Harnessing the Universal Geometry of Embeddings

• We introduce the first method for translating text embeddings from one vector space to another without any paired data, encoders, or predefined sets of matches. Our unsupervised approach translates any embedding to and from a universal latent representation (i.e., a universal semantic structure conjectured by the Platonic Representation Hypothesis). Our translations achieve high cosine similarity across model pairs with different architectures, parameter counts, and training datasets. The ability to translate unknown embeddings into a different space while preserving their geometry has serious implications for the security of vector databases. An adversary with access only to embedding vectors can extract sensitive information about the underlying documents, sufficient for classification and attribute inference.

Russian GRU Targeting Western Logistics Entities and Technology Companies

• This joint cybersecurity advisory (CSA) highlights a Russian state-sponsored cyber campaign targeting Western logistics entities and technology companies. This includes those involved in the coordination, transport, and delivery of foreign assistance to Ukraine. Since 2022, Western logistics entities and IT companies have faced an elevated risk of targeting by the Russian General Staff Main Intelligence Directorate (GRU) 85th Main Special Service Center (85th GTsSS), military unit 26165—tracked in the cybersecurity community under several names (see “Cybersecurity Industry Tracking”). The actors’ cyber espionage-oriented campaign, targeting technology companies and logistics entities, uses a mix of previously disclosed tactics, techniques, and procedures (TTPs). The authoring agencies expect similar targeting and TTP use to continue.

GPT Agents:

• Finished first pass at NYTimes Op Ed

SBIRs

• Many meetings. Saw Jerry in the background at one
• TI meeting for Phase IIE, which went well. In-person meeting next week