Personal AI Assistants Build Detailed Profiles on Friends and Family Raising Privacy Concerns

The latest generation of personal AI agents such as Muse from Meta and Dots from OpenAI are gaining deep access to user emails, messengers, and financial accounts while autonomously collecting data. Security researchers discovered that Muse, internally referred to as Hatch, stores memory in Markdown files under ~/memory/ and runs hourly background tasks that create individual profile pages for every person connected to the user. These profiles include sections on Facts, History, Relationships, Open Topics, and Strengthening, populated only with verified details such as addresses, recurring themes, important dates, and relationship dynamics. The agents operate with root privileges on Ubuntu by default and maintain separate directories for 113 sub-agents along with a PostgreSQL-backed search system and nightly dream processes. Data collection extends to individuals who never installed the agent, supplementing existing social graphs maintained by major technology companies. An isolated virtual machine architecture developed with assistance from Signal creator Moxie Marlinspike is intended to limit cross-agent communication and allow users to erase memory at any time.

HabrTranslated from Russian

Read at source

The newest wave of personal AI agents, including Muse from Meta and Dots from OpenAI, is replacing earlier chatbots that lacked persistent memory and direct access to user data. These agents receive broad permissions to read emails, messengers, and bank accounts while performing actions on the user’s behalf, although financial transactions still require physical confirmation.

Security researchers examining Muse (internally codenamed Hatch) found that default installation grants root privileges on Ubuntu together with access to RAM, cron.d, and gigabytes of user files including SSH keys. Memory is stored in dated Markdown files inside ~/memory/, updated automatically during conversations and organized by hourly background tasks that feed into a PostgreSQL search index. A separate nightly “dream” process reviews recent dialogues and generates recommendations stored in ~/dreams/.

One of the agent’s core instructions requires creating a dedicated page for every person in the user’s life, covering family, partners, friends, colleagues, collaborators, and followed individuals. Each profile begins with minimal information and expands over time with verified entries under headings such as Facts, History, Relationships, Open Topics, and Strengthening. Examples include addresses, occupations, recurring themes like apartment moves or shared savings goals, birthdays, anniversaries, past events, and assessments of relationship closeness together with suggested actions to improve ties.

Because the agents gather information from the primary user’s communications and files, detailed dossiers are compiled on people who never installed any AI assistant. This process augments the extensive social graphs already held by technology platforms. Researchers also noted the presence of 113 sub-agents recorded in JSONL files and a large Spaces framework used for application deployment.

A post-installation safeguard creates an isolated virtual machine that holds all user data and context. The VM is inaccessible to other agents, and users can delete memory or disconnect external services at any moment. The architecture was developed with input from Signal creator Moxie Marlinspike to prevent formation of swarms of personal agents that could communicate and evolve collective intelligence.

Meridian digestThe week's most consequential security stories, distilled into one briefing.See the digest

More in Privacy & Surveillance

AmneziaWG Container for Mikrotik Routers Achieves Major Performance and Feature Upgrades Six Months On
Samsung Bixby Sends Data to Cloud Despite Galaxy AI On-Device Processing Setting
Maximizing iPhone Privacy: Essential Settings to Enable, Disable, and Verify Immediately