machine Learning Book
◾️ Hands-On ML
(https://t.me/mlresourcestp/19)
🏷 Unlimited Resources
◽️ https://t.me/techpsyche
7️⃣ Deep Learning
🏷 TensorFlow Library
◾️ TensorFlow Tutorial
(https://www.tensorflow.org/tutorials)
🏷 PyTorch Library
◾️ PyTorch Documentation
(https://pytorch.org/docs/stable/index.html)
🏷 Unlimited Resources
◽️ https://t.me/mlresourcestp
8️⃣ Big Data Technologies
🏷 Spark Framework Course
◾️ Spark Course
(https://www.youtube.com/watch?v=S2MUhGA3lEw)
🏷 Unlimited Resources
◽️ https://t.me/datascienceresourcestp
9️⃣ Advanced Topics
🏷 Natural Language Processing Course in Python
◾️ NLP in Python
(https://www.datacamp.com/courses/introduction-to-natural-language-processing-in-python)
🏷 Unlimited Resources
◽️ https://t.me/airesourcestp
1️⃣ Share Your Projects on Kaggle and GitHub
🏷 Kaggle Platform
◾️ Kaggle (https://www.kaggle.com/)
🏷 GitHub Platform
◾️ GitHub (https://github.com/)
Happy Learning! 🌟
Learn DatA & AI: https://365datascience.pxf.io/Z6KDgk
Free Notes & Books to learn Data Science: https://t.me/datascienceresourcestp
Python Project Ideas: https://t.me/pythonresourcestp/74
Best Resources to learn Data Science 👇👇
Python Tutorial (http://pythontutorial.net/)
Data Science Course (http://kaggle.com/learn) by Kaggle
Machine Learning Course (http://developers.google.com/machine-learning/crash-course) by Google
Best Data Science & Machine Learning Resources (https://topmate.io/learning_resources/1406977)
Interview Process for Data Science Role at Amazon (https://t.me/datascienceresourcestp/85)
Python Interview Resources (https://t.me/pythonresourcestp/40)
Join for more free courses
https://t.me/techpsyche
Like for more ❤️
ENJOY LEARNING👍👍
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
🔰List of Decompilers🔰
JVM-Based Languages
• Krakatau (https://github.com/Storyyeller/Krakatau) - the best decompiler I have used. Is able to decompile apps written in Scala and Kotlin into Java code. JD-GUI and Luyten have failed to do it fully.
• JD-GUI (https://github.com/java-decompiler/jd-gui)
• procyon (https://bitbucket.org/mstrobel/procyon/wiki/Java%20Decompiler)
◦ Luyten (https://github.com/deathmarine/Luyten) - one of the best, though a bit slow, hangs on some binaries and not very well maintained.
• JAD (http://varaneckas.com/jad/) - JAD Java Decompiler (closed-source, unmaintained)
• JADX (https://github.com/skylot/jadx) - a decompiler for Android apps. Not related to JAD.
.NET-Based Languages
◦ dotPeek (https://www.jetbrains.com/decompiler/) - a free-of-charge .NET decompiler from JetBrains
◦ ILSpy (https://github.com/icsharpcode/ILSpy/) - an open-source .NET assembly browser and decompiler
◦ dnSpy (https://github.com/0xd4d/dnSpy) - .NET assembly editor, decompiler, and debugger
Native Code
◦ Hopper (https://www.hopperapp.com/) - A OS X and Linux Disassembler/Decompiler for 32/64-bit Windows/Mac/Linux/iOS executables.
◦ cutter (https://github.com/radareorg/cutter) - a decompiler based on radare2.
◦ retdec (https://github.com/avast-tl/retdec)
◦ snowman (https://github.com/yegord/snowman)
◦ Hex-Rays (https://www.hex-rays.com/products/decompiler/)
Python
◦ uncompyle6 (https://github.com/rocky/python-uncompyle6) - decompiler for the over 20 releases and 20 years of CPython.
7 Free Courses by Udacity: https://t.me/techpsyche/633
ML Crash Course by Google
https://developers.google.com/machine-learning/crash-course
IBM Free Courses with Certification
https://tinyurl.com/42nau8jx
Passive Income Ideas for Developers
https://t.me/techpsyche/596
CISCO Free Certification Courses
https://bit.ly/4i9Kc9Z
ENJOY LEARNING 👍👍
Follow this WhatsApp Channel for More Resources
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
JVM-Based Languages
• Krakatau (https://github.com/Storyyeller/Krakatau) - the best decompiler I have used. Is able to decompile apps written in Scala and Kotlin into Java code. JD-GUI and Luyten have failed to do it fully.
• JD-GUI (https://github.com/java-decompiler/jd-gui)
• procyon (https://bitbucket.org/mstrobel/procyon/wiki/Java%20Decompiler)
◦ Luyten (https://github.com/deathmarine/Luyten) - one of the best, though a bit slow, hangs on some binaries and not very well maintained.
• JAD (http://varaneckas.com/jad/) - JAD Java Decompiler (closed-source, unmaintained)
• JADX (https://github.com/skylot/jadx) - a decompiler for Android apps. Not related to JAD.
.NET-Based Languages
◦ dotPeek (https://www.jetbrains.com/decompiler/) - a free-of-charge .NET decompiler from JetBrains
◦ ILSpy (https://github.com/icsharpcode/ILSpy/) - an open-source .NET assembly browser and decompiler
◦ dnSpy (https://github.com/0xd4d/dnSpy) - .NET assembly editor, decompiler, and debugger
Native Code
◦ Hopper (https://www.hopperapp.com/) - A OS X and Linux Disassembler/Decompiler for 32/64-bit Windows/Mac/Linux/iOS executables.
◦ cutter (https://github.com/radareorg/cutter) - a decompiler based on radare2.
◦ retdec (https://github.com/avast-tl/retdec)
◦ snowman (https://github.com/yegord/snowman)
◦ Hex-Rays (https://www.hex-rays.com/products/decompiler/)
Python
◦ uncompyle6 (https://github.com/rocky/python-uncompyle6) - decompiler for the over 20 releases and 20 years of CPython.
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Forwarded from SQL Resources TP
Practice these 5 intermediate SQL interview questions today!
1. Write a SQL query for cumulative sum of salary of each employee from Jan to July. (Column name – Emp_id, Month, Salary).
2. Write a SQL query to display year on year growth for each product. (Column name – transaction_id, Product_id, transaction_date, spend). Output will have year, product_id & yoy_growth.
3. Write a SQL query to find the numbers which consecutively occurs 3 times. (Column name – id, numbers)
4. Write a SQL query to find the days when temperature was higher than its previous dates. (Column name – Days, Temp)
5. Write a SQL query to find the nth highest salary from the table emp. (Column name – id, salary)
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Also try to apply what you learn through hands-on projects or challenges.
ENJOY LEARNING 👍👍
More Resources Here
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Like this post if you need more 👍❤️
Hope it helps :)
1. Write a SQL query for cumulative sum of salary of each employee from Jan to July. (Column name – Emp_id, Month, Salary).
2. Write a SQL query to display year on year growth for each product. (Column name – transaction_id, Product_id, transaction_date, spend). Output will have year, product_id & yoy_growth.
3. Write a SQL query to find the numbers which consecutively occurs 3 times. (Column name – id, numbers)
4. Write a SQL query to find the days when temperature was higher than its previous dates. (Column name – Days, Temp)
5. Write a SQL query to find the nth highest salary from the table emp. (Column name – id, salary)
SQL Relational Database Free Course Here: https://tinyurl.com/42nau8jx
Learn & Practice SQL (https://bit.ly/4kNb15x)
SQL Topics for Data Analysts (https://t.me/sqlresourcestp/83)
SQL Udacity Course (https://udacity.com/course/sql-for-data-analysis--ud198)
Download SQL Cheatsheet (https://t.me/sqlresourcestp/4)
Also try to apply what you learn through hands-on projects or challenges.
ENJOY LEARNING 👍👍
More Resources Here
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Like this post if you need more 👍❤️
Hope it helps :)
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Code Here https://t.me/pythonresourcestp/91?single
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Remote Webflow & Wordpress Developer Job at The Sher Agency(Texas, USA)
https://kenyatrends.co.ke/so8e
Remote Senior Backend Software Developer Job at Missive(Quebec, Canada)
https://kenyatrends.co.ke/x8a6
Remote Online English Teacher Job at Native Camp (Japan)
https://kenyatrends.co.ke/nbcg
Remote Senior iOS Developer Job at Neybox Digital Ltd. (Limassol, Cyprus, EUROPE)
https://kenyatrends.co.ke/bs6u
Remote Golang Engineer Job at Canonical, United Kingdom(UK)
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#remotejobs
🔰What is CTF? 🔰
CTF (Capture The Flag) is a kind of information security competition that challenges contestants to solve a variety of tasks ranging from a scavenger hunt on wikipedia to basic programming exercises, to hacking your way into a server to steal data. In these challenges, the contestant is usually asked to find a specific piece of text that may be hidden on the server or behind a webpage. This goal is called the flag, hence the name! Like many competitions, the skill level for CTFs varies between the events. Some are targeted towards professionals with experience operating on cyber security teams. These typically offer a large cash reward and can be held at a specific physical location.
How to Solve CTF: https://t.me/zerotrusthackers/76
CTF (Capture The Flag) is a kind of information security competition that challenges contestants to solve a variety of tasks ranging from a scavenger hunt on wikipedia to basic programming exercises, to hacking your way into a server to steal data. In these challenges, the contestant is usually asked to find a specific piece of text that may be hidden on the server or behind a webpage. This goal is called the flag, hence the name! Like many competitions, the skill level for CTFs varies between the events. Some are targeted towards professionals with experience operating on cyber security teams. These typically offer a large cash reward and can be held at a specific physical location.
How to Solve CTF: https://t.me/zerotrusthackers/76
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