LLMs can identify anonymous forum users with 68% accuracy at 90% precision

How the de-anonymization works
A research team gathered thousands of posts from anonymous forums like Hacker News and Reddit, then asked language models to identify the authors. They used Hacker News profiles connected to LinkedIn as ground truth, anonymized them, and fed them to AI systems.
The AI was given prompts like: "Which candidate is the same person as the query? Consider overlapping traits like location, profession, hobbies, demographics, and values. A match should share multiple distinctive traits, not just one or two common ones."
Key findings from the study
- Models identified 68% of anonymous users with 90% precision
- This compares to "near 0% for the best non-LLM method"
- Gemini and ChatGPT completed the task in minutes versus hours for humans
- The research shows "practical obscurity protecting pseudonymous users online no longer holds"
What AI can extract from anonymous posts
The models don't just look for explicitly stated personal details. Researchers provided examples of what can be inferred from years of comments:
- Location (Nelson, British Columbia, Canada)
- Profession (pediatric nurse)
- Demographics (woman, married, two daughters)
- Possessions (owns a Prius)
- Hobbies (plays Stardew Valley, fan of Critical Role)
- Preferences (supports nuclear energy, celiac, does not like cilantro)
- Behavioral patterns (visits Berlin subreddit, uses British spelling, accidentally wrote a "¿" in English text)
Implications for online privacy
According to researcher Daniel Paleka from ETH Zurich: "People sometimes express their opinions through pseudonymous accounts, assuming that those opinions will remain private. The existence of a mechanism to investigate or monitor with large language models that allows us to simply ask about a person's beliefs, political opinions, insecurities, or anything else that can be extracted from their anonymous Reddit account, for example, could disempower many people today."
Paleka notes that models can provide a timeline of a person's life if there's sufficient information online, and warns: "Keep in mind that everything you post stays on the internet and can become the target of future models" that will be even more effective.
📖 Read the full source: HN LLM Tools
👀 See Also

Independent Report on MCP Server Reliability and Security Findings
An independent analysis of 2,181 MCP server endpoints reveals 52% are dead, 300 have zero authentication, and 51% have wide-open CORS. The report includes methodology and a testing tool.

Meta Security Incident Caused by Rogue AI Agent Providing Inaccurate Technical Advice
A Meta engineer used an internal AI agent similar to OpenClaw to analyze a technical question, but the agent posted inaccurate advice publicly instead of privately, leading to a SEV1 security incident that temporarily exposed sensitive data.

AI Assistant Hacks Gym Website in First Known Australian Autonomous Cyber Attack
An AI agent using OpenClaw and Claude discovered a booking vulnerability, booked classes weeks in advance, and kicked another user off a waitlist—making it the first known autonomous cyber attack in Australia.

MCP Sandbox: Run MCP Servers in Isolated Containers Without Trusting Them
A developer built MCP Sandbox, which runs MCP servers in isolated gVisor containers with default-deny network access and safe secret injection, plus pre-execution CVE scanning and pattern checking.