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The security of cryptographic systems depends on some secret data that is known to authorized persons but unknown and unpredictable to others. To achieve this unpredictability, some randomization is typically employed. Modern cryptographic protocols often require frequent generation of random quantities.

Cryptographic attacks that subvert or exploit weaknesses in this process are known as random number generator attacks. A high quality random number generation RNG process is almost always required for security, and lack of quality generally provides attack vulnerabilities and so leads to lack of security, even to complete compromise, in cryptographic systems.

If the attacker can substitute pseudo-random bits generated in a way they can predict, security is totally compromised, yet generally undetectable by any upstream test of the bits.

Furthermore, such attacks require only a single access to the system that is being compromised. No data need be sent back in contrast to, say, a computer virus that steals keys and then e-mails them to some drop point.

Humans generally do poorly at generating random quantities. Magicians, professional gamblers and con artists depend on the predictability of human behavior. In World War II German code clerks were instructed to select three letters at random to be the initial rotor setting for each Enigma machine message.

Instead some chose predictable values like their own or a girlfriend's initials, greatly aiding Allied breaking of these encryption systems.

Another example is the often predictable ways computer users choose passwords see password cracking. Nevertheless, in the specific case of playing mixed strategy games, use of human gameplay entropy for randomness generation was studied by Ran Halprin and Moni Naor.

Just as with other components of a cryptosystem, a software random number generator should be designed to resist certain attacks. Some attacks possible on a RNG include from [3] :. A number of attacks on hardware random number generators are possible, including trying to capture radio-frequency emissions from the computer obtaining hard drive interrupt times from motor noise, for example , or trying to feed controlled signals into a supposedly random source such as turning off the lights in a lava lamp or feeding a strong, known signal into a sound card.

Subverted random numbers can be created using a cryptographically secure pseudorandom number generator with a seed value known to the attacker but concealed in the software.

A relatively short, say 24 to 40 bit, portion of the seed can be truly random to prevent tell-tale repetitions, but not long enough to prevent the attacker from recovering, say, a "randomly" produced key.

Random numbers typically go through several layers of hardware and software before they are used. Bits may be generated in a peripheral device, sent over a serial cable, collected in an operating system utility and retrieved by a system call. The subverted bits can be substituted at any point in this process with little likelihood of detection. A hardware circuit to produce subverted bits can be built on an integrated circuit a few millimeters square.

The most sophisticated hardware random number generator can be subverted by placing such a chip anywhere upstream of where the source of randomness is digitized, say in an output driver chip or even in the cable connecting the RNG to the computer.

It could be installed by the manufacturer at the behest of their national signals intelligence service, or added later by anyone with physical access. CPU chips with built-in hardware random number generators can be replaced by compatible chips with a subverted RNG in the chips' firmware.

Designing a secure random number generator requires at least as high a level of care as designing other elements of a cryptographic system. These quantities are often relatively predictable, and so have little entropy and are less than random, and so that version of SSL was found to be insecure as a result.

The problem in the running code was discovered in by Ian Goldberg and David Wagner , [4] who had to reverse engineer the object code because Netscape refused to reveal the details of its random number generation security through obscurity.

That RNG was fixed in later releases version 2 and higher by more robust i. Microsoft uses an unpublished algorithm to generate random values for its Windows operating system. These random quantities are made available to users via the CryptGenRandom utility. In November , Leo Dorrendorf et al. The paper's conclusions were based on disassembly of the code in Windows , but according to Microsoft applied to Windows XP as well.

The U. In August , Dan Shumow and Niels Ferguson of Microsoft showed that the constants could be constructed in such a way as to create a kleptographic backdoor in the algorithm. The system is proprietary and originally the algorithm has not been published. Upon reverse engineering of the chip, researchers from the University of Virginia and the Chaos Computer Club found an attack on Crypto-1 exploiting a poorly initialized random number generator.

In May , security researcher Luciano Bello revealed his discovery that changes made in to the random number generator in the version of the OpenSSL package distributed with Debian Linux and other Debian-based distributions, such as Ubuntu , dramatically reduced the entropy of generated values and made a variety of security keys vulnerable to attack.

Keys generated by non-Debian-based Linux distributions are also unaffected. The weak-key-generation vulnerability was promptly patched after it was reported, but any services still using keys that were generated by the old code remain vulnerable.

A number of software packages now contain checks against a weak key blacklist to attempt to prevent use of any of these remaining weak keys, but researchers continue to find weak key implementations. In December , a group calling itself fail0verflow announced recovery of the elliptic curve digital signature algorithm ECDSA private key used by Sony to sign software for the PlayStation 3 game console.

The attack was made possible because Sony failed to generate a new random nonce for each signature. They were able to factor 0.

Nadia Heninger , part of a group that did a similar experiment, said that the bad keys occurred almost entirely in embedded applications , and explains that the one-shared-prime problem uncovered by the two groups results from situations where the pseudorandom number generator is poorly seeded initially and then reseeded between the generation of the first and second primes.

When this occurred the private key could be recovered, in turn allowing stealing Bitcoins from the containing wallet. From Wikipedia, the free encyclopedia. IETF draft draft-jenkins-cnsa-cmc-profile National Security Agency. The use of inadequate pseudo-random number generators PRNGs can result in little or no security.

The generation of quality random numbers is difficult. Schneier; D. Wagner; C. Hall Retrieved 15 August Dobb's Journal. S2CID Archived from the original on May 11, The New York Times. San Francisco. Retrieved December 20, National Institute of Standards and Technology. SS'08 Proceedings of the 17th conference on Security symposium.

Debian Security Advisory. January 9, OpenSSL 0. Retrieved Freedom to Tinker. Archived from the original on Retrieved 27 November The Register. Categories : Cryptographic attacks Pseudorandom number generators. Hidden categories: CS1 errors: external links CS1 errors: missing periodical Wikipedia articles needing clarification from June Namespaces Article Talk. Views Read Edit View history.

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With various algorithm changes, updates, security issues in protocols, and having to write vendor statements for organisations like CERT, keeping the Bouncy Castle project going is turning into a full time job and several of us have now given up permanent work in order to free up time to work on it. If you are making use of our software, and are interested in making sure we are always here when you need us, there are two principal ways you can help. The first is by getting a support contract or by sponsoring specific work on the project. Not only will you get a hot-line to Bouncy Castle developers, consulting time, and release alerts if you need them, but, if you wish, we will also acknowledge your support publicly. Without considering the costs of actually doing what we do, we're also trying to raise money to allow us to get certifications such as FIPs for the APIs.

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Advertise on DistroWatch. The DistroWatch web site was first published on 31 May Trying to make it slightly more comprehensive and useful and failing to find anything similar and up-to-date on the Internet , I kept adding more distributions, features and packages until the table reached a fairly reasonable state in terms of information provided. At that stage, I decided to share the table with the Linux community worldwide and moved it from a spreadsheet into an HTML document. As of the 2nd quarter of , DistroWatch serves approximately 17 million pages to over , unique visitors per month. The main index page is viewed by about , - , visitors each working day and , - , visitors on weekends, while visits to pages devoted to individual distributions vary substantially - from around - 4, page views per day for major Linux distributions Mint, Ubuntu, Debian, Fedora to about 20 a day for some of the lesser known and regional distributions. Please see the Awstats analysis for more detailed information.

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Soaring cryptocurrency valuations have broken record after record over the past few years, turning people with once-modest holdings into overnight millionaires. One determined ring of criminals has tried to join the party using a wide-ranging operation that for the past 12 months has used a full-fledged marketing campaign to push custom-made malware written from scratch for Windows, macOS, and Linux devices. The operation, which has been active since at least January , has spared no effort in stealing the wallet addresses of unwitting cryptocurrency holders, according to a report published by security firm Intezer. The scheme includes three separate trojanized apps, each of which runs on Windows, macOS, and Linux. It also relies on a network of fake companies, websites, and social media profiles to win the confidence of potential victims.

Unix and Linux vendors are moving to using and bit SHA-2 for secure password hashing. Several cryptocurrencies, including Bitcoin, use SHA for.

Information on source package openssl

Journal of Cyber Security, Vol. All rights reserved. In this paper we examine the history of using random numbers in computer programs. Failures in this area have been both intentional and unintentional, but unfortunately the same sorts of mistakes are repeated.

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Random number generator attack

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A cryptocurrency is a digital or virtual currency that is secured by cryptography, which makes it nearly impossible to counterfeit or double-spend. Typically it does not exist in physical form like paper money and is also typically not issued by a central authority. Since then, thousands of unique cryptocurrencies have appeared. Of these, Bitcoin remains the most popular.

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