What is Hackers' Pub?

Hackers' Pub is a place for software engineers to share their knowledge and experience with each other. It's also an ActivityPub-enabled social network, so you can follow your favorite hackers in the fediverse and get their latest posts in your feed.

우리나라 섬 지역 263곳을 조사한 결과 약 60%의 섬에 개구리가 서식 중인 것으로 조사됐습니다. 가장 많이 발견된 건 청개구리로, 섬 143곳에서 확인됐고 멸종위기 야생생물 1급인 수원청개구리와 2급 맹꽁이·금개구리도 113곳에 분포하고 있었습니다. 일부 섬 개구리는 육지 개구리와 유전자도 달랐습니다.

빙하 타고 섬으로 간 ‘개구리들의 모험’…유전자 달라

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Large-scale online deanonymization with LLMs

https://arxiv.org/abs/2602.16800

It's over, anons.

arXiv logo

Large-scale online deanonymization with LLMs

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 identity-relevant 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 cross-platform references that appear in the profiles. Our second dataset matches users across Reddit movie discussion communities; and the third splits a single user's 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.

arxiv.org · arXiv.org

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RE: dair-community.social/@Meron/1

As someone who came to the US as a refugee with political asylum I can't overstate how cruel this is. I was already terrified and had nightmares every day. And here they're telling you that you didn't get to safety after all that, that they will reverse your status on a whim, if they deem it safe for you to return. As Warsan Shire wrote, no one leaves home unless home becomes the mouth of a shark.

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With Loops Starter Kits, you can set your desired privacy setting to auto approve, auto reject all requests or something in between.

We created a new notification tab to easily manage requests, updates and removals.

Yeah, you even get notified when you get removed from a kit 😎

You can always self-remove yourself from any kit if you change your mind, and with one button press, can mass-remove yourself from any kits you didn't create.

Loops Starter Kit Privacy SettingsLoops Starter Kit Notifications
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