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Confessions of a Scambaiter, Part I (Global Anti-scam Org)
Confessions of a Scambaiter, Part I (Global Anti-scam Org)
Scambaiting is the action of conversing with a scammer for a prolonged period of time so as to distract him/her from further scamming. --- I will admit that scambaiting began as a form of vengeance. A few weeks fresh from my scam discovery D-Day, the urge to seek some form of justice still raged through my veins. I began with language apps, then stemmed into Facebook and dating apps. In the beginning, the goal was only to waste the scammer’s time. After a while, it became a form of dark therapy, allowing me to relish over and over that I had “played” the “player” -- I was in on the charade before the scammer could even begin his charade. There was no sympathy for scammers, just a burning desire to know why they would scam sincere and kind people. I had heard that some scammers were human trafficked into their job, but I couldn’t believe it. It was to me another ploy from the scammer playbook -- engender sympathy from victims to maximize profits. My perspective has shifted since then to a better understanding of the industry, one in which things are not totally black and white. I’ve also gained a better perspective of what can be lied about and what can’t. The following tales highlight some of the most memorable moments since I started scambaiting last August. I hope to put a face behind the people involved in scamming and shed light on human trafficking. […] Luckily for Daddy, his workplace is kind. All employees receive a minimum wage base pay, plus a 16% bonus for successful scams. They live in a relatively clean dormitory, and no one is beaten or hurt. Workers may go out freely on certain days, being tourists at the Burj Khalifa, shopping for groceries, or visiting fresh fruit farms. The employees, most of whom have likely never before left their home country, overall appear to be enjoying their scam life. This can be juxtaposed next to the weekly influx of victims we receive in our victims group, many of whom are in tears or suicidal. Many of whom lost their life savings. […] Recently, Daddy showed off his $21k bonus from scamming an individual out of nearly $138k. He was so excited he could barely sleep for days.
·globalantiscam.org·
Confessions of a Scambaiter, Part I (Global Anti-scam Org)
Max Read: What's the deal with all those weird wrong-number texts?
Max Read: What's the deal with all those weird wrong-number texts?
These texts are usually the lead-in to romance scams that usually end with fake crypto deposits, written so as to imply wealth and success on the part of the scammer, who is often an abused and captive worker operating multiple phones and attempting to con several people from a compound operated by shady gambling rings somewhere in Southeast Asia. […] Now what? It seems likely we can expect this species of pig-butchering scam to eventually fade into the background, thanks to victims getting wise and authorities cracking down. An interview with the subject of the GASO rescue mission suggests that the scam rings’ operations in Europe and North America, at least, are not as profitable as they’d hoped…
·maxread.substack.com·
Max Read: What's the deal with all those weird wrong-number texts?
Darius Kazemi: The Bot Scare
Darius Kazemi: The Bot Scare
It's clear upon inspection that the media narrative about an influx of Russian or otherwise foreign bots influencing politics in America is built on flimsy data and enormous leaps of logic. Further, the narrative empowers conspiracy theorists to make essentially whatever claims they want about anyone. The bots that do exist are drops of water in the ocean of social media, but I believe that the effect of constant front-page news stirring up fear about foreign influence can have far-reaching negative effects on any democracy.
·tinysubversions.com·
Darius Kazemi: The Bot Scare
Aric Toler: Guide to Using Reverse Image Search for Investigations (Bellingcat)
Aric Toler: Guide to Using Reverse Image Search for Investigations (Bellingcat)
Reverse image search engines have progressed dramatically over the past decade, with no end in sight. Along with the ever-growing amount of indexed material, a number of search giants have enticed their users to sign up for image hosting services, such as Google Photos, giving these search algorithms an endless amount of material for machine learning. On top of this, facial recognition AI is entering the consumer space with products like FindClone and may already be used in some search algorithms, namely with Yandex. There are no publicly available facial recognition programs that use any Western social network, such as Facebook or Instagram, but perhaps it is only a matter of time until something like this emerges, dealing a major blow to online privacy while also (at that great cost) increasing digital research functionality. If you skipped most of the article and are just looking for the bottom line, here are some easy-to-digest tips for reverse image searching: • Use Yandex first, second, and third, and then try Bing and Google if you still can’t find your desired result. • If you are working with source imagery that is not from a Western or former Soviet country, then you may not have much luck. These search engines are hyper-focused on these areas, and struggle for photographs taken in South America, Central America/Caribbean, Africa, and much of Asia. • Increase the resolution of your source image, even if it just means doubling or tripling the resolution until it’s a pixelated mess. None of these search engines can do much with an image that is under 200×200. • Try cropping out elements of the image, or pixelating them if it trips up your results. Most of these search engines will focus on people and their faces like a heat-seeking missile, so pixelate them to focus on the background elements. • If all else fails, get really creative: mirror your image horizontally, add some color filters, or use the clone tool on your image editor to fill in elements on your image that are disrupting searches.
·bellingcat.com·
Aric Toler: Guide to Using Reverse Image Search for Investigations (Bellingcat)