@Ramo

Open source platform for X.509 certificate based service authentication and fine grained access control in dynamic infrastructures

Bull Bitcoin, a MiCA-licensed non-custodial exchange, has filed a landmark legal challenge before France's Conseil d'État to annul Decree No. 2025-1276, which implements the EU's DAC8 crypto tax reporting directive. The exchange argues the rules create a mass surveillance database linking identities and crypto activity, endangering holders' physical safety.

We submitted our first paper to ARR, intending to commit to IJCNLP-AACL. Area: Multilingualism and Cross-Lingual NLP Scores: (3,4) (2.5,3) (3,3) - average 2.83 for reviews, 3.33 for confidence 3 for soundness on all, 4 for reproducibility, and 2,3,3 for excitement. The reviewer who gave us 2.5 has a very short review. They only list one weakness in two sentences and give the paper 2.5. They also give 1,2 for the datasets and software while the other reviewers both give 3 or 4 for these. The (3,4) review gave us 3 weaknesses, with two being writing issues. The (3,3) review has a very nice and very thourough review with many weaknesses and strengths. Questions Is the score good for IJCNLP-AACL findings in the Multilingualism and Cross-Lingual NLP area? How will each review be weighted in the meta-review? Will the shorter outlier review be weighted less in this? How much will rebuttals help? Should we expect the reviewers to respond or change their scores because of the rebuttals? Is there a specific format for rebuttals or any tips you have for rebuttals in ARR? submitted by /u/hepiga [link] [Kommentare]

First real drive outside. Before this it only ran on the bench. Build: four 10.5" hoverboard hub motors, 2x ODrive (ODESC 3.6), Raspberry Pi 5, aluminium profile frame. Control is fully manual right now, from a laptop over 4G: live camera, per-motor telemetry, ARM / E-STOP. Main thing I learned: skid-steer turning depends heavily on surface grip, so that has to go into the control logic rather than being tuned by feel. Next step is autonomous A-to-B: 3D lidar, ODrive on CAN with closed-loop wheel control, ROS2/Nav2 for planning. Still early. Happy to answer anything about the build. submitted by /u/NiamorroMilky [link] [Kommentare]

Despite breathless reporting on how AI is going to change the world, Hannah Cyrus, a Bangor librarian, said that, in her experience, most library patrons aren’t finding it helpful.

AI agents act on behalf of user prompts, consuming external data and taking actions based on the agent context. Prior research on AI agent security has primarily focused on indirect prompt injection (IPI). Its most well-studied category is instruction injection, where attacker-controlled untrusted data is interpreted as an instruction. In response, many mitigations have been proposed to prevent instruction injection attacks. In this paper, we introduce a new category of IPI, agent data injection attacks (ADI). ADI injects malicious data disguised as trusted data, such as security-critical metadata (e.g., resource identifiers or data origins) or agent context data (e.g., tool call and response formats). As a result, agents unknowingly execute unintended actions based on attacker-controlled data. ADI has similar attack impacts as instruction injection attacks, because it causes agents to misbehave and execute unintended actions. Despite the similar impact, ADI remains underexplored and easily bypasses existing IPI defenses. We found several critical vulnerabilities in real-world agents that allow an attacker to launch various attacks: arbitrary click attacks on web agents (Claude in Chrome, Antigravity, and Nanobrowser), and remote code execution and supply-chain attacks on coding agents (Claude Code, Codex, and Gemini CLI). We evaluate ADI vulnerabilities across off-the-shelf models and AI agents, and find that ADI is effective in both standalone LLMs and AI agent settings. ADI exposes a critical gap in agent security, signifying that current AI agents do not employ a fundamental security principle: current agents do not isolate trusted data from untrusted data.

A fast, decentralized web search engine in one Rust binary. Every node is complete alone; federation is additive. No DHT, no tokens, no telemetry.