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FAQ
Fax is an efficiency killer but survives. Why?
3 previous posts show the Question posed has a premise. Fax is not an efficiency killer - but can be far more efficient than Email FTP Messaging etc. via internet ... when the problem being posed is considered accurately. Single sender to single recipient spur of the moment need to transmit a document FAX is FAR MORE EFFICIENT. COST EFFICIENCY? Monetary Years ago - $.5-$.15 for phone line use was not unusual for domestic long distances. Today unlimited calling nationwide makes monetary costs difference zero. We have band to burn. Moderate latency costs Fax scanning and printing out same latency issues - break even with scanning and printing. Receiver can collect and store electronically if they do not wish hard copy same as scan. (stock trading - dead disadvantage notwithstanding) REALITY many businesses still have manual workflow. Hardcopy is integral to their model of business. FAX is far more efficient for moderate sized docs sent infrequently between a small business and large number of customers from a large population of infrequent customers. A physical Faxed Doc sitting in a output bin is also a visual cue spurring action for office workers away from their desks. People and processes still exist in the physical domain from time to time during a well designed work day! Privacy Doctor's office insisted on fax transmission and they could not (would not) receive a scanned doc via email. HIPPA rules on privacypliance concerns? HIPAA Compliance Tips for Medical Practices Or is it just arcane reality of a dying breed? As long as workflow remains in the physical domain FAX can be safer and sometimes far more efficient. For the time being FAX machines will persist. nThere is an entire market segment set up around fax services through email. These will curiously persist well beyond physical fax machines disappearing ... Then the QUORA posted question will ask Why do inefficient FAX protocols persist after the last fax machine went out ofmission? Inertia - what a concept.
What are the main tools that I should use during a CTF contest in all categories?
Tools used for solving CTF challenges italic Attacks Tools used for performing various kinds of attacks italic Bettercap s - Framework to perform MITM (Man in the Middle) attacks. Layer 2 attacks s - Attack various protocols on layer 2 Crypto Tools used for solving Crypto challenges italic FeatherDuster s - An automated modular cryptanalysis tool PkCrack s~conrad - A tool for Breaking PkZip-encryption RSATool s - Generate private key with knowledge of p and q XORTool s - A tool to analyze multi-byte xor cipher Bruteforcers Tools used for various kind of bruteforcing (passwords etc.) italic Hashcat s - Password Cracker John The Jumbo s - Community enhanced version of John the Ripper John The Ripper - Password Cracker Ophcrack - Windows password cracker based on rainbow tables. Exploits Tools used for solving Exploits challenges italic DLLInjector s - Inject dlls in processes libformatstr s - Simplify format string exploitation. Metasploit - Penetration testing software Pwntools s - CTF Framework for writing exploits Qira s - QEMU Interactive Runtime Analyser ROP Gadget s - Framework for ROP exploitation Vlt s - Security CTF Toolkit Forensics Tools used for solving Forensics challenges italic Aircrack-Ng - Crack WEP and WPA-PSK keys apt-get install aircrack-ng code Audacity - Analyze sound files (mp3 m4a whatever) apt-get install audacity code Bkhive and Samdump2 - Dump SYSTEM and SAM files apt-get install samdump2 bkhive code CFF Explorer - PE Editor Creddump s - Dump windows credentials DVCS Ripper s - Rips web accessible (distributed) version control systems Exif Tool ~phil - Read write and edit file metadata Extundelete - Used for recovering lost data from mountable s. Boomerang s - Dpile x86 binaries to C ctf_import s 3 run basic functions from stripped binaries cross platform GDB s - The GNU project debugger GEF s - GDB plugin Hopper - Reverse engineering tool (disassembler) for OSX and Linux IDA Pro s - Most used Reversing software Jadx s - Dpile Android files Java Dpilers - An online dpiler for Java and Android APKs Krakatau s - Java dpiler and disassembler PEDA s - GDB plugin (only python2.7) Plasma s - An interactive disassembler for x86 which can generate ed pseudo-code with colored syntax. Pwndbg s - A GDB plugin that provides a suite of utilities to hack around GDB easily. radare2 s - A portable reversing framework Upyle s - Dpile Python 2.7 binaries (.pyc) WinDbg - Windows debugger distributed by Microsoft Z3 s - a theorem prover from Microsoft Research JavaScript Deobfustcators italic Detox - A Javascript malware analysis tool Revelo - Analyze obfuscated Javascript code SWF Analyzers italic RABCDAsm s - Collection of utilities including an ActionScript 3 assembler Swftools - Collection of utilities to work with SWF files Xxxswf s - A Python script for analyzing Flash files. Services Various kind of useful services available around the internet italic CSWSH - Cross-Site WebSocket Hijacking Tester Request Bin - Lets you inspect requests to a particular Steganography Tools used for solving Steganography challenges italic Convert b formats and apply filters Exif - Shows EXIF information in JPEG files Exiftool s - Read and write meta information in files Exiv2 - Image metadata manipulation tool ImageMagick Outguess s - Universal steganographic tool Pngtools - For various analysis related to PNGs apt-get install pngtools code SmartDeblur s - Used to deblur and fix defocused Steghide - Hide data in various kind of s Web Tools used for solving Web challenges italic Commix s - Automated All-in-One OS Command Injection and Exploitation Tool. Hackbar s - Firefox addon for easy web exploitation OWASP ZAP s - Intercepting proxy to replay debug and fuzz HTTP requests and responses Postman s - Add on for chrome for debugging network requests SQLMap s - Automatic SQL injection and database takeover tooli W3af s - Web Application Attack and Audit Framework. XSSer - Automated XSS testor
What are some interesting summer programming projects that one can do?
If you are interested in applied math a little and where it relates to CS (e.g.puter graphicsputational science optimization AI) you could try implementing some canonical problems in these areas. I think it's a good idea for people to learn math. What's better is that you have a way of learning it that others may not--through programming a solution. Even better you get to see how other people did it too. More importantly mathematical literacy shows a great skill that people who know anything about anything will see as a plus so put it on GitHub. Here are some things Code up a Newton-Raphson gradient descent simulated annealing or genetic algorithm methods for optimization Write a simple diffusion equation solver on a flat 2D (or 1D) grid Implement k-means clustering some simple Markov model or linear SVM (you can cheat here a little and just use some optimization libraries) Write up a Fourier transform routine then do the fast Fourier transform. Or Walsch-Hadamard whatever. Write a simple linear algebra library (i.e. addition matrix-matrix matrix-vector multiplication inner and outer products tensor products matrix inversion solving linear systems and really however far you want to go with it. if you're really into it try eigendposition or variations on these other methods for particular matrices.. if you've gone this far would be advisable to pick up a numerical linear algebra book) Write a simple quantum circuit simulator (initial state apply gates (read operators) to it check results) and implement some basic cool algorithms. Might want to pick up a book on this but not necessary. n ** Bonus points if you do a multithreaded distributed memory GPU or low-level optimized (e.g. SSE) implementation. I think that would be a good thing for anyone to see. And don't forget to put it on your GitHub dammit! I think this is a great chance to get acclimated with mathematics. Lots of people use the above things or moreplicated versions of them. Math is all the same in your head you just need to start somewhere. Once you know how to reason about a Fourier transform you might further understand how to solve certain ODEs or if you understand eigendposition you might understand dimensionality reduction in ML. From there you can build towards a good understanding of mathematics and how you can exploit it in your everyday problems. Good luck! If you decide to tackle any of these problems feel free toment for books or further resources.