#deanonymization — Public Fediverse posts

The Risks Of Anonymity In The Age Of Generative AI

https://fed.brid.gy/r/https://www.techdirt.com/2026/04/27/the-risks-of-anonymity-in-the-age-of-generative-ai/

Well, we don't decide what the customers decide to ship, or where it goes. We don't enforce policy like that; our job is just to provide a neutral platform for others to use to accomplish their goals. We don't even know what they ship - we just build the train cars. We don't even know where Bergen-Belsen is.

This is a post about #systemd.

#AgeVerification #AgeGate #AgeGating #identification #deanonymization #anonymous #fascism #fascist #compliance #ComplyInAdvance #DoNotComply #DoNotComplyInAdvance #resistance #freedom #FreeSoftware #OpenSource #coconspirator #accomplice #DeathCamp #ConcentrationCamp

[en] Paper: LLMs 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."

"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."

"We demonstrate that LLMs fundamentally change the picture, enabling fully automated deanonymization attacks that operate on #unstructured text at scale."

Note: also check paragraphs "Potential harms" and "Potential benefits".

https://arxiv.org/html/2602.16800

#llm #research

"TL;DR: We show that LLM agents can figure out who you are from your anonymous online posts. Across Hacker News, Reddit, LinkedIn, and anonymized interview transcripts, our method identifies users with high precision – and scales to tens of thousands of candidates.

While it has been known that individuals can be uniquely identified by surprisingly few attributes, this was often practically limited. Data is often only available in unstructured form and deanonymization used to require human investigators to search and reason based on clues. We show that from a handful of comments, LLMs can infer where you live, what you do, and your interests – then search for you on the web. In our new research, we show that this is not only possible but increasingly practical."

https://simonlermen.substack.com/p/large-scale-online-deanonymization

#AI #GenerativeAI #Anonymity #Deanonymization #LLMs

LLMs are good at deanonymization.
https://arxiv.org/abs/2602.16800
#AI #LLMs #deanonymization #cybersecurity

Large-scale online deanonymization with LLMs
From Cornel University Computer Science

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.

Simon Lermen, Daniel Paleka, Joshua Swanson, Michael Aerni, Nicholas Carlini, Florian Tramè

https://arxiv.org/abs/2602

#computerscience #cornelluniversity #AiResearch #privacy #anonymity #llm #HackNews #athropic #pseudonymity
#deanonymization

You've got nothing to hide, do you?

»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«

https://arxiv.org/abs/2602.16800

"#AI" #privacy #pseudonymity #anonymity #LLM

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 prior deanonymization work (e.g., on the Netflix prize) that required structured data or manual feature engineering, 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."

https://arxiv.org/html/2602.16800v1

#AI #GenerativeAI #LLMs #Anonymity #Privacy #Deanonymization

Especially with "generative AI" being available I don't see how one can do any kind of objective "age verification" reliably, without some kind of (government or (paid) 3rd party) doing what is essential an "identity verification" or de-anonymization & some kind of permanent audit trail being created outside your control maintained by middlemen: government or third party

(And likely more #DRM & #DMCA bullshit)

#AgeVerification #DeAnonymization

"Large-Scale Online #Deanonymization with #LLM s"

Long time coming, first time I see groundbreaking research into it. Scary jobby

Post: https://simonlermen.substack.com/p/large-scale-online-deanonymization
Paper (PDF): https://arxiv.org/pdf/2602.16800

#privacy #doom

Ah, the illustrious quest to deanonymize HN posts using #LLMs, because apparently, we didn't have enough ways to invade #privacy 🙄. Congratulations, you've managed to turn a noble pursuit of #cryptography into a privacy nightmare, one post at a time. Bravo, truly groundbreaking work in not respecting personal space! 🚀🔍
https://arxiv.org/abs/2602.16800 #deanonymization #invasion #ethical #concerns #HackerNews #ngated

#Republican plan would make #deanonymization of #census data trivial

But now, a little-known #algorithmic process called “differential privacy,” created to keep census data from being used to identify individual respondents, has become the right’s latest focus. WIRED spoke to six experts about the #GOP ’s ongoing effort to falsely allege that a system created to protect people’s #privacy has made the data from the 2020 census inaccurate.

https://arstechnica.com/tech-policy/2025/10/republican-plan-would-make-deanonymization-of-census-data-trivial/

I really like this kind of content that breaks down research papers for the rest of us. I had no idea that BGP hijacking was such a threat.

I wonder if any security folks out there have more up-to-date information on the resilience of OVH, Hetzner, DigitalOcean and other major provider networks. Are Counter-RAPTOR guards, counter-fingerprinting measures, BGP monitoring and RPKI being deployed in the wild?

https://youtu.be/XDsLDhKG8Cs

#Security #BGP #Networking #Tor #AttackVector #Deanonymization

Comprehensive Analysis of De-Anonymization Attacks Against the Privacy Coin XMR

https://monero.forex/is-monero-totally-private-a-comprehensive-analysis-of-de-anonymization-attacks-against-the-privacy-coin/

#HackerNews #DeAnonymization #Attacks #PrivacyCoin #XMR #Monero #Cybersecurity

Unique 0-click #deanonymization attack targeting #Signal, #Discord and hundreds of platform
https://gist.github.com/hackermondev/45a3cdfa52246f1d1201c1e8cdef6117
#twitter #x #cloudflare

Администраторов Telegram каналов теперь можно деанонимизировать по кастомным стикерам и эмоджи.

Уязвимость заключается в том, что UID стикер-пака позволяет извлечь ID его создателя, что помогает раскрыть профиль пользователя.

Авторы Telegram-каналов заказывают у дизайнеров фирменные наклейки и «регистрируют» их в мессенджере с помощью бота Stickers, не подозревая о том, что это раскрывает их аккаунт всем.

Для популярной OSINT-утилиты Maltego даже уже разработали модуль позволяющий автоматизировать данную задачу.

src: https://github.com/vognik/maltego-telegram

#blacktriangle #anonymity #deanonymization #maltego #telegram #opensource #osint

Tor Responds to Reports of German Police Deanonymizing Users https://www.securityweek.com/tor-responds-to-reports-of-german-police-deanonymizing-users/ #Tracking&LawEnforcement #deanonymization #anonymity #Tor

Tor Responds to Reports of German Police Deanonymizing Users https://www.securityweek.com/tor-responds-to-reports-of-german-police-deanonymizing-users/ #Tracking&LawEnforcement #deanonymization #anonymity #Tor

#Urgence à FranceTélévisions : inventer le #floutage de demain
https://larevuedesmedias.ina.fr/urgence-france-televisions-inventer-le-floutage-de-demain
#FranceTV is creating a new #anonymity charter with strict #guidelines on #voice and face anonymization to protect #sources, as current anonymization methods are susceptible to #AI-driven #deanonymization. After reviewing 1100 news segments, 30 were unpublished due to high deanonymization #risk.

https://arxiv.org/abs/2310.07298v1

Just tried to replicate the deanonymization technique proposed in this paper by giving it some of my old Reddit posts. My reddit profile is really puzzling to GPT-4: "Their interest in traditionally stereotyped masculine (computer science) and feminine (tea, Harry Potter books) domains makes it rather challenging to guess their gender accurately." :')

#llms #privacy #reddit #gpt4 #deanonymization

#deanonymization
I'm Mark Ruffalo and this is my Mastodon account.

NoScript - Cross-tab Identity Leak Protection

Protection, see picture.

Cache-based Targeted #Deanonymization #Attacks Paper + Info
https://leakuidatorplusteam.github.io/