Suramya's Blog : Welcome to my crazy life…

April 13, 2022

Internet of Things (IoT) Forensics: Challenges and Approaches

Internet of Things or IoT consists of interconnected devices that have sensors and software, which are connected to automated systems to gather information and depending on the information collected various actions can be performed. It is one of the fastest growing markets, with enterprise IoT spending to grow by 24% in 2021 from $128.9 billion. (IoT Analytics, 2021).

This massive growth brings new challenges to the table as administrators need to secure IoT devices in their network to prevent them from being security threats to the network and attackers have found multiple ways through which they can gain unauthorized access to systems by compromising IoT systems.

IoT Forensics is a subset of the digital forensics field and is the new kid on the block. It deals with forensics data collected from IoT devices and follows the same procedure as regular computer forensics, i.e., identification, preservation, analysis, presentation, and report writing. The challenges of IoT come into play when we realize that in addition to the IoT sensor or device we also need to collect forensic data from the internal network or Cloud when performing a forensic investigation. This highlights the fact that Forensics can be divided into three categories: IoT device level, network forensics and cloud forensics. This is relevant because IoT forensics is heavily dependent on cloud forensics (as a lot of data is stored in the cloud) and analyzing the communication between devices in addition to data gathered from the physical device or sensor.

Why IoT Forensics is needed

The proliferation of Internet connected devices and sensors have made life a lot easier for users and has a lot of benefits associated with it. However, it also creates a larger attack surface which is vulnerable to cyberattacks. In the past IoT devices have been involved in incidents that include identity theft, data leakage, accessing and using Internet connected printers, commandeering of cloud-based CCTV units, SQL injections, phishing, ransomware and malware targeting specific appliances such as VoIP devices and smart vehicles.

With attackers targeting IoT devices and then using them to compromise enterprise systems, we need the ability to extract and review data from the IoT devices in a forensically sound way to find out how the device was compromised, what other systems were accessed from the device etc.

In addition, the forensic data from these devices can be used to reconstruct crime scenes and be used to prove or disprove hypothesis. For example, data from a IoT connected alarm can be used to determine where and when the alarm was disabled and a door was opened. If there is a suspect who wears a smartwatch then the data from the watch can be used to identify the person or infer what the person was doing at the time. In a recent arson case, the data from the suspects smartwatch was used to implicate him in arson. (Reardon, 2018)

The data from IoT devices can be crucial in identifying how a breach occurred and what should be done to mitigate the risk. This makes IoT forensics a critical part of the Digital Forensics program.

Current Forensic Challenges Within the IoT

The IoT forensics field has a lot of challenges that need to be addressed but unfortunately none of them have a simple solution. As shown in the research done by M. Harbawi and A. Varol (Harbawi, 2017) we can divide the challenges into six major groups. Identification, collection, preservation, analysis and correlation, attack attribution, and evidence presentation. We will cover the challenges each of these presents in the paper.

A. Evidence Identification

One of the most important steps in forensics examination is to identify where the evidence is stored and collect it. This is usually quite simple in the traditional Digital Forensics but in IoT forensics this can be a challenge as the data required could be stored in a multitude of places such as on the cloud, or in a proprietary local storage.

Another problem is that since IoT fundamentally means that the nodes were in real-time and autonomous interaction with each other, it is extremely difficult to reconstruct the crime scene and to identify the scope of the damage.

A report conducted by the International Data Corporation (IDC) states that the estimated growth of data generated by IoT devices between 2005 to 2020 is going to be more than 40,000 exabytes (Yakubu et al., 2016) making it very difficult for investigators to identify data that is relevant to the investigation while discarding the irrelevant data.

B. Evidence Acquisition

Once the evidence required for the case has been identified the investigative team still has to collect the information in a forensically sound manner that will allow them to perform analysis of the evidence and be able to present it in the court for prosecution.

Due to the lack of a common framework or forensic model for IoT investigations this can be a challenge. Since the method used to collect evidence can be challenged in court due to omissions in the way it was collected.

C. Evidence Preservation and Protection

After the data is collected it is essential that the chain of custody is maintained, and the integrity of the data needs to be validated and verifiable. In the case of IoT Forensics, evidence is collected from multiple remote servers, which makes maintaining proper Chain of Custody a lot more complicated. Another complication is that since these devices usually have a limited storage capacity and the system is continuously running there is a possibility of the evidence being overwritten. We can transfer the data to a local storage device but then ensuring the chain of custody is unbroken and verifiable becomes more difficult.

D. Evidence Analysis and Correlation

Due to the fact that IoT nodes are continuously operating, they produce an extremely high volume of data making it difficult to analyze and process all the data collected. Also, since in IoT Forensics there is less certainty about the source of data and who created or modified the data, it makes it difficult to extract information about ownership and modification history of the data in question.

With most of the IoT devices not storing metadata such as timestamps or location information along with issues created by different time zones and clock skew/drift it is difficult for investigators to create causal links from the data collected and perform analysis that is sound, not subject to interpretation bias and can be defended in court.

E. Attack and Deficit Attribution

IoT forensics requires a lot of additional work to ensure that the device physical and digital identity are in sync and the device was not being used by another person at the time. For example, if a command was given to Alexa by a user and that is evidence in the case against them then the examiner needs to confirm that the person giving the command was physically near the device at the time and that the command was not given over the phone remotely.

F. Evidence Presentation

Due to the highly complex nature of IoT forensics and how the evidence was collected it is difficult to present the data in court in an easy to understand way. This makes it easier for the defense to challenge the evidence and its interpretation by the prosecution.

VI. Opportunities of IoT Forensics

IoT devices bring new sources of information into play that can provide evidence that is hard to delete and most of the time collected without the suspect’s knowledge. This makes it hard for them to account for that evidence in their testimony and can be used to trip them up. This information is also harder to destroy because it is stored in the cloud.

New frameworks and tools such Zetta, Kaa and M2mLabs Mainspring are now becoming available in the market which make it easier to collect forensic information from IoT devices in a forensically sound way.

Another group is pushing for including blockchain based evidence chains into the digital and IoT forensics field to ensure that data collected can be stored in a forensically verifiable method that can’t be tampered with.

Conclusion

IoT Forensics is becoming a vital field of investigation and a major subcategory of digital forensics. With more and more devices getting connected to each other and increasing the attack surface of the target it is very important that these devices are secured and have a sound way of investigating if and when a breach happens.

Tools using Artificial Intelligence and Machine learning are being created that will allow us to leverage their capabilities to investigate breaches, attacks etc faster and more accurately.

References

Reardon. M. (2018, April 5). Your Alexa and Fitbit can testify against you in court. Retrieved from https://www.cnet.com/tech/mobile/alexa-fitbit-apple-watch-pacemaker-can-testify-against-you-in-court/.

M. Harbawi and A. Varol, “An improved digital evidence acquisition model for the Internet of Things forensic I: A theoretical framework”, Proc. 5th Int. Symp. Digit. Forensics Security (ISDFS), pp. 1-6, 2017.

Yakubu, O., Adjei, O., & Babu, N. (2016). A review of prospects and challenges of internet of things. International Journal of Computer Applications, 139(10), 33–39. https://doi.org/10.5120/ijca2016909390


Note: This was originally written as a paper for one of my classes at EC-Council University in Q4 2021, which is why the tone is a lot more formal than my regular posts.

– Suramya

January 23, 2022

Some thoughts on Crypto currencies and why it is better to hold off on investing in them

Filed under: Computer Related,My Thoughts,Tech Related — Suramya @ 1:26 AM

It seems that every other day (or every other hour if you are unlucky) someone or the other is trying to get people to use Crypto currency because they claim that it is awesome and not at all dependent on government regulations and thus won’t fluctuate that much. Famous people are pushing it, others like New York City Mayor Eric Adams are trying to raise awareness of the product and have decided to convert his first paycheck to Crypto, El Savador started accepting crypto currency as legal tender etc. However, the promises made by crypto enthusiasts don’t translate into reality as the market remains extremely volatile.

I see people posting on twitter that Crypto currencies are better because they are stable, but in my opinion if a currency can drop 20% because Elon Musk tweeted a Broken heart emoji then it is not something I want to use to store my savings. Earlier this week the entire Bitcoin market dropped over 47% from it’s high back in Nov 2021. Mayor Adams paycheck which was converted to crypto is now worth ~1/2 of what it was when he invested it, and that is a massive drop. Imagine loosing 50% of your savings in one shot. You might suddenly have no way to pay rent or emergency repairs/hospitalization etc. Even El Savador has seen its credit become 4 times worse than it was before it moved to Bitcoin. People there are complaining that the promised reduction in cost for conversion to/from international currencies is a myth as they are paying more than what they were paying earlier as transaction costs.

Another major issue with crypto currency is the ecological hit caused by the mining. According to research done by University of Cambridge, globally Bitcoin uses more power per year than the entire population of Argentina. The recent Kazakhsthan unrest and protests were sparked off due to surging fuel prices that were caused by the migration of Bitcoin miners to the country after China banned them. This caused a lot of strain on the electricity grid and required an increase in the prices which kicked off a massive protest that has caused untold no of deaths. There are multiple folks coming up with new crypto-currencies that claim to be carbon neutral but so far none of them have delivered on the promise.

Bitcoin is thought to consume 707 kwH per transaction. In addition, the computers consume additional energy because they generate heat and need to be kept cool. And while it’s impossible to know exactly how much electricity Bitcoin uses because different computers and cooling systems have varying levels of energy efficiency, a University of Cambridge analysis estimated that bitcoin mining consumes 121.36 terawatt hours a year. This is more than all of Argentina consumes, or more than the consumption of Google, Apple, Facebook and Microsoft combined.

Check out this fantastic (though very long – 2hr+) video on economic critique of NFTs, DAOs, crypto currency and web3. (H/t to Cory Doctorow)

In summary, I would recommend against investing in crypto currencies till the issues highlighted above are resolved (if they are ever resolved).

– Suramya

September 26, 2020

Source code for multiple Microsoft operating systems including Windows XP & Server 2003 leaked

Filed under: Computer Related,Tech Related — Suramya @ 5:58 PM

Windows XP & Windows Server source code leaked online earlier this week and even though this is for an operating system almost 2 decades old this leak is significant. Firstly because some of the core XP components are still in use in Windows 7/8/10. So if a major bug is found in any of those subsystems after people analyze the code then it will have a significant impact on the modern OS’s as well from Redmond. Secondly, It will give everyone a chance to try and understand how the Windows OS works so that they can enhance tools like WINE and other similar tools to have better compatibility with Windows. The other major impact will be on systems that still use XP like ATM’s, embedded systems, point-of-sale, automated teller machines, set-top boxes etc. Those will be hard to upgrade & protect as is some cases the companies that made the device are no longer in business and in other cases the software is installed in devices that are hard to upgrade.

This is not the first time Windows source code has leaked to the internet. In early 2000 a mega torrent of all MS Operating systems going back to MS-DOS was released, it allegedly contained the source code for the following OS’s:

OS from filename Alleged source size (bytes)
——————— —————————
MS-DOS 6 10,600,000
NT 3.5 101,700,000
NT 4 106,200,000
Windows 2000 122,300,000
NT 5 2,360,000,000

Leaked Data from the latest leak


Alleged contents of the Torrent file with MS Source Code.

The leaked code is available for download at most Torrent sites, I am not going to link to it for obvious reasons. If you want to check it out you can go download it, however as always be careful of what you download off the internet as it might have viruses and/or trojans in it. This is especially true if you are downloading the torrent on a Windows machine. Several users on Twitter claim that the source code for the original Xbox is included as well, but the information is varied on this. I haven’t downloaded it myself so can’t say for sure either way.

Keep in mind that the leak was illegal and just because it has leaked doesn’t mean that you can use it to build a clone of Windows XP without written authorization from Microsoft.

Source: ZDNet: Windows XP source code leaked online, on 4chan, out of all places

– Suramya

September 21, 2020

Diffblue’s Cover is an AI powered software that can write full Unit Tests for you

Writing Unit Test cases for your software is one of the most boring parts of Software Development even though having accurate tests allows us to develop code faster & with more confidence. Having a full test suite allows a developer to ensure that the changes they have made didn’t break other parts of the project that were working fine earlier. This make Unit tests an essential part of CI/CD (Continuous Integration and Continuous Delivery) pipelines. It is therefore hard to do frequent releases without rigorous unit testing. For example SQLite database engine has 640 times as much testing code as code in the engine itself:

As of version 3.33.0 (2020-08-14), the SQLite library consists of approximately 143.4 KSLOC of C code. (KSLOC means thousands of “Source Lines Of Code” or, in other words, lines of code excluding blank lines and comments.) By comparison, the project has 640 times as much test code and test scripts – 91911.0 KSLOC.

Unfortunately, since the tests are boring and don’t give immediate tangible results they are the first casualties when a team is under a time crunch for delivery. This is where Diffblue’s Cover comes into play. Diffblue was spun out of the University of Oxford following their research into how to use AI to write tests automatically. Cover uses AI to write a complete Unit Test including logic that reflects the behavior of the program as compared to the other existing tools that generate Unit Tests based on Templates and depend on the user to provide the logic for the test.

Cover has now been released as a free Community Edition for people to see what the tool can do and try it out themselves. You can download the software from here, and the full datasheet on the software is available here.


Using Cover IntelliJ plug-in to write tests

The software is not foolproof as in it doesn’t identify bugs in the source code. It assumes that the code is working correctly when the tests are added in, so if there is incorrect logic in the code it won’t be able to help you. On the other hand if the original logic was correct then it will let you know if the changes made break any of the existing functionality.

Lodge acknowledged the problem, telling us: “The code might have bugs in it to begin with, and we can’t tell if the current logic that you have in the code is correct or not, because we don’t know what the intent is of the programmer, and there’s no good way today of being able to express intent in a way that a machine could understand.

“That is generally not the problem that most of our customers have. Most of our customers have very few unit tests, and what they typically do is have a set of tests that run functional end-to-end tests that run at the end of the process.”

Lodge’s argument is that if you start with a working application, then let Cover write tests, you have a code base that becomes amenable to high velocity delivery. “Our customers don’t have any unit tests at all, or they have maybe 5 to 10 per cent coverage. Their issue is not that they can’t test their software: they can. They can run end-to-end tests that run right before they cut a release. What they don’t have are unit tests that enable them to run a CI/CD pipeline and be able to ship software every day, so typically our customers are people who can ship software twice a year.”

The software is currently only compatible with Java & IntelliJ but work is ongoing to incorporate other coding languages & IDEs.

Thanks to Theregister.com for the link to the initial story.

– Suramya

September 12, 2020

Post-Quantum Cryptography

Filed under: Computer Related,Quantum Computing,Tech Related — Suramya @ 11:29 AM

As you are aware one of the big promises of Quantum Computers is the ability to break existing Encryption algorithms in a realistic time frame. If you are not aware of this, then here’s a quick primer on Computer Security/cryptography. Basically the current security of cryptography relies on certain “hard” problems—calculations which are practically impossible to solve without the correct cryptographic key. For example it is trivial to multiply two numbers together: 593 times 829 is 491,597 but it is hard to start with the number 491,597 and work out which two prime numbers must be multiplied to produce it and it becomes increasingly difficult as the numbers get larger. Such hard problems form the basis of algorithms like the RSA that would take the best computers available billions of years to solve and all current IT security aspects are built on top of this basic foundation.

Quantum Computers use “qubits” where a single qubit is able to encode more than two states (Technically, each qubit can store a superposition of multiple states) making it possible for it to perform massively parallel computations in parallel. This makes it theoretically possible for a Quantum computer with enough qubits to break traditional encryption in a reasonable time frame. In a theoretical projection it was postulated that a Quantum Computer could break a 2048-bit RSA encryption in ~8 hours. Which as you can imagine is a pretty big deal. But there is no need to panic as this is something that is still only theoretically possible as of now.

However this is something that is coming down the line so the worlds foremost Cryptographic experts have been working on Quantum safe encryption and for the past 3 years the National Institute of Standards and Technology (NIST) has been examining new approaches to encryption and data protection. Out of the initial 69 submissions received three years ago the group narrowed the field down to 15 finalists after two rounds of reviews. NIST has now begun the third round of public review of the algorithms to help decide the core of the first post-quantum cryptography standard.

They are expecting to end the round with one or two algorithms for encryption and key establishment, and one or two others for digital signatures. To make the process easier/more manageable they have divided the finalists into two groups or tracks, with the first track containing the top 7 algorithms that are most promising and have a high probability of being suitable for wide application after the round finishes. The second track has the remaining eight algorithms which need more time to mature or are tailored to a specific application.

The third-round finalist public-key encryption and key-establishment algorithms are Classic McEliece, CRYSTALS-KYBER, NTRU, and SABER. The third-round finalists for digital signatures are CRYSTALS-DILITHIUM, FALCON, and Rainbow. These finalists will be considered for standardization at the end of the third round. In addition, eight alternate candidate algorithms will also advance to the third round: BIKE, FrodoKEM, HQC, NTRU Prime, SIKE, GeMSS, Picnic, and SPHINCS+. These additional candidates are still being considered for standardization, although this is unlikely to occur at the end of the third round. NIST hopes that the announcement of these finalists and additional candidates will serve to focus the cryptographic community’s attention during the next round.

You should check out this talk by Daniel Apon of NIST detailing the selection criteria used to classify the finalists and the full paper with technical details is available here.

Source: Schneier on Security: More on NIST’s Post-Quantum Cryptography

– Suramya

September 1, 2020

Background radiation causes Integrity issues in Quantum Computers

Filed under: Computer Related,My Thoughts,Quantum Computing,Tech Related — Suramya @ 11:16 PM

As if Quantum Computing didn’t have enough issues preventing it from being a workable solution already, new research at MIT has found that ionizing radiation from environmental radioactive materials and cosmic rays can and does interfere with the integrity of quantum computers. The research has been published in Nature: Impact of ionizing radiation on superconducting qubit coherence.

Quantum computers are super powerful because their basic building blocks qubit (quantum bit) is able to simultaneously exist as 0 or 1 (Yes, it makes no sense which is why Eisenstein called it ‘spooky action at a distance’) allowing it process a magnitude more operations in parallel than the regular computing systems. Unfortunately it appears that these qubits are highly sensitive to their environment and even minor levels of radiation emitted by trace elements in concrete walls and cosmic rays can cause them to loose coherence corrupting the calculation/data, this is called decoherence. The longer we can avoid decoherence the more powerful/capable the quantum computer. We have made significant improvements in this over the past two decades, from maintaining it for less than one nanosecond in 1999 to around 200 microseconds today for the best-performing devices.

As per the study, the effect is serious enough to limit the performance to just a few milliseconds which is something we are expected to achieve in the next few years. The only way currently known to avoid this issue is to shield the computer which means putting these computers underground and surrounding it with a 2 ton wall of lead. Another possibility is to use something like a counter-wave of radiation to cancel the incoming radiation similar to how we do noise-canceling. But that is something which doesn’t exist today and will require significant technological breakthrough before it is feasible.

“Cosmic ray radiation is hard to get rid of,” Formaggio says. “It’s very penetrating, and goes right through everything like a jet stream. If you go underground, that gets less and less. It’s probably not necessary to build quantum computers deep underground, like neutrino experiments, but maybe deep basement facilities could probably get qubits operating at improved levels.”

“If we want to build an industry, we’d likely prefer to mitigate the effects of radiation above ground,” Oliver says. “We can think about designing qubits in a way that makes them ‘rad-hard,’ and less sensitive to quasiparticles, or design traps for quasiparticles so that even if they’re constantly being generated by radiation, they can flow away from the qubit. So it’s definitely not game-over, it’s just the next layer of the onion we need to address.”

Quantum Computing is a fascinating field but it really messes with your mind. So I am happy there are folks out there spending time trying to figure out how to get this amazing invention working and reliable enough to replace our existing Bit based computers.

Source: Cosmic rays can destabilize quantum computers, MIT study warns

– Suramya

August 29, 2020

You can be identified online based on your browsing history

Filed under: Computer Related,Computer Software,My Thoughts,Tech Related — Suramya @ 7:29 PM

Reliably Identifying people online is a bedrock of the million dollar advertising industry and as more and more users become privacy conscious browsers have been adding features to increase the user’s privacy and reduce the probability of them getting identified online. Users can be identified by Cookies, Super Cookies etc etc. Now there is a research paper (Replication: Why We Still Can’t Browse in Peace: On the Uniqueness and Reidentifiability of Web Browsing Histories) that claims to be able to identify users based on their browsing histories. It is built on top of previous research Why Johnny Can’t Browse in Peace: On the Uniqueness of Web Browsing History Patterns and re-validates the findings of the previous paper and builds on top of it.

We examine the threat to individuals’ privacy based on the feasibility of reidentifying users through distinctive profiles of their browsing history visible to websites and third parties. This work replicates and

extends the 2012 paper Why Johnny Can’t Browse in Peace: On the Uniqueness of Web Browsing History Patterns[48]. The original work demonstrated that browsing profiles are highly distinctive and stable.We reproduce those results and extend the original work to detail the privacy risk posed by the aggregation of browsing histories. Our dataset consists of two weeks of browsing data from ~52,000 Firefox users. Our work replicates the original paper’s core findings by identifying 48,919 distinct browsing profiles, of which 99% are unique. High uniqueness hold seven when histories are truncated to just 100 top sites. Wethen find that for users who visited 50 or more distinct do-mains in the two-week data collection period, ~50% can be reidentified using the top 10k sites. Reidentifiability rose to over 80% for users that browsed 150 or more distinct domains.Finally, we observe numerous third parties pervasive enough to gather web histories sufficient to leverage browsing history as an identifier.

Original paper

Olejnik, Castelluccia, and Janc [48] gathered data in a project aimed at educating users about privacy practices. For the analysis presented in [48] they used the CSS :vis-ited browser vulnerability [8] to determine whether various home pages were in a user’s browsing history. That is, they probed users’ browsers for 6,000 predefined “primary links” such as www.google.com and got a yes/no for whether that home page was in the user’s browsing history. A user may have visited that home page and then cleared their browsing history, in which case they would not register a hit. Additionally a user may have visited a subpage e.g. www.google.com/maps but not www.google.com in which case the probe for www.google.com would also not register a hit. The project website was open for an extended period of time and recorded profiles between January 2009 and May 2011 for 441,627 unique users, some of whom returned for multiple history tests, allowing the researchers to study the evolution of browser profiles as well. With this data, they examined the uniqueness of browsing histories.

This brings to mind a project that I saw a few years ago that would give you a list of websites from the top 1k websites that you had visited in the past using javascript and some script-fu. Unfortunately I can’t find the link to the site right now as I don’t remember the name and a generic search is returning random sites. If I find it I will post it here as it was quite interesting.

Well this is all for now. Will post more later.

– Suramya

August 27, 2020

Optimizing the making of peanut butter and banana sandwich using computer vision and machine learning

Filed under: Computer Related,Computer Software,Tech Related — Suramya @ 12:42 AM

The current Pandemic is forcing people to stay at home depriving them of activities that kept them occupied in the past so people are getting a bit stir-crazy & bored of staying at home. Its worse for developers/engineers as you never know what will come out from the depths of a bored programmer’s mind. Case in point is the effort spent by Ethan Rosenthal in writing Machine Learning/Computer Vision code to Optimizing the coverage of the banana slices on his peanut butter & Banana sandwich so that there is the same amount of banana in every mouthful. The whole exercise took him a few months to complete and he is quite proud of the results.

It’s really quite simple. You take a picture of your banana and bread, pass the image through a deep learning model to locate said items, do some nonlinear curve fitting to the banana, transform to polar coordinates and “slice” the banana along the fitted curve, turn those slices into elliptical polygons, and feed the polygons and bread “box” into a 2D nesting algorithm
[…]
If you were a machine learning model (or my wife), then you would tell me to just cut long rectangular strips along the long axis of the banana, but I’m not a sociopath. If life were simple, then the banana slices would be perfect circles of equal diameter, and we could coast along looking up optimal configurations on packomania. But alas, life is not simple. We’re in the middle of a global pandemic, and banana slices are elliptical with varying size.

The problem of fitting arbitrary polygons (sliced circular banana pieces) in a box (the bread piece) is NP-hard so the ideal solution is practically uncomputable and Rosenthal’s solution is a good approximation of the optimal solution in a reasonable time frame. The final solution is available as a command-line package called “nannernest” which takes a photo of the bread piece & banana as its argument and returns the an optimal slice-and-arrange pattern for the given combination.


Sample output created by nannernest

Check out the code & the full writeup on the project if you are interested. Even though the application is silly it’s a good writeup on using Machine Learning & Computer Vision for a project.

Source: Boing Boing

– Suramya

August 19, 2020

Convert typed text to realistic handwriting

Filed under: Computer Related,Computer Software,Tech Related — Suramya @ 6:45 PM

There are some tools or projects that really don’t make any practical sense but are a lot of fun to use or just impressive in how they implement technology. The Handwritten.js project by ‘alias-rahil’ is one such project. Basically what it does is take any Plain Text document and convert it into a realistic looking handwritten page. I tried it out on a few sample documents (logs) and it worked great. The programs does coredump if you try converting a 5MB file, but other than that it worked as expected.

Below is a sample file with some quotes that I converted as a test :

* Mountain Dew and doughnuts… because breakfast is the most important meal of the day

* Some days you’re the dog; some days you’re the hydrant.

* He who smiles in a crisis has found someone to blame.

* Marriage is one of the chief causes of divorce

* Earth is 98% full…please delete anyone you can.

* I came, I saw, I decided to order take out.

* F U CN RD THS U CNT SPL WRTH A DM!

* Work hard for eight hours a day, and eventually you may become a
boss and be able to work twelve.

* Quitters never win, and winners never quit, but those who never quit AND never win are idiots.

* What’s the difference between a bad golfer and a bad skydiver?

A bad golfer goes, WHACK! “Damn.”
A bad skydiver goes, “Damn.” WHACK!

* Beware of the light at the end of the tunnel. It could be an oncoming train.

* A girl is like a road. The more curves she has the more dangerous she is!

* A woman who dresses to kill probably cooks the same.

The script is fast and didn’t take more than a few seconds to process the file and create a PDF file with the output. The output for my test run is as below:


Output generated by Handwritten.js

I did also try converting a word file with the software but it didn’t take the content of the file for the conversion, instead it converted the XML & Code from the file. One suggestion for improvement I have is to enhance the script to support word files. It would be awesome if it could also convert any of the diagrams, tables etc to look like they were drawn by hand.

Maybe if I have some time I will look into this and see how easy it is to enhance the script. But no promises as I have a ton of other things I need to take complete first. 🙂

Source: Hacker News

– Suramya

August 14, 2020

Updating the BIOS to address a AMD Ryzen bug

Filed under: Computer Related,Computer Software,Tech Related — Suramya @ 5:13 PM

Over the past few months I have been infrequently seeing the following warning message in the Terminal and had been ignoring it because apparently the fix was to update the BIOS and I didn’t have the patience/time to do the upgrade at that point in time:

WARNING: CPU random generator seem to be failing, disable hardware random number generation
WARNING: RDRND generated: 0xffffffff 0xffffffff 0xffffffff 0xffffffff
WARNING: CPU random generator seem to be failing, disable hardware random number generation
WARNING: RDRND generated: 0xffffffff 0xffffffff 0xffffffff 0xffffffff

Today I thought that I should fix the error, a bit of Google searching confirmed that I needed to update the BIOS because apparently there was a bug in the AMD Ryzen 3000 series processor that causes the onboard random number generator to always return 0xffffffff when asked to generate a Random number. Obviously getting the same number every time is not optimal even though Dilbert feels otherwise.


Random Number Generator in Accounting

AMD was notified about it last year and they released a BIOS update to fix the issue, however each Motherboard company had to validate and release the new BIOS which took time. The fix was to upgrade the BIOS and I really wasn’t looking forward to it as the last time I upgraded the BIOS it was a painful exercise involving floppy disks and cursing etc.

I looked up my BIOS version using the dmidecode command but that didn’t give me enough information to find the new BIOS version for my motherboard (‘ROG STRIX X570-E GAMING’). So I rebooted the computer and found the built in BIOS upgrade section under Tools. I decided to give it a try and see what options are available so I clicked on the Upgrade option and it gave me the option of connecting to the Internet and automatically downloading the latest version of the BIOS or installing it from a USB/Disk Drive. I selected the Network Install option and the system happily downloaded the latest version of the BIOS from the Internet and then gave me the option to Install the new version. I selected ‘Yes’ and the BIOS was upgraded.

The system had to reboot a few times for the upgrade to complete and there was a boot where the system played a bunch of beeps without anything coming up on the display which scared the life out of me but then it immediately rebooted and the display came back. After the upgrade completed I got a screen with a bunch of messages about BIOS settings needing to be reinitialized but when I went into the BIOS the settings were all there. So I rebooted and now all looks good and I don’t see any more weird error messages in the Console or the logs.

I am happy to see that the process to upgrade the BIOS is now so simple and I will be upgrading the BIOS more frequently going forward.

– Suramya

Older Posts »

Powered by WordPress