More on Web3 & Crypto

rekt
3 years ago
LCX is the latest CEX to have suffered a private key exploit.
The attack began around 10:30 PM +UTC on January 8th.
Peckshield spotted it first, then an official announcement came shortly after.
We’ve said it before; if established companies holding millions of dollars of users’ funds can’t manage their own hot wallet security, what purpose do they serve?
The Unique Selling Proposition (USP) of centralised finance grows smaller by the day.
The official incident report states that 7.94M USD were stolen in total, and that deposits and withdrawals to the platform have been paused.
LCX hot wallet: 0x4631018f63d5e31680fb53c11c9e1b11f1503e6f
Hacker’s wallet: 0x165402279f2c081c54b00f0e08812f3fd4560a05
Stolen funds:
- 162.68 ETH (502,671 USD)
- 3,437,783.23 USDC (3,437,783 USD)
- 761,236.94 EURe (864,840 USD)
- 101,249.71 SAND Token (485,995 USD)
- 1,847.65 LINK (48,557 USD)
- 17,251,192.30 LCX Token (2,466,558 USD)
- 669.00 QNT (115,609 USD)
- 4,819.74 ENJ (10,890 USD)
- 4.76 MKR (9,885 USD)
**~$1M worth of $LCX remains in the address, along with 611k EURe which has been frozen by Monerium.
The rest, a total of 1891 ETH (~$6M) was sent to Tornado Cash.**
Why can’t they keep private keys private?
Is it really that difficult for a traditional corporate structure to maintain good practice?
CeFi hacks leave us with little to say - we can only go on what the team chooses to tell us.
Next time, they can write this article themselves.
See below for a template.

Vitalik
3 years ago
An approximate introduction to how zk-SNARKs are possible (part 1)
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has 2 very powerful applications: Perhaps the most powerful cryptographic technology to come out of the last decade is general-purpose succinct zero knowledge proofs, usually called zk-SNARKs ("zero knowledge succinct arguments of knowledge"). A zk-SNARK allows you to generate a proof that some computation has some particular output, in such a way that the proof can be verified extremely quickly even if the underlying computation takes a very long time to run. The "ZK" part adds an additional feature: the proof can keep some of the inputs to the computation hidden.
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has two very powerful applications:
- Scalability: if a block takes a long time to verify, one person can verify it and generate a proof, and everyone else can just quickly verify the proof instead
- Privacy: you can prove that you have the right to transfer some asset (you received it, and you didn't already transfer it) without revealing the link to which asset you received. This ensures security without unduly leaking information about who is transacting with whom to the public.
But zk-SNARKs are quite complex; indeed, as recently as in 2014-17 they were still frequently called "moon math". The good news is that since then, the protocols have become simpler and our understanding of them has become much better. This post will try to explain how ZK-SNARKs work, in a way that should be understandable to someone with a medium level of understanding of mathematics.
Why ZK-SNARKs "should" be hard
Let us take the example that we started with: we have a number (we can encode "cow" followed by the secret input as an integer), we take the SHA256 hash of that number, then we do that again another 99,999,999 times, we get the output, and we check what its starting digits are. This is a huge computation.
A "succinct" proof is one where both the size of the proof and the time required to verify it grow much more slowly than the computation to be verified. If we want a "succinct" proof, we cannot require the verifier to do some work per round of hashing (because then the verification time would be proportional to the computation). Instead, the verifier must somehow check the whole computation without peeking into each individual piece of the computation.
One natural technique is random sampling: how about we just have the verifier peek into the computation in 500 different places, check that those parts are correct, and if all 500 checks pass then assume that the rest of the computation must with high probability be fine, too?
Such a procedure could even be turned into a non-interactive proof using the Fiat-Shamir heuristic: the prover computes a Merkle root of the computation, uses the Merkle root to pseudorandomly choose 500 indices, and provides the 500 corresponding Merkle branches of the data. The key idea is that the prover does not know which branches they will need to reveal until they have already "committed to" the data. If a malicious prover tries to fudge the data after learning which indices are going to be checked, that would change the Merkle root, which would result in a new set of random indices, which would require fudging the data again... trapping the malicious prover in an endless cycle.
But unfortunately there is a fatal flaw in naively applying random sampling to spot-check a computation in this way: computation is inherently fragile. If a malicious prover flips one bit somewhere in the middle of a computation, they can make it give a completely different result, and a random sampling verifier would almost never find out.
It only takes one deliberately inserted error, that a random check would almost never catch, to make a computation give a completely incorrect result.
If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? There is a clever solution.
see part 2

CyberPunkMetalHead
3 years ago
Developed an automated cryptocurrency trading tool for nearly a year before unveiling it this month.
Overview
I'm happy to provide this important update. We've worked on this for a year and a half, so I'm glad to finally write it. We named the application AESIR because we’ve love Norse Mythology. AESIR automates and runs trading strategies.
Volatility, technical analysis, oscillators, and other signals are currently supported by AESIR.
Additionally, we enhanced AESIR's ability to create distinctive bespoke signals by allowing it to analyze many indicators and produce a single signal.
AESIR has a significant social component that allows you to copy the best-performing public setups and use them right away.
Enter your email here to be notified when AEISR launches.
Views on algorithmic trading
First, let me clarify. Anyone who claims algorithmic trading platforms are money-printing plug-and-play devices is a liar. Algorithmic trading platforms are a collection of tools.
A trading algorithm won't make you a competent trader if you lack a trading strategy and yolo your funds without testing. It may hurt your trade. Test and alter your plans to account for market swings, but comprehend market signals and trends.
Status Report
Throughout closed beta testing, we've communicated closely with users to design a platform they want to use.
To celebrate, we're giving you free Aesir Viking NFTs and we cover gas fees.
Why use a trading Algorithm?
Automating a successful manual approach
experimenting with and developing solutions that are impossible to execute manually
One AESIR strategy lets you buy any cryptocurrency that rose by more than x% in y seconds.
AESIR can scan an exchange for coins that have gained more than 3% in 5 minutes. It's impossible to manually analyze over 1000 trading pairings every 5 minutes. Auto buy dips or DCA around a Dip
Sneak Preview
Here's the Leaderboard, where you can clone the best public settings.
As a tiny, self-funded team, we're excited to unveil our product. It's a beta release, so there's still more to accomplish, but we know where we stand.
If this sounds like a project that you might want to learn more about, you can sign up to our newsletter and be notified when AESIR launches.
Useful Links:
Join the Discord | Join our subreddit | Newsletter | Mint Free NFT
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Will Lockett
3 years ago
Thanks to a recent development, solar energy may prove to be the best energy source.
Perovskite solar cells will revolutionize everything.
Humanity is in a climatic Armageddon. Our widespread ecological crimes of the previous century are catching up with us, and planet-scale karma threatens everyone. We must adjust to new technologies and lifestyles to avoid this fate. Even solar power, a renewable energy source, has climate problems. A recent discovery could boost solar power's eco-friendliness and affordability. Perovskite solar cells are amazing.
Perovskite is a silicon-like semiconductor. Semiconductors are used to make computer chips, LEDs, camera sensors, and solar cells. Silicon makes sturdy and long-lasting solar cells, thus it's used in most modern solar panels.
Perovskite solar cells are far better. First, they're easy to make at room temperature, unlike silicon cells, which require long, intricate baking processes. This makes perovskite cells cheaper to make and reduces their carbon footprint. Perovskite cells are efficient. Most silicon panel solar farms are 18% efficient, meaning 18% of solar radiation energy is transformed into electricity. Perovskite cells are 25% efficient, making them 38% more efficient than silicon.
However, perovskite cells are nowhere near as durable. A normal silicon panel will lose efficiency after 20 years. The first perovskite cells were ineffective since they lasted barely minutes.
Recent research from Princeton shows that perovskite cells can endure 30 years. The cells kept their efficiency, therefore no sacrifices were made.
No electrical or chemical engineer here, thus I can't explain how they did it. But strangely, the team said longevity isn't the big deal. In the next years, perovskite panels will become longer-lasting. How do you test a panel if you only have a month or two? This breakthrough technique needs a uniform method to estimate perovskite life expectancy fast. The study's key milestone was establishing a standard procedure.
Lab-based advanced aging tests are their solution. Perovskite cells decay faster at higher temperatures, so scientists can extrapolate from that. The test heated the panel to 110 degrees and waited for its output to reduce by 20%. Their panel lasted 2,100 hours (87.5 days) before a 20% decline.
They did some math to extrapolate this data and figure out how long the panel would have lasted in different climates, and were shocked to find it would last 30 years in Princeton. This made perovskite panels as durable as silicon panels. This panel could theoretically be sold today.
This technology will soon allow these brilliant panels to be released into the wild. This technology could be commercially viable in ten, maybe five years.
Solar power will be the best once it does. Solar power is cheap and low-carbon. Perovskite is the cheapest renewable energy source if we switch to it. Solar panel manufacturing's carbon footprint will also drop.
Perovskites' impact goes beyond cost and carbon. Silicon panels require harmful mining and contain toxic elements (cadmium). Perovskite panels don't require intense mining or horrible materials, making their production and expiration more eco-friendly.
Solar power destroys habitat. Massive solar farms could reduce biodiversity and disrupt local ecology by destroying vital habitats. Perovskite cells are more efficient, so they can shrink a solar farm while maintaining energy output. This reduces land requirements, making perovskite solar power cheaper, and could reduce solar's environmental impact.
Perovskite solar power is scalable and environmentally friendly. Princeton scientists will speed up the development and rollout of this energy.
Why bother with fusion, fast reactors, SMRs, or traditional nuclear power? We're close to developing a nearly perfect environmentally friendly power source, and we have the tools and systems to do so quickly. It's also affordable, so we can adopt it quickly and let the developing world use it to grow. Even I struggle to justify spending billions on fusion when a great, cheap technology outperforms it. Perovskite's eco-credentials and cost advantages could save the world and power humanity's future.

Gajus Kuizinas
3 years ago
How a few lines of code were able to eliminate a few million queries from the database
I was entering tens of millions of records per hour when I first published Slonik PostgreSQL client for Node.js. The data being entered was usually flat, making it straightforward to use INSERT INTO ... SELECT * FROM unnset() pattern. I advocated the unnest approach for inserting rows in groups (that was part I).
However, today I’ve found a better way: jsonb_to_recordset.
jsonb_to_recordsetexpands the top-level JSON array of objects to a set of rows having the composite type defined by an AS clause.
jsonb_to_recordset allows us to query and insert records from arbitrary JSON, like unnest. Since we're giving JSON to PostgreSQL instead of unnest, the final format is more expressive and powerful.
SELECT *
FROM json_to_recordset('[{"name":"John","tags":["foo","bar"]},{"name":"Jane","tags":["baz"]}]')
AS t1(name text, tags text[]);
name | tags
------+-----------
John | {foo,bar}
Jane | {baz}
(2 rows)Let’s demonstrate how you would use it to insert data.
Inserting data using json_to_recordset
Say you need to insert a list of people with attributes into the database.
const persons = [
{
name: 'John',
tags: ['foo', 'bar']
},
{
name: 'Jane',
tags: ['baz']
}
];You may be tempted to traverse through the array and insert each record separately, e.g.
for (const person of persons) {
await pool.query(sql`
INSERT INTO person (name, tags)
VALUES (
${person.name},
${sql.array(person.tags, 'text[]')}
)
`);
}It's easier to read and grasp when working with a few records. If you're like me and troubleshoot a 2M+ insert query per day, batching inserts may be beneficial.
What prompted the search for better alternatives.
Inserting using unnest pattern might look like this:
await pool.query(sql`
INSERT INTO public.person (name, tags)
SELECT t1.name, t1.tags::text[]
FROM unnest(
${sql.array(['John', 'Jane'], 'text')},
${sql.array(['{foo,bar}', '{baz}'], 'text')}
) AS t1.(name, tags);
`);You must convert arrays into PostgreSQL array strings and provide them as text arguments, which is unsightly. Iterating the array to create slices for each column is likewise unattractive.
However, with jsonb_to_recordset, we can:
await pool.query(sql`
INSERT INTO person (name, tags)
SELECT *
FROM jsonb_to_recordset(${sql.jsonb(persons)}) AS t(name text, tags text[])
`);In contrast to the unnest approach, using jsonb_to_recordset we can easily insert complex nested data structures, and we can pass the original JSON document to the query without needing to manipulate it.
In terms of performance they are also exactly the same. As such, my current recommendation is to prefer jsonb_to_recordset whenever inserting lots of rows or nested data structures.

The woman
3 years ago
Why Google's Hiring Process is Brilliant for Top Tech Talent
Without a degree and experience, you can get a high-paying tech job.
Most organizations follow this hiring rule: you chat with HR, interview with your future boss and other senior managers, and they make the final hiring choice.
If you've ever applied for a job, you know how arduous it can be. A newly snapped photo and a glossy resume template can wear you out. Applying to Google can change this experience.
According to an Universum report, Google is one of the world's most coveted employers. It's not simply the search giant's name and reputation that attract candidates, but its role requirements or lack thereof.
Candidates no longer need a beautiful resume, cover letter, Ivy League laurels, or years of direct experience. The company requires no degree or experience.
Elon Musk started it. He employed the two-hands test to uncover talented non-graduates. The billionaire eliminated the requirement for experience.
Google is deconstructing traditional employment with programs like the Google Project Management Degree, a free online and self-paced professional credential course.
Google's hiring is interesting. After its certification course, applicants can work in project management. Instead of academic degrees and experience, the company analyzes coursework.
Google finds the best project managers and technical staff in exchange. Google uses three strategies to find top talent.
Chase down the innovators
Google eliminates restrictions like education, experience, and others to find the polar bear amid the snowfall. Google's free project management education makes project manager responsibilities accessible to everyone.
Many jobs don't require a degree. Overlooking individuals without a degree can make it difficult to locate a candidate who can provide value to a firm.
Firsthand knowledge follows the same rule. A lack of past information might be an employer's benefit. This is true for creative teams or businesses that prefer to innovate.
Or when corporations conduct differently from the competition. No-experience candidates can offer fresh perspectives. Fast Company reports that people with no sales experience beat those with 10 to 15 years of experience.
Give the aptitude test first priority.
Google wants the best candidates. Google wouldn't be able to receive more applications if it couldn't screen them for fit. Its well-organized online training program can be utilized as a portfolio.
Google learns a lot about an applicant through completed assignments. It reveals their ability, leadership style, communication capability, etc. The course mimics the job to assess candidates' suitability.
Basic screening questions might provide information to compare candidates. Any size small business can use screening questions and test projects to evaluate prospective employees.
Effective training for employees
Businesses must train employees regardless of their hiring purpose. Formal education and prior experience don't guarantee success. Maintaining your employees' professional knowledge gaps is key to their productivity and happiness. Top-notch training can do that. Learning and development are key to employee engagement, says Bob Nelson, author of 1,001 Ways to Engage Employees.
Google's online certification program isn't available everywhere. Improving the recruiting process means emphasizing aptitude over experience and a degree. Instead of employing new personnel and having them work the way their former firm trained them, train them how you want them to function.
If you want to know more about Google’s recruiting process, we recommend you watch the movie “Internship.”