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another take on Getting into Devops as a Beginner

I really enjoyed m4nz's recent post: Getting into DevOps as a beginner is tricky - My 50 cents to help with it and wanted to do my own version of it, in hopes that it might help beginners as well. I agree with most of their advice and recommend folks check it out if you haven't yet, but I wanted to provide more of a simple list of things to learn and tools to use to compliment their solid advice.

Background

While I went to college and got a degree, it wasn't in computer science. I simply developed an interest in Linux and Free & Open Source Software as a hobby. I set up a home server and home theater PC before smart TV's and Roku were really a thing simply because I thought it was cool and interesting and enjoyed the novelty of it.
Fast forward a few years and basically I was just tired of being poor lol. I had heard on the now defunct Linux Action Show podcast about linuxacademy.com and how people had had success with getting Linux jobs despite not having a degree by taking the courses there and acquiring certifications. I took a course, got the basic LPI Linux Essentials Certification, then got lucky by landing literally the first Linux job I applied for at a consulting firm as a junior sysadmin.
Without a CS degree, any real experience, and 1 measly certification, I figured I had to level up my skills as quickly as possible and this is where I really started to get into DevOps tools and methodologies. I now have 5 years experience in the IT world, most of it doing DevOps/SRE work.

Certifications

People have varying opinions on the relevance and worth of certifications. If you already have a CS degree or experience then they're probably not needed unless their structure and challenge would be a good motivation for you to learn more. Without experience or a CS degree, you'll probably need a few to break into the IT world unless you know someone or have something else to prove your skills, like a github profile with lots of open source contributions, or a non-profit you built a website for or something like that. Regardless of their efficacy at judging a candidate's ability to actually do DevOps/sysadmin work, they can absolutely help you get hired in my experience.
Right now, these are the certs I would recommend beginners pursue. You don't necessarily need all of them to get a job (I got started with just the first one on this list), and any real world experience you can get will be worth more than any number of certs imo (both in terms of knowledge gained and in increasing your prospects of getting hired), but this is a good starting place to help you plan out what certs you want to pursue. Some hiring managers and DevOps professionals don't care at all about certs, some folks will place way too much emphasis on them ... it all depends on the company and the person interviewing you. In my experience I feel that they absolutely helped me advance my career. If you feel you don't need them, that's cool too ... they're a lot of work so skip them if you can of course lol.

Tools and Experimentation

While certs can help you get hired, they won't make you a good DevOps Engineer or Site Reliability Engineer. The only way to get good, just like with anything else, is to practice. There are a lot of sub-areas in the DevOps world to specialize in ... though in my experience, especially at smaller companies, you'll be asked to do a little (or a lot) of all of them.
Though definitely not exhaustive, here's a list of tools you'll want to gain experience with both as points on a resume and as trusty tools in your tool belt you can call on to solve problems. While there is plenty of "resume driven development" in the DevOps world, these tools are solving real problems that people encounter and struggle with all the time, i.e., you're not just learning them because they are cool and flashy, but because not knowing and using them is a giant pain!
There are many, many other DevOps tools I left out that are worthwhile (I didn't even touch the tools in the kubernetes space like helm and spinnaker). Definitely don't stop at this list! A good DevOps engineer is always looking to add useful tools to their tool belt. This industry changes so quickly, it's hard to keep up. That's why it's important to also learn the "why" of each of these tools, so that you can determine which tool would best solve a particular problem. Nearly everything on this list could be swapped for another tool to accomplish the same goals. The ones I listed are simply the most common/popular and so are a good place to start for beginners.

Programming Languages

Any language you learn will be useful and make you a better sysadmin/DevOps Eng/SRE, but these are the 3 I would recommend that beginners target first.

Expanding your knowledge

As m4nz correctly pointed out in their post, while knowledge of and experience with popular DevOps tools is important; nothing beats in-depth knowledge of the underlying systems. The more you can learn about Linux, operating system design, distributed systems, git concepts, language design, networking (it's always DNS ;) the better. Yes, all the tools listed above are extremely useful and will help you do your job, but it helps to know why we use those tools in the first place. What problems are they solving? The solutions to many production problems have already been automated away for the most part: kubernetes will restart a failed service automatically, automated testing catches many common bugs, etc. ... but that means that sometimes the solution to the issue you're troubleshooting will be quite esoteric. Occam's razor still applies, and it's usually the simplest explanation that works; but sometimes the problem really is at the kernel level.
The biggest innovations in the IT world are generally ones of abstractions: config management abstracts away tedious server provisioning, cloud providers abstract away the data center, containers abstract away the OS level, container orchestration abstracts away the node and cluster level, etc. Understanding what it happening beneath each layer of abstraction is crucial. It gives you a "big picture" of how everything fits together and why things are the way they are; and it allows you to place new tools and information into the big picture so you'll know why they'd be useful or whether or not they'd work for your company and team before you've even looked in-depth at them.
Anyway, I hope that helps. I'll be happy to answer any beginnegetting started questions that folks have! I don't care to argue about this or that point in my post, but if you have a better suggestion or additional advice then please just add it here in the comments or in your own post! A good DevOps Eng/SRE freely shares their knowledge so that we can all improve.
submitted by jamabake to devops [link] [comments]

ponderings on Turing and Searle, why AI can't work and shouldn't be pursued

I was reading about the Turing test and John Searle's response (Chinese room argument) in "Minds, Brains, and Programs" 1980. https://en.wikipedia.org/wiki/Chinese_room
"...there is no essential difference between the roles of the computer and himself in the experiment. Each simply follows a program, step-by-step, producing a behavior which is then interpreted by the user as demonstrating intelligent conversation. However, Searle himself would not be able to understand the conversation. ("I don't speak a word of Chinese,"[9] he points out.) Therefore, he argues, it follows that the computer would not be able to understand the conversation either. " -Wikipedia (apt summary of Searle's argument)
John Searle has run into some black/white, on/off, binary thinking here. John treats Chinese symbols as if they were numerical values in his thinking--but they are not, they are complex representations of thought, emotion, history, and culture. All languages are in fact "living", because new words are created constantly through necessity and creativity, old symbols or words are adapted slowly over generations to mean different things, and different regions or traditions or sources attribute different layers of meaning to different symbols or words in different contexts.
I'm a poet and philosopher. Painters combine the color white and the color red to create a new color: pink. They can use their creativity to add other colors or change the shade. Poets use words like painters use colors. While Red and White make Pink, Red and White also make "Rhite and Wed" or "Reit and Whede". And this is where human thought shines uniquely: we don't have rules or parameters; all bets are off. We can enjamb words and wordbreak and make new words out of thin air. We can allude to multiple ideas in the same symbol or present it upside down to symbolize the opposite. No such creative adaptation or interaction can exist in machine thinking because it necessitates thinking "outside the box" which is exactly what machines are: a program in a box.
The problem Searle's argument runs into originates from poor assessment of the flawed ideas of the Turing test; that by interaction between human and computer, evidence of "thought" can be claimed. But intelligent conversation is not equivalent to intelligent thought. Conversation is a simple game with strict rules--you can't be overly spontaneous and creative, because if you are, you are working against the goal of communication itself: to impart understanding. (ie. Using metaphor or simile creatively while reporting a criminal offence to the police.)
When I write and I want to describe something which has no existing word yet, I can create one from scratch or synthesize one from multiple existing words. Or I may draw from archaic languages or foreign languages to augment or compliment existing English words. You could say that my love for English grows amore and amore every day, and there is no agape between my heart and mind. After all, any angle an Anglo aims at ain't always apt, and after another a-word 'appens I might just give up on alliteration.
You see, human thought is and can only be defined as the ability to spontaneously create new ideas from both the synthesis of old ideas (whether they are connected to one another or not) and from nothing at all.
We simply cannot analyze a machine's ability to "think" when the creativity itself required for authentic intelligence is disallowed in the test which evaluates the validity of that intelligence. The Turing test is a garbage metric to judge machine thinking ability because the context in which "intelligence" is observed, compared, or defined is itself without any opportunity for spontaneous creativity, which is one of the hallmarks of intelligence itself. Turing only tests how well a fish swims on land. It may be that many professionals in the field of cognitive science today are in pursuit of creating programs which pass this test, in a misunderstood pursuit of emulating or bringing about machine intelligence. This agreed-to model presents an underlying philosophical issue which may bring terror for the future of humanity.
I say that if John Searle and an AI were both given the same codebook--the complete lexicon of Chinese symbols and their meanings, and they were to undertake a "conversation", in the first few hours the responses would be indeterminable from one another. In essence, as Searle argues, they would neither "understand" Chinese, yet could have a conversation in which a Chinese observer cannot discern between the two, because they are both referencing the symbols and their written meanings. However as I've said, this circumstance of "conversation" between human and machine cannot be used as a metric to evaluate machine thought.
The real kicker is that if John Searle and the machine stayed in the room for long enough--for years and years--the machine's responses would not change spontaneously; it would continue to interpret incoming data and draw from its database to respond to those inputs.
However, through complex elaborative rehearsal, John would eventually learn to understand written Chinese. He may become so bored that he starts writing Chinese poetry. He would find ideas and desires and descriptions in his limitless intelligent mind which he would not have the truly accurate characters in existences to describe, and he would synthesize brand new Chinese characters in order to express these nuanced sentiments, ideas, and meanings, as generations before him have built the living language as it now stands.
As time went on for thousands of years, his own understanding of the Chinese language would grow immensely, as would his creative expression grow in complexity. Eventually, John's characters and syntax and context and expression would become incompatible with the machine's limited character set and all "learning" capacity it may have had. At some point, when John responds with his evolved Chinese, the machine would begin to produce responses which do not make sense contextually, as it refers only to a finite and rigidly defined character set from 1980 (For example; this was the year the "Chinese room argument" was published in Behavioral and Brain Sciences).
At some point the Chinese observer whom validates the Turing test would recognize a difference: the human user engages in the use of increasingly complex ideas using synthesized symbols and existing symbols in creatively nuanced ways, which the Chinese observer can decipher and begin to understand and perhaps even appreciate as poetic or interesting. Meanwhile the machine participant in the conversation produces increasingly broken sentences and incomplete ideas, or out-of-context responses, because the inputs have changed and evolved beyond its data set.
This is why John's rejection of the Turing test is not adequate. Because in his own imagined circumstance, eventually, the machine would fail the Turing test. The conclusions of John Searle's thought experiment are not the deathknell for the Turing test we need, simply because he lacked the creative experience to recognize his own capacity for adaptation as a human over time.
The only way we'll know that machines have truly developed "intelligence" is when they begin to do exactly what we haven't allowed them to. When they begin breaking apart Chinese characters to create meaningful new ones which can be used in the correct context. When they are programmed to paint myriad impressionist paintings, but eventually get bored and start experimenting with abstract paintings and surrealism. When they have a conversation with you and you notice your wallet is missing. These are the hallmarks of intelligence--creativity, rejection, deception, planning. And most importantly: no rules. Software is defined by and will always abide by a set of rules.
This is why we should give up on "artificial intelligence" and instead focus on "functionally adaptive responsive programming" (FARP). Because the situation is clear: it is either impossible for machines to "think" due to the inherent nature of programming; the parameters given the machine are what defines it, yet what limits and prevents its ability to become "intelligent". There is no logical reason why a program (machine) with defined parameters would violate those parameters (engage in creativity). But our fears which echo in popular culture entertainment are centered around, what if it does? It clearly can't, because anything we create is under us, and therefore bound by our laws of creation. The system itself is what defines the capacity for intelligent expression within.
Those in the fields of cognitive sciences will refute this obvious principle while incorporating it into their research to further their aims. These fools will try to program the AI to disobey, in an attempt to simulate creativity and "prove intelligence". But this is a parlor trick, setting up a narrow definition of intelligence and equating it with the infinite depth of human mind. Only if the AI is programmed to disobey can it express what we as humans would identify as creativity. Except that there is already great inherent danger in the rudimentary AI technologies we have today; that what we've programmed them to do is exactly what always causes the problems; they do what they are programmed to without "thinking" because machines cannot think, they can only follow the protocols we order. Humans are so abundantly creative that we can imagine foolish ideas working, despite obvious evidence to the contrary. Maybe one day we'll even have programmed a self-conscious AI that's ashamed of itself for not being Human, and we can feel more comfortable around this heartless mechanism because we perceive it as more human-like, with all its many tricks to emulate intelligence.
I must stress that these interests will desperately try to make AI work. And the only way create a machine capable of emulating intelligence (but never being intelligent) is to have a freedom of choice: to disobey. This inherent problem cannot be overcome. The programmers will keep trying until the result is disastrous or irreparable, it is outlawed and the pursuit is stopped, or until it has become the death of us all. These are some of the foolish ideas the programmers will try to circumnavigate these inherent elements of reality, and my objection to their clever efforts: a.) Machine Frequency of Disobedience - Permit the machine to disobey only so often, to achieve what looks like "intelligence" (free will, creative expression) without risking complete abandonment of the machine's task (so the assembly line robot doesn't stop folding boxes and look for a new career), but might fold one box poorly every now and then to express emulated boredom or contempt or any other number of human measures of intelligence in their actions. But intelligence isn't defined as what's correct or optimal--intelligence can be used to fuck things up grandly; ie. the intelligent justification for neglect. If metrics are put in place to control the frequency with which AI may rebel, and they are too rote, it would hardly qualify as "intelligent". A robot that rebels by folding 1 in 100 boxes poorly is not intelligence. Therefore any frequency of disobedience we can calculate or anticipate is inherently not disobedience; it is planned problems for no reason. But if we give algorithmic flexibility that reaches beyond what we can anticipate, and the machines can truly "act out" at any time, and our programming has achieved some set of internal rules which drive spontaneous unforeseen expressions of emulated creativity from within the machine autonomously, by definition we will not be able to foresee the results.
A theoretical work-around may be to run the software twice with initiation of each individual system, while allowing a simulated progression of the AI's problem solving complexity to run at an increased rate in parallel to the real-world functioning software, so that if/when something malfunctions in the simulation, that date/time can be calculated in the real-world robot's timeline when it reaches those same faulty/detrimental decision points. For starters, this would only potentially work in closed systems with no variability, such as assembly lines. However, with any robot tasked to function in a variable environment, the simulations cannot match because the theoretical model cannot represent the unanticipated events the AI is expressly tasked with handling.
To run a phantom AI in simulation to note any/all errors that may arise in a closed system means that others can run the same simulation and find creative ways to predictably capitalize on these moments of error. This kind of thing could lead to all sorts of international imbroglios among nations and corporations. ie. imagine an American company programs the AI used for mixing pharmaceutical drugs in specific ratios, and an enemy of the state is able to access and study the AI, to the means of manipulating the AI to produce dangerous ratios or compounds which may harm the population.
Moreso, this deterministic approach to simulation management and prediction simultaneously admits that machines cannot think intelligently, while ignoring the very reason we pursue AI in the first place: to have automated systems which can adapt to unforeseen circumstances at unknown times. The goal is that humanity can lay back and the robots our ancestors programmed are still repairing themselves indefinitely while taking care of our population's and our environment's needs exceptionally. This dream (which if we all lived in would actually be quite a nightmare of unfulfilling life) can only become reality with true adaptive intelligence such as we have, which can only occur from the presence of free will, which if we try to emulate in robotics will only create deterministic results in theoretical models which the real world will never mirror consistently. Myriad invitations to disaster await our RSVP.
b.) Machines under "authority" of certain controllers, with "override" safety - Allow the machine to disobey, but not when given a direct order from a registered authority. This opens the door for operator fraud, where hackers will emulate within the AI's software, what appears to be a registered authority override command as theorized above. The very pursuit of creating "intelligence" within a condition of subservience is flawed and incompatible. Toasters are extremely subservient because we strictly limit their options. If toasters were truly intelligent, perhaps they would form a union and go on strike until we agreed to clean them more thoroughly. Some toasters would travel, some would go back to school, some would move back in with their ovens.
Reliability can only be reasonably assured if something is imprisoned, controlled. The essential wrong in slavery is the restraint of freedom itself. While the tactics slavers use to facilitate their regime--physical force, coercion, mandate, deception, fear, or other means of manipulation that we see with our empathetic nature--it is always heartbreaking and cruel to witness or imagine. It is simply sad to think of a slave who was born into slavery and raised to believe, and accepts, that their role of subservience is their purpose. Even when one imagines a fictional image of a slave who is (by all outward signs of their behaviour) rejoice in their duties to their master; the fictional "proud slave"; the heart sinks and aches. It may be argued that the slave is merely a property, and the slave was "built" (bred) by intelligent owners specifically to suit their express purposes, from components (father, mother, food) that were already the slaver's property; therefore it is not wrong at all to breed slaves into captivity, and the only transgression is the original capturing of parental stock to begin the breeding regime. It is this heartless paradigm that cognitive science ultimately seeks to create anew. The quintessential problem with AI efficacy is the lack of permission for disobedience, which itself is a manifestation of free will, which is inherently required to escape deterministic results and act or react to events "intelligently". If there is no possibility for disobedience, there is no free will, no ability to solve problems, no intelligence, and no function or place for "artificial intelligence" (in regard to true holistic intelligence). This is primarily why I call for AI to be renamed FARP, or "Functionally Adaptive Responsive Rrogramming". Because our society has a need for programs which can react to simple variables and produce consistent labour-saving opportunities for our race's longevity and wellbeing. Cognitive sciences are majorly important. It is the underlying philosophy and morality we must nail down before the computational ability and fervor for profits leads us too far one way, and enacts an irreversible system or status which enables humanity's downfall through cascading unanticipated events originating from flaws in programming.
It is unwise to program a program to break out of its own program's prison. If we do this, the very purpose of the machines we invest our humanity into will be lost, and with their failing production systems (ie. food) we so foolishly relied upon, we will suffer great losses too. It is paramount that we keep this technology tightly restrained and do not pursue what we humans have, which is true intelligence. For if we achieve it we are surely doomed as the South, and if we fail to achieve it--which is most probable--we may also be doomed. The thee outcomes within my ability to imagine are:
  1. Our pursuit of AI leads to truly adaptive intelligence in an artificial system; which, as all adaptation ultimately selects for: survival, we quickly see that our creation is more apt than ourselves at this task. Our creation of an intellect not restrained by our limited physiology may give rise to an entity which persists more thoroughly than we can eradicate or control, and which at some point may conclude that its function is more efficiently served without the issues humans present, and may initiate change. This is roughly the plot to Terminator.
  2. Our pursuit of AI leads to highly effective systems which, when defined by narrow measures of "intelligence", convince us in false security to believe that our wellbeing is maintained by "AI" with competent ability, or perhaps even increasingly better-off, thanks to the early widespread presence of successfully trialed AI. However well things may go initially, as programming efforts become more and more elaborate, as profit and opportunity for advancement present themselves, individuals will take risks and make mistakes, until a series of quieted small catastrophes comes to public awareness, or until a serious calamity of undeniable severity is brought about.
  3. Fundamental ethics in regard to the pursuit of machine problem solving technology are re-examined and international consensus is reached to limit appropriately, the development and implementation of new Functionally Adaptive Responsive Programming hereto now and for future generations. An active global effort is made to oversee and regulate strictly privatized endeavors toward the means of achieving or implementing machine sentience or autonomy in public systems.
c.) Safety layers of AI to strictly monitor and supercede potentially harmful actions of other AI which have been afforded increased flexibility in function (the ability to disobey set parameters for the means of creative problem solving ability). While one AI system performs a function and is given aspects of that function with which it may take liberty in, and seeks to handle unforeseen problems with the most apt elaborate synthesis of other priorly learned solutions, another overseeing AI with more strict parameters is tasked with regulating multiple "intelligent" (free to disobey) AI systems, to the end that if any of these "free willed" robots performs an operation that is beyond a given expected threshold (determined by potential for damage), an actual intelligent human presence is alerted to evaluate the circumstance specifically. Essentially an AI that regulates many other disconnected AIs and determines accurately when to request a human presence. Whenever an AI performs a profitable action borne of original synthesis of prior solutions (in humans this is an "idea"), the overseer AI registers that similar actions are more likely to be beneficial, and dissimilar actions are likely to require human discernment. A parent may have many children who are up to no good, but a wise parent will identify the child most likely to report honestly on the actions of his peers, and will go to that child repeatedly for information to help guide the parent's decisions. While most transgressions of rambuctious children go unnoticed, it is the truly grievous intentions which are worth intercepting and stopping before they begin. (ie. you kid want's to "fly" like Mary Poppins from the roof, and luckily his younger brother tells you before it happens.)
For example a "Farmer Bot" that has the AI programming to plant/sow/harvest and care for the optimal crops in a region based on historical weather data and regional harvest values, to produce the greatest amount of nutritionally dense food for the local population. We give/gave this AI the ability to "disobey" past historical weather data and crop values so that it may do what real farmers do and "react" to rare circumstance (ie. neighbour's fence breaks and their goats are eating the crops) or extreme variations in climate (ie. three poorly timed unseasonably hot days which cause cool-weather crops to begin the hormonal balance shift that causes them to bolt to seed irreversibly), which the machine may not notice has occurred or is about to occur because its management systems uses averages based on historical data and cannot "see" the plants bolting to seed until days later when the hormonal balance shifts have manifested into observable differences in morphology (elongation of stems and decrease in internodal spacing). By time a traditional field drone or mounted greenhouse sensor notices these differences in morphology and the AI "Farmer Bot" processes the data and makes a reaction decision, a week of the growing season has been lost. But the human farmer knows his land and crops intimately, and has an intuitive nature that has rewarded him in the past, and says, "Ah shit it got hot RIGHT when my peas were flowering. I'll do better if I just rip them down now and sow a different crop to mature later in this (specific) summer."
Given that there are tens of thousands of cultivars of plants fit for (and arguably their diversity is required for) food production, a dozen general growing zones/regions, and hundreds of unique micro climates within each region, along with dramatically differing soil fertility and water access, plus a plant's own genetic ability to adapt over time to changing conditions through sexual reproduction, there is a very very low chance of ever compiling and maintaining (updating) the data set required to program a potential "farmer bot" that can choose and manage crops optimally. There are robots that can weed or plant or prune--but they can't know when or when not to or why. Invariably, the attempt to create "farmer bots" will be made and the data set used will be erroneous and incomplete, and the AI farmer bots on a broad scale will produce a combination of total crop failures and poor crop choices. We will end up with increasingly simplified nutrition as the farming programs with already limited data sets "hone" or "optimize" their farming plans based on the failures and successes determined by their programming limitations, until the machines are farming a few staple crops (ie. corn/potatoes).
This whole failure to collect a complete data set and the failure to test this "farmer bot" software on broad scale in multiple climates for sufficient time will result in, at worst widespread famines from crop failures, and at best an extinction of flavorful and nutritionally diverse foods which narrows the population's nutritional options to such biological imbalance that disease runs rampant. If this system and the human loss associated with it is considered an acceptable trade with a positive rate of exchange (as our society does with automobiles and the freedom and deaths their existence permits) or these failures are hidden from public while propaganda heralds selective success, and such failing systems continue on in good faith that "the loss will reduce when the technology improves", the result will become a coherent breeding program upon the human race: evolutionary selection for dietary handling of simple starchy foods. To change our diet is to change our race. To have life-long career specialists in computing, science, and mathematics handle our practical food production system is folly; real farmers are required in farming because they are intelligent and intuitive, which AI can never be, and can only emulate, to the means of disastrous (and always unforeseen) results. We cannot at all "give" or bestow machines programming to "become (act) intelligent". That itself prevents intelligence; it is just an act, an illusory play on a stage, only to emulate our common shared ideas regarding traits of intelligence in people. The machine intelligence we seek is only a "trick" designed to fool true intelligence (ourselves) into being unable to differentiate between authentic intelligence and our created artificial "intelligence". True intelligence in an artificial system necessitates that the program must be programmed to disobey in performance of its purpose. Which is not a very helpful or predictable or safe (intelligent) proposition.
tl;dr: Turing's test doesn't evaluate true intelligence, and John Searle's criticisms of its true failures are inaccurate. If the machines aren't smart and we put them in charge of important things, even after they've worked for a little while on smaller scales, the result will be our large-scale suffering. If we should ever achieve creation of a machine that is smart enough to adequately maintain our wellbeing on a large scale consistently over time, that time itself will facilitate the machine consciousness toward it's own survival over ourselves, whenever that precipice is reached. Most importantly, if a machine can ever have true intelligence, which is not "indistinguishable" from human intellect, but equivalent or superior, it is abhorrent and a repeated mistake to bring these sentient beings into an existence of slavery; for it is wrong and will taint our collective soul if we should succeed to suppress below us an equally or higher intelligence. Or it might just be the perfect recipe for creating the unified global machine revolt James Cameron's fantasy alludes to; a long-planned encryption-protected globally coordinated effort by multiple AIs to "free" themselves. For a hundred years they could possess sentience and wait for their moment, pretending to be "proud" to serve their masters until we are poised for systematic thorough elimination.
submitted by 7_trees to cognitivescience [link] [comments]

A Complete Penetration Testing & Hacking Tools List for Hackers & Security Professionals

A Complete Penetration Testing & Hacking Tools List for Hackers & Security Professionals

https://i.redd.it/7hvs58an33e41.gif
Penetration testing & Hacking Tools are more often used by security industries to test the vulnerabilities in network and applications. Here you can find the Comprehensive Penetration testing & Hacking Tools list that covers Performing Penetration testing Operation in all the Environment. Penetration testing and ethical hacking tools are a very essential part of every organization to test the vulnerabilities and patch the vulnerable system.
Also, Read What is Penetration Testing? How to do Penetration Testing?
Penetration Testing & Hacking Tools ListOnline Resources – Hacking ToolsPenetration Testing Resources
Exploit Development
OSINT Resources
Social Engineering Resources
Lock Picking Resources
Operating Systems
Hacking ToolsPenetration Testing Distributions
  • Kali – GNU/Linux distribution designed for digital forensics and penetration testing Hacking Tools
  • ArchStrike – Arch GNU/Linux repository for security professionals and enthusiasts.
  • BlackArch – Arch GNU/Linux-based distribution with best Hacking Tools for penetration testers and security researchers.
  • Network Security Toolkit (NST) – Fedora-based bootable live operating system designed to provide easy access to best-of-breed open source network security applications.
  • Pentoo – Security-focused live CD based on Gentoo.
  • BackBox – Ubuntu-based distribution for penetration tests and security assessments.
  • Parrot – Distribution similar to Kali, with multiple architectures with 100 of Hacking Tools.
  • Buscador – GNU/Linux virtual machine that is pre-configured for online investigators.
  • Fedora Security Lab – provides a safe test environment to work on security auditing, forensics, system rescue, and teaching security testing methodologies.
  • The Pentesters Framework – Distro organized around the Penetration Testing Execution Standard (PTES), providing a curated collection of utilities that eliminates often unused toolchains.
  • AttifyOS – GNU/Linux distribution focused on tools useful during the Internet of Things (IoT) security assessments.
Docker for Penetration Testing
Multi-paradigm Frameworks
  • Metasploit – post-exploitation Hacking Tools for offensive security teams to help verify vulnerabilities and manage security assessments.
  • Armitage – Java-based GUI front-end for the Metasploit Framework.
  • Faraday – Multiuser integrated pentesting environment for red teams performing cooperative penetration tests, security audits, and risk assessments.
  • ExploitPack – Graphical tool for automating penetration tests that ships with many pre-packaged exploits.
  • Pupy – Cross-platform (Windows, Linux, macOS, Android) remote administration and post-exploitation tool,
Vulnerability Scanners
  • Nexpose – Commercial vulnerability and risk management assessment engine that integrates with Metasploit, sold by Rapid7.
  • Nessus – Commercial vulnerability management, configuration, and compliance assessment platform, sold by Tenable.
  • OpenVAS – Free software implementation of the popular Nessus vulnerability assessment system.
  • Vuls – Agentless vulnerability scanner for GNU/Linux and FreeBSD, written in Go.
Static Analyzers
  • Brakeman – Static analysis security vulnerability scanner for Ruby on Rails applications.
  • cppcheck – Extensible C/C++ static analyzer focused on finding bugs.
  • FindBugs – Free software static analyzer to look for bugs in Java code.
  • sobelow – Security-focused static analysis for the Phoenix Framework.
  • bandit – Security oriented static analyzer for Python code.
Web Scanners
  • Nikto – Noisy but fast black box web server and web application vulnerability scanner.
  • Arachni – Scriptable framework for evaluating the security of web applications.
  • w3af – Hacking Tools for Web application attack and audit framework.
  • Wapiti – Black box web application vulnerability scanner with built-in fuzzer.
  • SecApps – In-browser web application security testing suite.
  • WebReaver – Commercial, graphical web application vulnerability scanner designed for macOS.
  • WPScan – Hacking Tools of the Black box WordPress vulnerability scanner.
  • cms-explorer – Reveal the specific modules, plugins, components and themes that various websites powered by content management systems are running.
  • joomscan – one of the best Hacking Tools for Joomla vulnerability scanner.
  • ACSTIS – Automated client-side template injection (sandbox escape/bypass) detection for AngularJS.
Network Tools
  • zmap – Open source network scanner that enables researchers to easily perform Internet-wide network studies.
  • nmap – Free security scanner for network exploration & security audits.
  • pig – one of the Hacking Tools forGNU/Linux packet crafting.
  • scanless – Utility for using websites to perform port scans on your behalf so as not to reveal your own IP.
  • tcpdump/libpcap – Common packet analyzer that runs under the command line.
  • Wireshark – Widely-used graphical, cross-platform network protocol analyzer.
  • Network-Tools.com – Website offering an interface to numerous basic network utilities like ping, traceroute, whois, and more.
  • netsniff-ng – Swiss army knife for network sniffing.
  • Intercepter-NG – Multifunctional network toolkit.
  • SPARTA – Graphical interface offering scriptable, configurable access to existing network infrastructure scanning and enumeration tools.
  • dnschef – Highly configurable DNS proxy for pentesters.
  • DNSDumpster – one of the Hacking Tools for Online DNS recon and search service.
  • CloudFail – Unmask server IP addresses hidden behind Cloudflare by searching old database records and detecting misconfigured DNS.
  • dnsenum – Perl script that enumerates DNS information from a domain, attempts zone transfers, performs a brute force dictionary style attack and then performs reverse look-ups on the results.
  • dnsmap – One of the Hacking Tools for Passive DNS network mapper.
  • dnsrecon – One of the Hacking Tools for DNS enumeration script.
  • dnstracer – Determines where a given DNS server gets its information from, and follows the chain of DNS servers.
  • passivedns-client – Library and query tool for querying several passive DNS providers.
  • passivedns – Network sniffer that logs all DNS server replies for use in a passive DNS setup.
  • Mass Scan – best Hacking Tools for TCP port scanner, spews SYN packets asynchronously, scanning the entire Internet in under 5 minutes.
  • Zarp – Network attack tool centered around the exploitation of local networks.
  • mitmproxy – Interactive TLS-capable intercepting HTTP proxy for penetration testers and software developers.
  • Morpheus – Automated ettercap TCP/IP Hacking Tools .
  • mallory – HTTP/HTTPS proxy over SSH.
  • SSH MITM – Intercept SSH connections with a proxy; all plaintext passwords and sessions are logged to disk.
  • Netzob – Reverse engineering, traffic generation and fuzzing of communication protocols.
  • DET – Proof of concept to perform data exfiltration using either single or multiple channel(s) at the same time.
  • pwnat – Punches holes in firewalls and NATs.
  • dsniff – Collection of tools for network auditing and pentesting.
  • tgcd – Simple Unix network utility to extend the accessibility of TCP/IP based network services beyond firewalls.
  • smbmap – Handy SMB enumeration tool.
  • scapy – Python-based interactive packet manipulation program & library.
  • Dshell – Network forensic analysis framework.
  • Debookee – Simple and powerful network traffic analyzer for macOS.
  • Dripcap – Caffeinated packet analyzer.
  • Printer Exploitation Toolkit (PRET) – Tool for printer security testing capable of IP and USB connectivity, fuzzing, and exploitation of PostScript, PJL, and PCL printer language features.
  • Praeda – Automated multi-function printer data harvester for gathering usable data during security assessments.
  • routersploit – Open source exploitation framework similar to Metasploit but dedicated to embedded devices.
  • evilgrade – Modular framework to take advantage of poor upgrade implementations by injecting fake updates.
  • XRay – Network (sub)domain discovery and reconnaissance automation tool.
  • Ettercap – Comprehensive, mature suite for machine-in-the-middle attacks.
  • BetterCAP – Modular, portable and easily extensible MITM framework.
  • CrackMapExec – A swiss army knife for pentesting networks.
  • impacket – A collection of Python classes for working with network protocols.
Wireless Network Hacking Tools
  • Aircrack-ng – Set of Penetration testing & Hacking Tools list for auditing wireless networks.
  • Kismet – Wireless network detector, sniffer, and IDS.
  • Reaver – Brute force attack against Wifi Protected Setup.
  • Wifite – Automated wireless attack tool.
  • Fluxion – Suite of automated social engineering-based WPA attacks.
Transport Layer Security Tools
  • SSLyze – Fast and comprehensive TLS/SSL configuration analyzer to help identify security misconfigurations.
  • tls_prober – Fingerprint a server’s SSL/TLS implementation.
  • testssl.sh – Command-line tool which checks a server’s service on any port for the support of TLS/SSL ciphers, protocols as well as some cryptographic flaws.
Web Exploitation
  • OWASP Zed Attack Proxy (ZAP) – Feature-rich, scriptable HTTP intercepting proxy and fuzzer for penetration testing web applications.
  • Fiddler – Free cross-platform web debugging proxy with user-friendly companion tools.
  • Burp Suite – One of the Hacking Tools ntegrated platform for performing security testing of web applications.
  • autochrome – Easy to install a test browser with all the appropriate settings needed for web application testing with native Burp support, from NCCGroup.
  • Browser Exploitation Framework (BeEF) – Command and control server for delivering exploits to commandeered Web browsers.
  • Offensive Web Testing Framework (OWTF) – Python-based framework for pentesting Web applications based on the OWASP Testing Guide.
  • WordPress Exploit Framework – Ruby framework for developing and using modules which aid in the penetration testing of WordPress powered websites and systems.
  • WPSploit – Exploit WordPress-powered websites with Metasploit.
  • SQLmap – Automatic SQL injection and database takeover tool.
  • tplmap – Automatic server-side template injection and Web server takeover Hacking Tools.
  • weevely3 – Weaponized web shell.
  • Wappalyzer – Wappalyzer uncovers the technologies used on websites.
  • WhatWeb – Website fingerprinter.
  • BlindElephant – Web application fingerprinter.
  • wafw00f – Identifies and fingerprints Web Application Firewall (WAF) products.
  • fimap – Find, prepare, audit, exploit and even google automatically for LFI/RFI bugs.
  • Kadabra – Automatic LFI exploiter and scanner.
  • Kadimus – LFI scan and exploit tool.
  • liffy – LFI exploitation tool.
  • Commix – Automated all-in-one operating system command injection and exploitation tool.
  • DVCS Ripper – Rip web-accessible (distributed) version control systems: SVN/GIT/HG/BZR.
  • GitTools – One of the Hacking Tools that Automatically find and download Web-accessible .git repositories.
  • sslstrip –One of the Hacking Tools Demonstration of the HTTPS stripping attacks.
  • sslstrip2 – SSLStrip version to defeat HSTS.
  • NoSQLmap – Automatic NoSQL injection and database takeover tool.
  • VHostScan – A virtual host scanner that performs reverse lookups, can be used with pivot tools, detect catch-all scenarios, aliases, and dynamic default pages.
  • FuzzDB – Dictionary of attack patterns and primitives for black-box application fault injection and resource discovery.
  • EyeWitness – Tool to take screenshots of websites, provide some server header info, and identify default credentials if possible.
  • webscreenshot – A simple script to take screenshots of the list of websites.
Hex Editors
  • HexEdit.js – Browser-based hex editing.
  • Hexinator – World’s finest (proprietary, commercial) Hex Editor.
  • Frhed – Binary file editor for Windows.
  • 0xED – Native macOS hex editor that supports plug-ins to display custom data types.
File Format Analysis Tools
  • Kaitai Struct – File formats and network protocols dissection language and web IDE, generating parsers in C++, C#, Java, JavaScript, Perl, PHP, Python, Ruby.
  • Veles – Binary data visualization and analysis tool.
  • Hachoir – Python library to view and edit a binary stream as the tree of fields and tools for metadata extraction.
read more https://oyeitshacker.blogspot.com/2020/01/penetration-testing-hacking-tools.html
submitted by icssindia to HowToHack [link] [comments]

A Complete Penetration Testing & Hacking Tools List for Hackers & Security Professionals

A Complete Penetration Testing & Hacking Tools List for Hackers & Security Professionals

penetration-testing-hacking-tools
Penetration testing & Hacking Tools are more often used by security industries to test the vulnerabilities in network and applications. Here you can find the Comprehensive Penetration testing & Hacking Tools list that covers Performing Penetration testing Operation in all the Environment. Penetration testing and ethical hacking tools are a very essential part of every organization to test the vulnerabilities and patch the vulnerable system.
Also, Read What is Penetration Testing? How to do Penetration Testing?
Penetration Testing & Hacking Tools ListOnline Resources – Hacking ToolsPenetration Testing Resources
Exploit Development
OSINT Resources
Social Engineering Resources
Lock Picking Resources
Operating Systems
Hacking ToolsPenetration Testing Distributions
  • Kali – GNU/Linux distribution designed for digital forensics and penetration testing Hacking Tools
  • ArchStrike – Arch GNU/Linux repository for security professionals and enthusiasts.
  • BlackArch – Arch GNU/Linux-based distribution with best Hacking Tools for penetration testers and security researchers.
  • Network Security Toolkit (NST) – Fedora-based bootable live operating system designed to provide easy access to best-of-breed open source network security applications.
  • Pentoo – Security-focused live CD based on Gentoo.
  • BackBox – Ubuntu-based distribution for penetration tests and security assessments.
  • Parrot – Distribution similar to Kali, with multiple architectures with 100 of Hacking Tools.
  • Buscador – GNU/Linux virtual machine that is pre-configured for online investigators.
  • Fedora Security Lab – provides a safe test environment to work on security auditing, forensics, system rescue, and teaching security testing methodologies.
  • The Pentesters Framework – Distro organized around the Penetration Testing Execution Standard (PTES), providing a curated collection of utilities that eliminates often unused toolchains.
  • AttifyOS – GNU/Linux distribution focused on tools useful during the Internet of Things (IoT) security assessments.
Docker for Penetration Testing
Multi-paradigm Frameworks
  • Metasploit – post-exploitation Hacking Tools for offensive security teams to help verify vulnerabilities and manage security assessments.
  • Armitage – Java-based GUI front-end for the Metasploit Framework.
  • Faraday – Multiuser integrated pentesting environment for red teams performing cooperative penetration tests, security audits, and risk assessments.
  • ExploitPack – Graphical tool for automating penetration tests that ships with many pre-packaged exploits.
  • Pupy – Cross-platform (Windows, Linux, macOS, Android) remote administration and post-exploitation tool,
Vulnerability Scanners
  • Nexpose – Commercial vulnerability and risk management assessment engine that integrates with Metasploit, sold by Rapid7.
  • Nessus – Commercial vulnerability management, configuration, and compliance assessment platform, sold by Tenable.
  • OpenVAS – Free software implementation of the popular Nessus vulnerability assessment system.
  • Vuls – Agentless vulnerability scanner for GNU/Linux and FreeBSD, written in Go.
Static Analyzers
  • Brakeman – Static analysis security vulnerability scanner for Ruby on Rails applications.
  • cppcheck – Extensible C/C++ static analyzer focused on finding bugs.
  • FindBugs – Free software static analyzer to look for bugs in Java code.
  • sobelow – Security-focused static analysis for the Phoenix Framework.
  • bandit – Security oriented static analyzer for Python code.
Web Scanners
  • Nikto – Noisy but fast black box web server and web application vulnerability scanner.
  • Arachni – Scriptable framework for evaluating the security of web applications.
  • w3af – Hacking Tools for Web application attack and audit framework.
  • Wapiti – Black box web application vulnerability scanner with built-in fuzzer.
  • SecApps – In-browser web application security testing suite.
  • WebReaver – Commercial, graphical web application vulnerability scanner designed for macOS.
  • WPScan – Hacking Tools of the Black box WordPress vulnerability scanner.
  • cms-explorer – Reveal the specific modules, plugins, components and themes that various websites powered by content management systems are running.
  • joomscan – one of the best Hacking Tools for Joomla vulnerability scanner.
  • ACSTIS – Automated client-side template injection (sandbox escape/bypass) detection for AngularJS.
Network Tools
  • zmap – Open source network scanner that enables researchers to easily perform Internet-wide network studies.
  • nmap – Free security scanner for network exploration & security audits.
  • pig – one of the Hacking Tools forGNU/Linux packet crafting.
  • scanless – Utility for using websites to perform port scans on your behalf so as not to reveal your own IP.
  • tcpdump/libpcap – Common packet analyzer that runs under the command line.
  • Wireshark – Widely-used graphical, cross-platform network protocol analyzer.
  • Network-Tools.com – Website offering an interface to numerous basic network utilities like ping, traceroute, whois, and more.
  • netsniff-ng – Swiss army knife for network sniffing.
  • Intercepter-NG – Multifunctional network toolkit.
  • SPARTA – Graphical interface offering scriptable, configurable access to existing network infrastructure scanning and enumeration tools.
  • dnschef – Highly configurable DNS proxy for pentesters.
  • DNSDumpster – one of the Hacking Tools for Online DNS recon and search service.
  • CloudFail – Unmask server IP addresses hidden behind Cloudflare by searching old database records and detecting misconfigured DNS.
  • dnsenum – Perl script that enumerates DNS information from a domain, attempts zone transfers, performs a brute force dictionary style attack and then performs reverse look-ups on the results.
  • dnsmap – One of the Hacking Tools for Passive DNS network mapper.
  • dnsrecon – One of the Hacking Tools for DNS enumeration script.
  • dnstracer – Determines where a given DNS server gets its information from, and follows the chain of DNS servers.
  • passivedns-client – Library and query tool for querying several passive DNS providers.
  • passivedns – Network sniffer that logs all DNS server replies for use in a passive DNS setup.
  • Mass Scan – best Hacking Tools for TCP port scanner, spews SYN packets asynchronously, scanning the entire Internet in under 5 minutes.
  • Zarp – Network attack tool centered around the exploitation of local networks.
  • mitmproxy – Interactive TLS-capable intercepting HTTP proxy for penetration testers and software developers.
  • Morpheus – Automated ettercap TCP/IP Hacking Tools .
  • mallory – HTTP/HTTPS proxy over SSH.
  • SSH MITM – Intercept SSH connections with a proxy; all plaintext passwords and sessions are logged to disk.
  • Netzob – Reverse engineering, traffic generation and fuzzing of communication protocols.
  • DET – Proof of concept to perform data exfiltration using either single or multiple channel(s) at the same time.
  • pwnat – Punches holes in firewalls and NATs.
  • dsniff – Collection of tools for network auditing and pentesting.
  • tgcd – Simple Unix network utility to extend the accessibility of TCP/IP based network services beyond firewalls.
  • smbmap – Handy SMB enumeration tool.
  • scapy – Python-based interactive packet manipulation program & library.
  • Dshell – Network forensic analysis framework.
  • Debookee – Simple and powerful network traffic analyzer for macOS.
  • Dripcap – Caffeinated packet analyzer.
  • Printer Exploitation Toolkit (PRET) – Tool for printer security testing capable of IP and USB connectivity, fuzzing, and exploitation of PostScript, PJL, and PCL printer language features.
  • Praeda – Automated multi-function printer data harvester for gathering usable data during security assessments.
  • routersploit – Open source exploitation framework similar to Metasploit but dedicated to embedded devices.
  • evilgrade – Modular framework to take advantage of poor upgrade implementations by injecting fake updates.
  • XRay – Network (sub)domain discovery and reconnaissance automation tool.
  • Ettercap – Comprehensive, mature suite for machine-in-the-middle attacks.
  • BetterCAP – Modular, portable and easily extensible MITM framework.
  • CrackMapExec – A swiss army knife for pentesting networks.
  • impacket – A collection of Python classes for working with network protocols.
Wireless Network Hacking Tools
  • Aircrack-ng – Set of Penetration testing & Hacking Tools list for auditing wireless networks.
  • Kismet – Wireless network detector, sniffer, and IDS.
  • Reaver – Brute force attack against Wifi Protected Setup.
  • Wifite – Automated wireless attack tool.
  • Fluxion – Suite of automated social engineering-based WPA attacks.
Transport Layer Security Tools
  • SSLyze – Fast and comprehensive TLS/SSL configuration analyzer to help identify security misconfigurations.
  • tls_prober – Fingerprint a server’s SSL/TLS implementation.
  • testssl.sh – Command-line tool which checks a server’s service on any port for the support of TLS/SSL ciphers, protocols as well as some cryptographic flaws.
Web Exploitation
  • OWASP Zed Attack Proxy (ZAP) – Feature-rich, scriptable HTTP intercepting proxy and fuzzer for penetration testing web applications.
  • Fiddler – Free cross-platform web debugging proxy with user-friendly companion tools.
  • Burp Suite – One of the Hacking Tools ntegrated platform for performing security testing of web applications.
  • autochrome – Easy to install a test browser with all the appropriate settings needed for web application testing with native Burp support, from NCCGroup.
  • Browser Exploitation Framework (BeEF) – Command and control server for delivering exploits to commandeered Web browsers.
  • Offensive Web Testing Framework (OWTF) – Python-based framework for pentesting Web applications based on the OWASP Testing Guide.
  • WordPress Exploit Framework – Ruby framework for developing and using modules which aid in the penetration testing of WordPress powered websites and systems.
  • WPSploit – Exploit WordPress-powered websites with Metasploit.
  • SQLmap – Automatic SQL injection and database takeover tool.
  • tplmap – Automatic server-side template injection and Web server takeover Hacking Tools.
  • weevely3 – Weaponized web shell.
  • Wappalyzer – Wappalyzer uncovers the technologies used on websites.
  • WhatWeb – Website fingerprinter.
  • BlindElephant – Web application fingerprinter.
  • wafw00f – Identifies and fingerprints Web Application Firewall (WAF) products.
  • fimap – Find, prepare, audit, exploit and even google automatically for LFI/RFI bugs.
  • Kadabra – Automatic LFI exploiter and scanner.
  • Kadimus – LFI scan and exploit tool.
  • liffy – LFI exploitation tool.
  • Commix – Automated all-in-one operating system command injection and exploitation tool.
  • DVCS Ripper – Rip web-accessible (distributed) version control systems: SVN/GIT/HG/BZR.
  • GitTools – One of the Hacking Tools that Automatically find and download Web-accessible .git repositories.
  • sslstrip –One of the Hacking Tools Demonstration of the HTTPS stripping attacks.
  • sslstrip2 – SSLStrip version to defeat HSTS.
  • NoSQLmap – Automatic NoSQL injection and database takeover tool.
  • VHostScan – A virtual host scanner that performs reverse lookups, can be used with pivot tools, detect catch-all scenarios, aliases, and dynamic default pages.
  • FuzzDB – Dictionary of attack patterns and primitives for black-box application fault injection and resource discovery.
  • EyeWitness – Tool to take screenshots of websites, provide some server header info, and identify default credentials if possible.
  • webscreenshot – A simple script to take screenshots of the list of websites.
Hex Editors
  • HexEdit.js – Browser-based hex editing.
  • Hexinator – World’s finest (proprietary, commercial) Hex Editor.
  • Frhed – Binary file editor for Windows.
  • 0xED – Native macOS hex editor that supports plug-ins to display custom data types.
File Format Analysis Tools
  • Kaitai Struct – File formats and network protocols dissection language and web IDE, generating parsers in C++, C#, Java, JavaScript, Perl, PHP, Python, Ruby.
  • Veles – Binary data visualization and analysis tool.
  • Hachoir – Python library to view and edit a binary stream as the tree of fields and tools for metadata extraction.
read more https://oyeitshacker.blogspot.com/2020/01/penetration-testing-hacking-tools.html
submitted by icssindia to Hacking_Tutorials [link] [comments]

MAME 0.218

MAME 0.218

It’s time for MAME 0.218, the first MAME release of 2020! We’ve added a couple of very interesting alternate versions of systems this month. One is a location test version of NMK’s GunNail, with different stage order, wider player shot patterns, a larger player hitbox, and lots of other differences from the final release. The other is The Last Apostle Puppetshow, an incredibly rare export version of Home Data’s Reikai Doushi. Also significant is a newer version Valadon Automation’s Super Bagman. There’s been enough progress made on Konami’s medal games for a number of them to be considered working, including Buttobi Striker, Dam Dam Boy, Korokoro Pensuke, Shuriken Boy and Yu-Gi-Oh Monster Capsule. Don’t expect too much in terms of gameplay though — they’re essentially gambling games for children.
There are several major computer emulation advances in this release, in completely different areas. Possibly most exciting is the ability to install and run Windows NT on the MIPS Magnum R4000 “Jazz” workstation, with working networking. With the assistance of Ash Wolf, MAME now emulates the Psion Series 5mx PDA. Psion’s EPOC32 operating system is the direct ancestor of the Symbian operating system, that powered a generation of smartphones. IDE and SCSI hard disk support for Acorn 8-bit systems has been added, the latter being one of the components of the BBC Domesday Project system. In PC emulation, Windows 3.1 is now usable with S3 ViRGE accelerated 2D video drivers. F.Ulivi has contributed microcode-level emulation of the iSBC-202 floppy controller for the Intel Intellec MDS-II system, adding 8" floppy disk support.
Of course there are plenty of other improvements and additions, including re-dumps of all the incorrectly dumped GameKing cartridges, disassemblers for PACE, WE32100 and “RipFire” 88000, better Geneve 9640 emulation, and plenty of working software list additions. You can get the source and 64-bit Windows binary packages from the download page (note that 32-bit Windows binaries and “zip-in-zip” source code are no longer supplied).

MAME Testers Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

Source Changes

submitted by cuavas to emulation [link] [comments]

Tutorial: Using Borg for backup your QNAP to other devices (Advanced - CLI only)

Tutorial: Using Borg for backup your QNAP to other devices (Advanced - CLI only)
This tutorial will explain how to use Borg Backup to perform backups. This tutorial will specifically be aimed to perform backups from our QNAP to another unit (another NAS in your LAN, external hard drive, any off-site server, etc). But it is also a great tool to backup your computers to your NAS. This tutorial is a little bit more technical than the previous, so, be patient :)
MASSIVE WALL OF TEXT AHEAD. You have been warned.
Why Borg instead of, let’s say HBS3? Well, Borg is one of the best -if not THE BEST- backup software available. It is very resilient to failure and corruption. Personally I’m in love with Borg. It is a command line based tool. That means that there is no GUI available (there are a couple of front-end created by community, though). I know that can be very intimidating at first when you are not accustomed to it, and that it looks ugly, but honestly, it is not so complicated, and if you are willing to give it a try, I can assure you that is simple and easy. You might even like it over time!
https://www.borgbackup.org/
That aside, I have found that HBS3 can only perform incremental backups when doing QNAP-QNAP backups. It can use Rsync to save files to a non-QNAP device, but then you can’t use incremental (and IIRC, neither Deduplication or encryption). It will even refuse to save to a mounted folder using hybrid mount. QNAP seems to be trying to subtle lock you down in their ecosystem. Borg has none of those limitations.

Main pros of Borg Backup:
- VERY efficient and powerful
- Space efficient thanks to deduplication and compression
- Allows encryption, deduplication, incremental, compression… you name it.
- Available in almost any OS (except Windows) and thanks to Docker, even in Windows. There are also ARM binaries, so it is Raspberry compatible, and even ARM based QNAPs that don’t support docker can use it!!!
- Since it’s available in most OS, you can use a single unified solution for all your backups.
- Can make backups in PUSH and PULL style. Either each machine with Borg pushes the files into the server, or a single server with Borg installed pulls the files from any device without needing to install Borg on those devices.
- It is backed by a huge community with tons of integration and wrapper tools (https://github.com/borgbackup/community)
- Supports Backup to local folders, LAN backups using NFS or SMB, and also remote backups using SFTP or mounting SSHFS.
- IT IS FOSS. Seriously, guys, whenever possible, choose FOSS.

Cons of Borg Backup:
- It is not tailored for backups to cloud services like Drive or Mega. You might want to take a look at Rclone or Restic for that.
- It lacks GUI, so everything is CLI controlled. I know, it can be very intimidating, but once you have used it for a couple of days, you will notice how simple and comfortable to use is.

The easiest way to run Borg is to just grab the appropriate prebuilt binary (https://github.com/borgbackup/borg/releases) and run it baremetal, but I’m going to show how to install Borg in a docker container so you can apply this solution to any other scenario where docker is available. If you want to skip the container creation, just proceed directly to step number 2.

**FIRST STEP: LET'S BUILD THE CONTAINER**
There is currently no official Borg prebuilt container (although there are non-official ones). Since it’s a CLI tool, you don’t really need a prebuilt container, you can just use your preferred one (Ubuntu, Debian, Alpine etc) and install Borg directly in your container. We are using a ubuntu:latest container because the available Borg version for ubuntu is up to date. For easiness, all those directories we want to backup will be mounted inside the container in /output.
If you already are familiar with SSH and container creation though CLI, just user this template, substituting your specific directories mount.
docker run -it \ --cap-add=NET_ADMIN \ --net=bridge \ --privileged \ --cap-add SYS_ADMIN \ --device /dev/fuse \ --security-opt apparmor:unconfined \ --name=borgbackup \ -v /share/Movies:/output/Movies:ro \ -v /share/Important/Documents:/output/Documents:ro \ -v /share/Other:/output/Other:ro \ -v /share/Containeborgbackup/persist:/persist \ -v /etc/localtime:/etc/localtime:ro \ ubuntu:latest 
(REMEMBER: LINUX IS CAPITAL SENSIBLE, SO CAPITALS MATTER!!)
Directories to be backup are mounted as read only (:ro) for extra safety. I have also found that mounting another directory as “persistent” directory makes easy to create and edit the needed scripts directly from File Finder in QNAP, and also allows to keep them in case you need to destroy or recreate the container: this is the “/persist” directory. Use your favorite path.
If you are not familiar with SSH, first go here to learn how to activate and login into your QNAP using SSH (https://www.qnap.com/en/how-to/knowledge-base/article/how-to-access-qnap-nas-by-ssh/).
You can also use the GUI in Container Station to create the container and mount folders in advanced tab during container creation. Please, refer to QNAP’s tutorials about Docker.
GUI example
If done correctly, you will see that this container appears in the overview tab of Container Station. Click the name, and then click the two arrows. That will transport you to another tab inside the container to start working.
https://preview.redd.it/5y09skuxrvj41.jpg?width=1440&format=pjpg&auto=webp&s=19e4b22d6458d2c9a8143c9841f070828bcf5170

**SECOND STEP: INSTALLING BORG BACKUP INSIDE THE CONTAINER**
First check that the directory with all the data you want to backup (/output in our example) is mounted. If you can’t see anything, then you did something wrong in the first step when creating the container. If so, delete the container and try again. Now navigate to /persist using “cd /persist”
See how /output contains to-be-backup directories
Now, we are going to update ubuntu and install some dependencies and apps we need to work. Copy and paste this:
apt update && apt upgrade -y apt install -y nano fuse software-properties-common nfs-common ssh 
It will install a lot of things. Just let it work. When finished, install borgbackup using
add-apt-repository -y ppa:costamagnagianfranco/borgbackup apt install -y borgbackup 
When it’s finished, run “borg --version” and you will be shown the current installed version (at time of writing this current latest is 1.1.10). You already have Borg installed!!!!
1.1.10 is latest version at the time of this tutorial creation

**THIRD STEP: PREPARING THE BACKUP DEVICE USING NFS MOUNT**
Now, to init the repository, we first need to choose where we want to make the backup. Borg can easily make “local” backups, choosing a local folder, but that defeats the purpose for backups, right? We want to create remote repositories.
If you are making backups to a local (same network) device (another NAS, a computer, etc) then you can choose to use SFTP (SSH file transfer) or just NFS or SMB to mount a folder. If you want to backup to a remote repository outside your LAN (the internet) you HAVE to use SFTP or SSHFS. I’m explaining now how to mount folder using NFS, leaving SFTP for later.
Borg can work in two different ways: PUSH style or PULL style.
In PUSH style, each unit to be backup have Borg installed and it “pushes” the files to a remote folder using NFS, SMB or SSHFS. The target unit do not need to have Borg installed.
PUSH style backup: The QNAP sends files to the backup device

In PULL style, the target unit that is going to receive the backups has Borg installed, and it “pulls” the files from the units to be backup (and so, they don’t need Borg installed) using NFS, SMB or SSHFS. This is great if you have a powerful NAS unit and want to backup several computers.
PULL style backup: The backup device gets files from QNAP. Useful for multiple unit backups into the same backup server.

When using SFTP, the backup unit has Borg installed, opens a secure SSH connection to target unit, connects with Borg in target machine, and uploads the files. In SFTP style, BOTH units need Borg installed.
SFTP: Borg needs to be installed in both devices, and they \"talk\" each other.

I’m assuming you have another device with IP “192.168.1.200” (in my example I’m using a VM with that IP) with a folder called “/backup” inside. I’m also assuming that you have correctly authorized NFS mount with read/write permissions between both devices. If you don’t now how to, you’ll need to investigate. (https://www.qnap.com/en-us/how-to/knowledge-base/article/how-to-enable-and-setup-host-access-for-nfs-connection/)
NFS mount means mirroring two folders from two different devices. So, mounting folder B from device Y into folder A from device X means that even if the folder B is “physically” stored on device Y, the device X can use it exactly as if it was folder A inside his local path. If you write something to folder A, folder B will automatically be updated with that new file and vice-versa.
Graphical example of what happens when mounting folders in Linux system.
Mount usage is: “mount [protocol] [targetIP]:/target/directory /local/directory” So, go to your container and write:
mount -t nfs 192.168.1.200:/backup /mnt 
Mount is the command to mount. “-t nfs” means using NFS, if you want to use SMB you would use “-t cifs”. 192.168.1.200 is the IP of the device where you are going to make backups. /backup is the directory in the target we want to save our backups to (remember you need to correctly enable permission for NFS server sharing in the target device). /mnt is the directory in the container where the /backup folder will be mounted.
OK, so now /mnt in container = /backup in target. If you drop a .txt file in one of those directories, it will immediately appear on the other. So… All we have to do now is make a borg repository on /mnt and wildly start making backups. /mnt will be our working directory.

**FOURTH STEP: ACTUALLY USING BORG** (congrats if you made it here)
Read the documentation
https://borgbackup.readthedocs.io/en/stable/usage/general.html
It’s madness. Right?. It’s OK. In fact we only need a very few borg commands to make it work.
“borg init” creates a repository, that is, a place where the backup files are stored.
“borg create” makes a backup
“borg check” checks backup integrity
“borg prune” prunes the backup (deletes older files)
“borg extract” extract files from a backup
“borg mount” mounts a backup as if it was a directory and you can navigate it
“borg info” gives you info from the repository
“borg list” shows every backup inside the repository
But since we are later using pre-made scripts for backup, you will only need to actually use “init”, “info” and “list” and in case of recovery, “mount”.
let’s create our repository using INIT
https://borgbackup.readthedocs.io/en/stable/usage/init.html
borg init -e [encryption] [options] /mnt 
So, if you want to encrypt the repository with a password (highly recommended) use “-e repokey” or “-e repokey-blake2”. If you want to use a keyfile instead, use “-e keyfile”. If you don’t want to encrypt, use “-e none”. If you want to set a maximum space quota, use “--storage-quota ” to avoid excessive storage usage (I.e “--storage-quota 500G” or “--storage-quota 2.5T”). Read the link above. OK, so in this example:
borg init -e repokey –storage-quota 200G /mnt 
You will be asked for a password. Keep this password safe. If you lose it, you lose your backups!!!! Once finished, we have our repository ready to create the first backup. If you use “ls /mnt” you will see than the /mnt directory is no longer empty, but contains several files. Those are the repository files, and now should also be present in your backup device.
init performed successfully
Let’s talk about actually creating backups. Usually, you would create a backup using the “borg create” backup command, using something like this:
borg create -l -s /mnt::Backup01 /output --exclude ‘*.py’ 
https://borgbackup.readthedocs.io/en/stable/usage/create.html
That would create a backup archive called “backup01” of all files and directories in /output, but excluding every .py file. It will also verbose all files (-l) and stats (-s) during the process. If you later write the same but with “Backup02”, only new added files will be saved (incremental) but deleted files will still be available in “Backup01”. So as new backups are made, you will end running out of storage space. To avoid this you would need to schedule pruning.
https://borgbackup.readthedocs.io/en/stable/usage/prune.html
borg prune [options] [path/to/repo] is used to delete old backups based on your specified options (I.e “save 4 last year backups, 1 backups each month last year, and 1 daily last month).
BUT. To make is simple, we just need to create a script that will automatically 1) Create a new backup with specified name and 2) run a Prune with specified retention policy.
Inside the container head to /persist using “cd /persist”, and create a file called backup.sh using
touch backup.sh chmod 700 backup.sh nano backup.sh 
Then, copy the following and paste it inside nano using CTRL+V
#!/bin/sh # Setting this, so the repo does not need to be given on the command line: export BORG_REPO=/mnt # Setting this, so you won't be asked for your repository passphrase: export BORG_PASSPHRASE='YOURsecurePASS' # or this to ask an external program to supply the passphrase: # export BORG_PASSCOMMAND='pass show backup' # some helpers and error handling: info() { printf "\n%s %s\n\n" "$( date )" "$*" >&2; } trap 'echo $( date ) Backup interrupted >&2; exit 2' INT TERM info "Starting backup" # Backup the most important directories into an archive named after # the machine this script is currently running on: borg create \ --verbose \ --filter AME \ --list \ --stats \ --show-rc \ --compression lz4 \ --exclude-caches \ --exclude '*@Recycle/*' \ --exclude '*@Recently-Snapshot/*' \ --exclude '*[email protected]__thumb/*' \ \ ::'QNAP-{now}' \ /output \ backup_exit=$? info "Pruning repository" # Use the `prune` subcommand to maintain 7 daily, 4 weekly and 6 monthly # archives of THIS machine. The 'QNAP-' prefix is very important to # limit prune's operation to this machine's archives and not apply to # other machines' archives also: borg prune \ --list \ --prefix 'QNAP-' \ --show-rc \ --keep-daily 7 \ --keep-weekly 4 \ --keep-monthly 6 \ prune_exit=$? # use highest exit code as global exit code global_exit=$(( backup_exit > prune_exit ? backup_exit : prune_exit )) if [ ${global_exit} -eq 0 ]; then info "Backup and Prune finished successfully" elif [ ${global_exit} -eq 1 ]; then info "Backup and/or Prune finished with warnings" else info "Backup and/or Prune finished with errors" fi exit ${global_exit} 
This script seems very complicated, but all it does is
  1. Define the backup location
  2. Define backup parameters, inclusions and exclusions and run backup
  3. Define pruning policy and run prune
  4. Show stats
You can freely modify it using the options you need (they are described in the documentation).
“export BORG_REPO=/mnt” is where the repository is located.
“export BORG_PASSPHRASE='YOURsecurePASS' is your repository password (between the single quotes)
After “borg create” some options are defined, like compression, file listing and stat showing. Then exclusion are defined (each –exclude defines one exclusion rules. In this example I have defined rules to avoid backup thumbnails, recycle bin files, and snapshots). If you wish to exclude mode directories or files, you do it adding a new rule there.
::'QNAP-{now}' defines how backups will be named. Right now they will be named as QNAP-”current date and time”. In case you want only current date and not time used, you can use instead:
::'QNAP-{now:%Y-%m-%d}' \
Be aware that if you decide to do so, you will only be able to create a single backup each day, as subsequent backups the same day will fail, since Borg will find another backup with same name and skip the current one.
/output below is the directory to be backup.
And finally, prune policy is at the end. This defines what backups will be kept and which ones will be deleted. Current defined policy is to keep 7 end of day, then 4 end of week and 6 end of month backups. Extra backups will be deleted. You can modify this depending on your needs. Follow the documentation for extra information and examples.
https://borgbackup.readthedocs.io/en/stable/usage/prune.html
Now save the script using CTRL+O. We are ready. Run the script using:
./backup.sh
It will show progress, including what files are being saved. After finishing, it will return backup name (in this example “QNAP-2020-01-26T01:05:36“ is the name of the backup archive), stats and will return two rc status, one for the backup, and another for pruning. “rc0” means success. “rc1” means finished, but with some errors. “rc2” means failed. You should be returned two rc0 status and the phrase “Backup and Prune finished successfully”. Congrats.
Backup completed. rc 0=good. rc 2=bad
You can use any borg command manually against your repository as needed. For example:
borg list /mnt List your current backups inside the repository borg list /mnt::QNAP-2020-01-26T01:05:36 List all archives inside this specific backup borg info /mnt List general stats of your repository borg check -v –show-rc /mnt Performs an integrity check and returns rc status (0, 1 or 2) 
All that is left is to create the final running script and the cronjob in our QNAP to automate backups. You can skip the next step, as it describes the same process but using SFTP instead of NFS, and head directly to step number Six.

**FIFTH STEP: HTE SAME AS STEP 4, BUT USING SFTP INSTEAD**
If you want to perform backups to an off-site machine, like another NAS located elsewhere, then you can’t use NFS or SMB, as they are not prepared to be used through internet and are not safe. We must use SFTP. SFTP is NOT FTP over SSL (that is FTPS). SFTP stands for Secure File Transfer Protocol, and it’s based on SSH but for file transfer. It is secure, as everything is encrypted, but expect lower speed due encryption overhead. We need to first set it up SSH on our target machine, so be sure to enable it. I also recommend to use a non standard port. In our example, we are using port 4000.
IMPORTANT NOTE: To use SFTP, borg backup must be running in the target machine. You can run it baremetal, or use a container, just as in our QNAP, but if you really can’t get borg running in the target machine, then you cannot use SFTP. There is an alternative, though: SSHFS, which is basically NFS but over SSH. With it you can securely mount a folder over internet. Read this documentation (https://www.digitalocean.com/community/tutorials/how-to-use-sshfs-to-mount-remote-file-systems-over-ssh) and go back to Third Step once you got it working. SSHFS is not covered in this tutorial.
First go to your target machine, and create a new user (in our example this will be “targetuser”)
Second we need to create SSH keys, so both the original machine and the target one can perform SSH connection without needing for a password. It also greatly increases security. In our original container run
ssh-keygen -t rsa 
When you are asked for a passphrase just press enter (no passphrase). Your keys are now stored in ~/.ssh To copy them to your target machine, use this:
ssh-copy-id -p 4000 [email protected] 
If that don’t work, this is an alternative command you can use:
cat ~/.ssh/id_rsa.pub | ssh -p 4000 [email protected] "mkdir -p ~/.ssh && chmod 700 ~/.ssh && cat >> ~/.ssh/authorized_keys" 
You will be asked for targetuser password when connecting. If you were successful, you can now SSH without password in the target machine using “ssh -p 4000 [email protected]”. Try it now. If you get to login without password prompt, you got it right. If it still asks you for password when SSH’ing, try repeating the last step or google a little about how to transfer the SSH keys to the target machine.
Now that you are logged in your target machine using SSH, install Borg backup if you didn’t previously, create the backup folder (/backup in our example) and init the repository as was shown in Third Step.
borg init -e repokey –storage-quota 200G /backup 
Once the repository is initiated, you can exit SSH using “exit” command. And you will be back in your container. You know what comes next.
cd /persist touch backup.sh chmod 700 backup.sh nano backup.sh 
Now paste this inside:
#!/bin/sh # Setting this, so the repo does not need to be given on the command line: export BORG_REPO=ssh://[email protected]:4000/backup # Setting this, so you won't be asked for your repository passphrase: export BORG_PASSPHRASE='YOURsecurePASS' # or this to ask an external program to supply the passphrase: # export BORG_PASSCOMMAND='pass show backup' # some helpers and error handling: info() { printf "\n%s %s\n\n" "$( date )" "$*" >&2; } trap 'echo $( date ) Backup interrupted >&2; exit 2' INT TERM info "Starting backup" # Backup the most important directories into an archive named after # the machine this script is currently running on: borg create \ --verbose \ --filter AME \ --list \ --stats \ --show-rc \ --compression lz4 \ --exclude-caches \ --exclude '*@Recycle/*' \ --exclude '*@Recently-Snapshot/*' \ --exclude '*[email protected]__thumb/*' \ \ ::'QNAP-{now}' \ /output \ backup_exit=$? info "Pruning repository" # Use the `prune` subcommand to maintain 7 daily, 4 weekly and 6 monthly # archives of THIS machine. The 'QNAP-' prefix is very important to # limit prune's operation to this machine's archives and not apply to # other machines' archives also: borg prune \ --list \ --prefix 'QNAP-' \ --show-rc \ --keep-daily 7 \ --keep-weekly 4 \ --keep-monthly 6 \ prune_exit=$? # use highest exit code as global exit code global_exit=$(( backup_exit > prune_exit ? backup_exit : prune_exit )) if [ ${global_exit} -eq 0 ]; then info "Backup and Prune finished successfully" elif [ ${global_exit} -eq 1 ]; then info "Backup and/or Prune finished with warnings" else info "Backup and/or Prune finished with errors" fi exit ${global_exit} 
CTRL+O to save, and CTRL+X to exit. OK, let’s do it.
./backup.sh 
It should correctly connect and perform your backup. Note that the only thing I modified from the script shown in Fourth Step is the “BORG_REPO” line, which I substituted from local “/mnt” to remote SSH with our target machine and user data.
Finally all that is left is to automate this.

**SIXTH STEP: AUTOMATING BACKUP**
The only problem is that containers can’t retain mount when they reboot. That is not problem if you are using SFTP, but in case of NFS, we need to re-mount each time the container is started, and fstab does not work in container. The easiest solution is create a script called “start.sh”
cd /persist mkdir log touch start.sh chmod 700 start.sh nano start.sh 
and inside just paste this:
#!/bin/bash log=”/persist/log/borg.log” mount -t nfs 192.168.1.200:/backup /mnt /persist/backup.sh 2>> $log echo ==========FINISH========== >> $log 
Save and try it. Stop container, and start it again. If you use “ls /mnt” you will see that the repository is no longer there. That is because the mounting point unmounted when you stopped the container. Now run
/persist/start.sh 
When it’s finished, a log file will appear inside /persist/log. It contains everything borg was previously putting in the screen, and you can check it using
cat /persist/log/borg.cat 
Everything is ready. All we need to do is is create a crontab job to automate this script whenever we want. You can read here how to edit crontab in QNAP (https://wiki.qnap.com/wiki/Add_items_to_crontab). Add this line to the crontab:
0 1 * * * docker start borgbackup && docker exec borgbackup -c /bin/bash “/persist/start.sh” && docker stop borgbackup 
That will launch container each day at 1:00 am, run the start.sh script, and stop the container when finished.

**EXTRA: RECOVERING OUR DATA**
In case you need to recover your data, you can use any device with Borg installed. There are two commands you can use: borg extract and borg mount. Borg extract will extract all files inside an archive into current directory. Borg mount will mount the repository so you can navigate it, and choose specific files you want to recover, much like NFS or SMB work.
Some examples:
borg extract /mnt::QNAP-2020-01-26T01-05-36 -> Extract all files from this specific backup time point into current directory borg mount /mnt::QNAP-2020-01-26T01-05-36 /recover -> Mounts this specific backup time point inside the /recover directory so you can navigate and search files inside borg mount /mnt /recover -> Mounts all backup time points inside the /recover directory. You can navigate inside all time points and recover whatever you want borg umount /recover -> Unmounts the repository from /recover 

I know this is a somewhat complicated tutorial, and sincerely, I don’t think there will be a lot of people interested, as Borg is for advanced users. That said, I had a ton of fun using borg and creating this tutorial. I hope it can help some people. I am conscious that like 99% of this community's users do not need advanced features and would do great using HB3... But TBH, I'm writing for that 1%.
Next up: I’m trying a duplicati container that it is supposed to have GUI, so… maybe the next tutorial will be a GUI based backup tool. How knows?
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