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ttdayngheso1 joined the community
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Vand advertoriale in aproximativ 700 site uri din romania
j1ll2013 replied to M4T3!'s topic in Black SEO & monetizare
advertorialele inca merg bine ! am avut si eu la fel dar pe limba romana. daca e pe engleza recomand PLR - SPIN = BLOG -
socolive2cv5 joined the community
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teslaexpress changed their profile photo
- Yesterday
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Vand advertoriale in aproximativ 700 site uri din romania
alezu2000 replied to M4T3!'s topic in Black SEO & monetizare
ti-am lasat mesaj in privat -
Cum sa procedezi cu ofertele de backlinks
Gonzalez replied to Nemessis's topic in Black SEO & monetizare
Ai vreo recomandare pentru ferma de click-uri? - Last week
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Tarziu ti-ai dat seama . N-am mai intrat de 2 ani si vad comentariul tau De la it la panarama, isi merita soarta.
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gfhfg changed their profile photo
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fly88free changed their profile photo
- Earlier
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"A crypto drainer is a type of malicious software or scam tool designed to steal cryptocurrency from a victimβs wallet, usually by tricking them into approving a harmful transaction." - Nici nu stiam ce e mizeria asta. E bine ca un malware de genul asta nu poate ajunge la portofelul meu cu multe hartii de 10 RON pentru bacsisuri.
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vua99aioig changed their profile photo
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dumneata esti inginer fara diploma. bun pont !
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Hello evryone , after many asked me to share this method i am tierd to answer evryone at private and explain , here is a full shared method with step by step , method i am talking about its crypto drainig , for those who don't know what is its a script you add to any scam page and its ask vectim to connect his crypto wallet as a legit action like for connecting , or claim somthing , once he connect he recive a signature request like any legit website , but inside this requsest there is a hdien request that givers permiison to take all crypto once signed Next, you need a good traffic method , a traffic method that will target crypto users. For me, I am using Twitter ads, targeting new projects, and posting free claims. I have a team working with me of 3 people. We are making until now this money: Β£91k. You can start with just a $100 budget for ads, and then you can go with more once you get hits. There are some people making over Β£1m in one hitβhit crazy, right? Our biggest hit ever was Β£466k. That's right, one good wallet can change your life. One more thing: be sure that you have a good method; don't just jump in with no knowledge or dig deep in the methods shared on panels like Exogator. Well, this is the end for now. If you have any questions, I will post a part 2 thread that answers these questions.
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Sfatul nr 1 din hacking: "Inveti vreo 10 ani si pe urma te apuci de facut bani". Daca nu inveti vreo 10 ani te prind astia imediat si pe urma stai 10 ani prin salile de judecata si calare pe Microsoft Word sa scrii documentele pt dosarele tale. Tu alegi. Ori 10 ani sa devii hacker ori 10 ani sa devii propriul tau avocat.
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Large-scale online deanonymization with LLMs
fbi_suge replied to Nytro's topic in ML / AI / LLM Security
as adauga 4. Trb sa iei in considerare din prima zi ca gaborii americani iti stiu identitatea reala de la bun inceput. Exista vreo asociere reala intre contul tau bancar (de Persoana Fizica) si conturile alea bancare? E vreo asociere? toate soft-urile de parafrazare folosesc modele de AI. -
Large-scale online deanonymization with LLMs
Nytro replied to Nytro's topic in ML / AI / LLM Security
Da, nu e tocmai practic research-ul lor, dar e destul de interesant ca metodologie. Ideea de baza, desigur, e sa nu dai detalii despre tine niciunde. Degeaba esti "HackerMan1337" daca ai Facebook-ul la fel. Da. Sau LLM-uri, doar sunt bune la asta. -
Large-scale online deanonymization with LLMs
fbi_suge replied to Nytro's topic in ML / AI / LLM Security
Ideea e interesanta insa sa combati analiza e f usor: 1. Nu dai detalii despre tine 2. Dai detalii fake despre tine 3. Folosesti software de parafrazare -
We show that large language models can be used to perform at-scale deanonymization. With full Internet access, our agent can re-identify Hacker News users and Anthropic Interviewer participants at high precision, given pseudonymous online profiles and conversations alone, matching what would take hours for a dedicated human investigator. We then design attacks for the closed-world setting. Given two databases of pseudonymous individuals, each containing unstructured text written by or about that individual, we implement a scalable attack pipeline that uses LLMs to: (1) extract identityrelevant features, (2) search for candidate matches via semantic embeddings, and (3) reason over top candidates to verify matches and reduce false positives. Compared to classical deanonymization work (e.g., on the Netflix prize) that required structured data , our approach works directly on raw user content across arbitrary platforms. We construct three datasets with known ground-truth data to evaluate our attacks. The first links Hacker News to LinkedIn profiles, using crossplatform references that appear in the profiles. Our second dataset matches users across Reddit movie discussion communities; and the third splits a single userβs Reddit history in time to create two pseudonymous profiles to be matched. In each setting, LLM-based methods substantially outperform classical baselines, achieving up to 68% recall at 90% precision compared to near 0% for the best non-LLM method. Our results show that the practical obscurity protecting pseudonymous users online no longer holds and that threat models for online privacy need to be reconsidered. Download: https://arxiv.org/pdf/2602.16800