Wish you more bang for your buck

By ‘Cost a Bomb’ I didn’t mean to exaggerate. It’s an idiom that means ‘To be very expensive’. In fact, no app on the planet costs a bomb lol.

So, to the point.

Chronicle

(Freemium. For Pro, $24.99 | Available on Setapp)

You probably have trouble keeping track of dozens of bills and subscriptions each month.

Try Chronicle.

Easy-to-use app

• Add payment due dates and receive reminders,

• Save payment documentation,

• Analyze your spending by season, year, and month.

• Observe expenditure trends and create new budgets.

Best of all, Chronicle features an integrated browser for fast payment and logging.

iOS and macOS sync.

SoundSource

($39 for lifetime)

Background Music, a free macOS program, was featured in #6 of this post last month.

It controls per-app volume, stereo balance, and audio over its max level.

Background Music is fully supported. Additionally,

• Connect various speakers to various apps (Wow! ),

• change the audio sample rate for each app,

• To facilitate access, add a floating SoundSource window.

• Use its blocks in Shortcuts app,

• On the menu bar, include meters for output/input devices and running programs.

PixelSnap

($39 for lifetime | Available on Setapp)

This software is heaven for UI designers.

It aids you.

• quickly calculate screen distances (in pixels) ,

• Drag an area around an object to determine its borders,

• Measure the distances between the additional guides,

• screenshots should be pixel-perfect.

What’s more.

You can

• Adapt your tolerance for items with poor contrast and shadows.

• Use your Touch Bar to perform important tasks, if you have one.

Mate Translation

($3.99 a month / $29.99 a year | Available on Setapp)

Mate Translate resembles a roided-up version of BarTranslate, which I wrote about in #1 of this piece last month.

If you translate often, utilize Mate Translate on macOS and Safari.

I'm really vocal about it.

It stays on the menu bar, and is accessible with a click or ⌥+shift+T hotkey.

It lets you

• Translate in 103 different languages,

• To translate text, double-click or right-click on it.

• Totally translate websites. Additionally, Netflix subtitles,

• Listen to their pronunciation to see how close it is to human.

iPhone and Mac sync Mate-ing history.

Swish

($16 for lifetime | Available on Setapp)

Swish is awesome!

Swipe, squeeze, tap, and hold movements organize chaotic desktop windows. Swish operates with mouse and trackpad.

Some gestures:

• Pinch Once: Close an app
• Pinch Twice: Quit an app
• Swipe down once: Minimise an app
• Pinch Out: Enter fullscreen mode
• Tap, Hold, & Swipe: Arrange apps in grids
and many more...

After getting acquainted to the movements, your multitasking will improve.

Unite

($24.99 for lifetime | Available on Setapp)

It turns webapps into macOS apps. The end.

Unite's functionality is a million times better.

• Provide extensive customization (incl. its icon, light and dark modes)

• make menu bar applications,

• Get badges for web notifications and automatically refresh websites,

• Replace any dock icon in the window with it (Wow!) by selecting that portion of the window.

• Use PiP (Picture-in-Picture) on video sites that support it.

• Delete advertising,

• Throughout macOS, use floating windows

and many more…

I feel $24.99 one-off for this tool is a great deal, considering all these features. What do you think?

https://www.bzgapps.com/unite

CleanShot X

(Basic: $29 one-off. Pro: $8/month | Available on Setapp)

CleanShot X can achieve things the macOS screenshot tool cannot. Complete screenshot toolkit.

CleanShot X, like Pixel Snap 2 (#3), is fantastic.

Allows

• Scroll to capture a long page,

• screen recording,

  With webcam on,
• With mic and system audio,
• Highlighting mouse clicks and hotkeys.

• Maintain floating screenshots for reference

• While capturing, conceal desktop icons and notifications.

• Recognize text in screenshots (OCR),

• You may upload and share screenshots using the built-in cloud.

These are just 6 in 50+ features, and you’re already saying Wow!

Recent investigations have shown that generative AI can boost hackers and misinformation spreaders.

Since its inception in late November 2022, OpenAI's ChatGPT has entertained and assisted many online users in writing, coding, task automation, and linguistic translation. Given this versatility, it is maybe unsurprising but nonetheless regrettable that fraudsters and mis-, dis-, and malinformation (MDM) spreaders are also considering ChatGPT and related AI models to streamline and improve their operations.

Malign actors may benefit from ChatGPT, according to a WithSecure research. ChatGPT promises to elevate unlawful operations across many attack channels. ChatGPT can automate spear phishing attacks that deceive corporate victims into reading emails from trusted parties. Malware, extortion, and illicit fund transfers can result from such access.

ChatGPT's ability to simulate a desired writing style makes spear phishing emails look more genuine, especially for international actors who don't speak English (or other languages like Spanish and French).

This technique could let Russian, North Korean, and Iranian state-backed hackers conduct more convincing social engineering and election intervention in the US. ChatGPT can also create several campaigns and various phony online personas to promote them, making such attacks successful through volume or variation. Additionally, image-generating AI algorithms and other developing techniques can help these efforts deceive potential victims.

Hackers are discussing using ChatGPT to install malware and steal data, according to a Check Point research. Though ChatGPT's scripts are well-known in the cyber security business, they can assist amateur actors with little technical understanding into the field and possibly develop their hacking and social engineering skills through repeated use.

Additionally, ChatGPT's hacking suggestions may change. As a writer recently indicated, ChatGPT's ability to blend textual and code-based writing might be a game-changer, allowing the injection of innocent content that would subsequently turn out to be a malicious script into targeted systems. These new AI-powered writing- and code-generation abilities allow for unique cyber attacks, regardless of viability.

OpenAI fears ChatGPT usage. OpenAI, Georgetown University's Center for Security and Emerging Technology, and Stanford's Internet Observatory wrote a paper on how AI language models could enhance nation state-backed influence operations. As a last resort, the authors consider polluting the internet with radioactive or misleading data to ensure that AI language models produce outputs that other language models can identify as AI-generated. However, the authors of this paper seem unaware that their "solution" might cause much worse MDM difficulties.

Literally False News

The public argument about ChatGPTs content-generation has focused on originality, bias, and academic honesty, but broader global issues are at stake. ChatGPT can influence public opinion, troll individuals, and interfere in local and national elections by creating and automating enormous amounts of social media material for specified audiences.

ChatGPT's capacity to generate textual and code output is crucial. ChatGPT can write Python scripts for social media bots and give diverse content for repeated posts. The tool's sophistication makes it irrelevant to one's language skills, especially English, when writing MDM propaganda.

I ordered ChatGPT to write a news piece in the style of big US publications declaring that Ukraine is on the verge of defeat in its fight against Russia due to corruption, desertion, and exhaustion in its army. I also gave it a fake reporter's byline and an unidentified NATO source's remark. The outcome appears convincing:

Worse, terrible performers can modify this piece to make it more credible. They can edit the general's name or add facts about current wars. Furthermore, such actors can create many versions of this report in different forms and distribute them separately, boosting its impact.

In this example, ChatGPT produced a news story regarding (fictional) greater moviegoer fatality rates:

Editing this example makes it more plausible. Dr. Jane Smith, the putative author of the medical report, might be replaced with a real-life medical person or a real victim of this supposed medical hazard.

Can deceptive texts be found? Detecting AI text is behind AI advancements. Minor AI-generated text alterations can upset these technologies.

Some OpenAI individuals have proposed covert methods to watermark AI-generated literature to prevent its abuse. AI models would create information that appears normal to humans but would follow a cryptographic formula that would warn other machines that it was AI-made. However, security experts are cautious since manually altering the content interrupts machine and human detection of AI-generated material.

How to Prepare

Cyber security and IT workers can research and use generative AI models to fight spear fishing and extortion. Governments may also launch MDM-defence projects.

In election cycles and global crises, regular people may be the most vulnerable to AI-produced deceit. Until regulation or subsequent technical advances, individuals must recognize exposure to AI-generated fraud, dating scams, other MDM activities.

A three-step verification method of new material in suspicious emails or social media posts can help identify AI content and manipulation. This three-step approach asks about the information's distribution platform (is it reliable? ), author (is the reader familiar with them? ), and plausibility given one's prior knowledge of the topic.

Consider a report by a trusted journalist that makes shocking statements in their typical manner. AI-powered fake news may be released on an unexpected platform, such as a newly created Facebook profile. However, if it links to a known media source, it is more likely to be real.

Though hard and subjective, this verification method may be the only barrier against manipulation for now.

AI language models:

How to Recognize an AI-Generated Article ChatGPT, the popular AI-powered chatbot, can and likely does generate medium.com-style articles.

AI-Generated Text Detectors Fail. Do This. Online tools claim to detect ChatGPT output. Even with superior programming, I tested some of these tools. pub

Why Original Writers Matter Despite AI Language Models Creative writers may never be threatened by AI language models.

Few sentences can have global significance.

Ethan Zuckerman invented the pop-up commercial in 1997.

He was working for Tripod.com, an online service that let people make little web pages for free. Tripod offered advertising to make money. Advertisers didn't enjoy seeing their advertising next to filthy content, like a user's anal sex website.

Zuckerman's boss wanted a solution. Wasn't there a way to move the ads away from user-generated content?

When you visited a Tripod page, a pop-up ad page appeared. So, the ad isn't officially tied to any user page. It'd float onscreen.

Here’s the thing, though: Zuckerman’s bit of Javascript, that created the popup ad? It was incredibly short — a single line of code:

window.open('http://tripod.com/navbar.html'
"width=200, height=400, toolbar=no, scrollbars=no, resizable=no, target=_top");

Javascript tells the browser to open a 200-by-400-pixel window on top of any other open web pages, without a scrollbar or toolbar.

Simple yet harmful! Soon, commercial websites mimicked Zuckerman's concept, infesting the Internet with pop-up advertising. In the early 2000s, a coder for a download site told me that most of their revenue came from porn pop-up ads.

Pop-up advertising are everywhere. You despise them. Hopefully, your browser blocks them.

Zuckerman wrote a single line of code that made the world worse.

I read Zuckerman's story in How 26 Lines of Code Changed the World. Torie Bosch compiled a humorous anthology of short writings about code that tipped the world.

Most of these samples are quite short. Pop-cultural preconceptions about coding say that important code is vast and expansive. Hollywood depicts programmers as blurs spouting out Niagaras of code. Google's success was formerly attributed to its 2 billion lines of code.

It's usually not true. Google's original breakthrough, the piece of code that propelled Google above its search-engine counterparts, was its PageRank algorithm, which determined a web page's value based on how many other pages connected to it and the quality of those connecting pages. People have written their own Python versions; it's only a few dozen lines.

Google's operations, like any large tech company's, comprise thousands of procedures. So their code base grows. The most impactful code can be brief.

The examples are fascinating and wide-ranging, so read the whole book (or give it to nerds as a present). Charlton McIlwain wrote a chapter on the police beat algorithm developed in the late 1960s to anticipate crime hotspots so law enforcement could dispatch more officers there. It created a racial feedback loop. Since poor Black neighborhoods were already overpoliced compared to white ones, the algorithm directed more policing there, resulting in more arrests, which convinced it to send more police; rinse and repeat.

Kelly Chudler's You Are Not Expected To Understand This depicts the police-beat algorithm.

Even shorter code changed the world: the tracking pixel.

Lily Hay Newman's chapter on monitoring pixels says you probably interact with this code every day. It's a snippet of HTML that embeds a single tiny pixel in an email. Getting an email with a tracking code spies on me. As follows: My browser requests the single-pixel image as soon as I open the mail. My email sender checks to see if Clives browser has requested that pixel. My email sender can tell when I open it.

Adding a tracking pixel to an email is easy:

<img src="URL LINKING TO THE PIXEL ONLINE" width="0" height="0">

An older example: Ellen R. Stofan and Nick Partridge wrote a chapter on Apollo 11's lunar module bailout code. This bailout code operated on the lunar module's tiny on-board computer and was designed to prioritize: If the computer grew overloaded, it would discard all but the most vital work.

When the lunar module approached the moon, the computer became overloaded. The bailout code shut down anything non-essential to landing the module. It shut down certain lunar module display systems, scaring the astronauts. Module landed safely.

22-line code

POODOO    INHINT
    CA  Q
    TS  ALMCADR

    TC  BANKCALL
    CADR  VAC5STOR  # STORE ERASABLES FOR DEBUGGING PURPOSES.

    INDEX  ALMCADR
    CAF  0
ABORT2    TC  BORTENT

OCT77770  OCT  77770    # DONT MOVE
    CA  V37FLBIT  # IS AVERAGE G ON
    MASK  FLAGWRD7
    CCS  A
    TC  WHIMPER -1  # YES.  DONT DO POODOO.  DO BAILOUT.

    TC  DOWNFLAG
    ADRES  STATEFLG

    TC  DOWNFLAG
    ADRES  REINTFLG

    TC  DOWNFLAG
    ADRES  NODOFLAG

    TC  BANKCALL
    CADR  MR.KLEAN
    TC  WHIMPER

This fun book is worth reading.

I'm a contributor to the New York Times Magazine, Wired, and Mother Jones. I've also written Coders: The Making of a New Tribe and the Remaking of the World and Smarter Than You Think: How Technology is Changing Our Minds. Twitter and Instagram: @pomeranian99; Mastodon: @clive@saturation.social.

The Merge cut Ethereum's energy use by 99.5%.

The Crypto community celebrated on September 15, 2022. This day, Ethereum Merged. The entire blockchain successfully merged with the Beacon chain, and it was so smooth you barely noticed.

Many have waited, dreaded, and longed for this day.

Some investors feared the network would break down, while others envisioned a seamless merging.

Speculators predict a successful Merge will lead investors to Ethereum. This could boost Ethereum's popularity.

What Has Changed Since The Merge

The merging transitions Ethereum mainnet from PoW to PoS.

PoW sends a mathematical riddle to computers worldwide (miners). First miner to solve puzzle updates blockchain and is rewarded.

The puzzles sent are power-intensive to solve, so mining requires a lot of electricity. It's sent to every miner competing to solve it, requiring duplicate computation.

PoS allows investors to stake their coins to validate a new transaction. Instead of validating a whole block, you validate a transaction and get the fees.

You can validate instead of mine. A validator stakes 32 Ethereum. After staking, the validator can validate future blocks.

Once a validator validates a block, it's sent to a randomly selected group of other validators. This group verifies that a validator is not malicious and doesn't validate fake blocks.

This way, only one computer needs to solve or validate the transaction, instead of all miners. The validated block must be approved by a small group of validators, causing duplicate computation.

PoS is more secure because validating fake blocks results in slashing. You lose your bet tokens. If a validator signs a bad block or double-signs conflicting blocks, their ETH is burned.

Theoretically, Ethereum has one block every 12 seconds, so a validator forging a block risks burning 1 Ethereum for 12 seconds of transactions. This makes mistakes expensive and risky.

What Impact Does This Have On Energy Use?

Cryptocurrency is a natural calamity, sucking electricity and eating away at the earth one transaction at a time.

Many don't know the environmental impact of cryptocurrencies, yet it's tremendous.

A single Ethereum transaction used to use 200 kWh and leave a large carbon imprint. This update reduces global energy use by 0.2%.

Ethereum will submit a challenge to one validator, and that validator will forward it to randomly selected other validators who accept it.

This reduces the needed computing power.

They expect a 99.5% reduction, therefore a single transaction should cost 1 kWh.

Carbon footprint is 0.58 kgCO2, or 1,235 VISA transactions.

This is a big Ethereum blockchain update.

I love cryptocurrency and Mother Earth.

Do you want to build and launch your own software company? To do this, all you need is a product that solves a problem.

Coming up with profitable ideas is not that easy. But you’re in luck because you got me!

I’ll give you the idea for free. All you need to do is execute it properly.

If you’re ready, let’s jump right into it! Starting with the problem.

Problem

Youtube has many creators. Every day, they think of new ways to entertain or inform us.

They work hard to make videos. Many of their efforts go to waste. They limit their revenue and reach.

Solution

Content repurposing solves this problem.

One video can become several TikToks. Creating YouTube videos from a podcast episode.

Or, one video might become a blog entry.

By turning videos into blog entries, Youtubers may develop evergreen SEO content, attract a new audience, and reach a non-YouTube audience.

Many YouTube creators want this easy feature.

Let's build it!

Implementation

We identified the problem, and we have a solution. All that’s left to do is see how it can be done.

Monitoring new video uploads

First, watch when a friend uploads a new video. Everything should happen automatically without user input.

YouTube Webhooks make this easy. Our server listens for YouTube Webhook notifications.

After publishing a new video, we create a conversion job.

Creating a Blog Post from a Video

Next, turn a video into a blog article.

To convert, we must extract the video's audio (which can be achieved by using FFmpeg on the server).

Once we have the audio channel, we can use speech-to-text.

Services can accomplish this easily.

• Speech-to-text on Google

• Google Translate

• Deepgram

Deepgram's affordability and integration make it my pick.

After conversion, the blog post needs formatting, error checking, and proofreading.

After this, a new blog post will appear in our web app's dashboard.

Completing a blog post

After conversion, users must examine and amend their blog posts.

Our application dashboard would handle all of this. It's a dashboard-style software where users can:

• Link their Youtube account

• Check out the converted videos in the future.

• View the conversions that are ongoing.

• Edit and format converted blog articles.

It's a web-based app.

It doesn't matter how it's made but I'd choose Next.js.

Next.js is a React front-end standard. Vercel serverless functions could conduct the conversions.

This would let me host the software for free and reduce server expenditures.

Taking It One Step Further

SaaS in a nutshell. Future improvements include integrating with WordPress or Ghost.

Our app users could then publish blog posts. Streamlining the procedure.

MVPs don't need this functionality.

Final Thoughts

Repurposing content helps you post more often, reach more people, and develop faster.

Many agencies charge a fortune for this service. Handmade means pricey.

Content creators will go crazy if you automate and cheaply solve this problem.

Just execute this idea!

Key Takeaways:

Another hack. This time was different. This is a doozy.

Why? Nomad got exploited for $190m. It was crypto's 5th-biggest hack. Ouch.

It wasn't hackers, but random folks. What happened:

A Nomad smart contract flaw was discovered. They couldn't drain the funds at once, so they tried numerous transactions. Rookie!

People noticed and copied the attack.

They just needed to discover a working transaction, substitute the other person's address with theirs, and run it.

In a two-and-a-half-hour attack, $190M was siphoned from Nomad Bridge.

Nomad is a novel approach to blockchain interoperability that leverages an optimistic mechanism to increase the security of cross-chain communication.  — nomad.xyz

This hack was permissionless, therefore anyone could participate.

After the fatal blow, people fought over the scraps.

Cross-chain bridges remain a DeFi weakness and exploit target. When they collapse, it's typically total.

$190M...gobbled.

Unbacked assets are hurting Nomad-dependent chains. Moonbeam, EVMOS, and Milkomeda's TVLs dropped.

This incident is every-man-for-himself, although numerous whitehats exploited the issue... 

But what triggered the feeding frenzy?

How did so many pick the bones?

After a normal upgrade in June, the bridge's Replica contract was initialized with a severe security issue. The  0x00 address was a trusted root, therefore all messages were valid by default.

After a botched first attempt (costing $350k in gas), the original attacker's exploit tx called process() without first 'proving' its validity.

The process() function executes all cross-chain messages and checks the merkle root of all messages (line 185).

The upgrade caused transactions with a'messages' value of 0 (invalid, according to old logic) to be read by default as 0x00, a trusted root, passing validation as 'proven'

Any process() calls were valid. In reality, a more sophisticated exploiter may have designed a contract to drain the whole bridge.

Copycat attackers simply copied/pasted the same process() function call using Etherscan, substituting their address.

The incident was a wild combination of crowdhacking, whitehat activities, and MEV-bot (Maximal Extractable Value) mayhem.

For example, 🍉🍉🍉. eth stole $4M from the bridge, but claims to be whitehat.

Others stood out for the wrong reasons. Repeat criminal Rari Capital (Artibrum) exploited over $3M in stablecoins, which moved to Tornado Cash.

The top three exploiters (with 95M between them) are:

$47M: 0x56D8B635A7C88Fd1104D23d632AF40c1C3Aac4e3

$40M: 0xBF293D5138a2a1BA407B43672643434C43827179

$8M: 0xB5C55f76f90Cc528B2609109Ca14d8d84593590E

Here's a list of all the exploiters:

The project conducted a Quantstamp audit in June; QSP-19 foreshadowed a similar problem.

The auditor's comments that "We feel the Nomad team misinterpreted the issue" speak to a troubling attitude towards security that the project's "Long-Term Security" plan appears to confirm:

Concerns were raised about the team's response time to a live, public exploit; the team's official acknowledgement came three hours later.

"Removing the Replica contract as owner" stopped the exploit, but it was too late to preserve the cash.

Closed blockchain systems are only as strong as their weakest link.

The Harmony network is in turmoil after its bridge was attacked and lost $100M in late June.

What's next for Nomad's ecosystems?

Moonbeam's TVL is now $135M, EVMOS's is $3M, and Milkomeda's is $20M.

Loss of confidence may do more damage than $190M.

Cross-chain infrastructure is difficult to secure in a new, experimental sector. Bridge attacks can pollute an entire ecosystem or more.

Nomadic liquidity has no permanent home, so consumers will always migrate in pursuit of the "next big thing" and get stung when attentiveness wanes.

DeFi still has easy prey...

Sources: rekt.news & The Milk Road.