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Policy2026-08-21 · source-backed
13 public sources consolidated into 9,740 skills (7,505 malicious, 2,235 benign) across 11 harmonized attack categories. Learned text detectors score 0.882-0.932 Macro-F1 under random splits but collapse to 0.653-0.665 source-disjoint. arXiv Three off-the-shelf skill scanners cut false positives only by giving up most of their malicious recall. Anyone gating a skill marketplace today is choosing between alert fatigue and blind spots, and the random-split numbers everyone quotes are measuring source style, not maliciousness.
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macro-inc/macro hit #4 on GitHub trending at 2,821 stars total, shipping email, chat, docs, tasks, calls and CRM that all @-link into a shared context graph agents read as team-level memory. Explicitly "fully open source, not open core," with commercial licensing sold separate...
An agent proposes changes to a training pipeline, runs it, and keeps edits improving a verifiable in-loop metric. Looks like reliable progress. The authors name algorithmic mode collapse: surface edit diversity stays stable while semantic and mechanism-level diversity collapse...
Agent-agnostic middleware with two halves: System I handles known attacks through a Tier-0 library of rule-based detection scripts backed by Tier-1 optimized LLM inference, System II watches for abnormal signals and attempts to synthesize a new defense. It matches standard-ben...
A paper on arXiv shows attack success rate is an attacker-tunable variable, and a reverse-training framework produces low-ASR backdoors that keep clean-input performance while the backdoor behavior stays intact. State-of-the-art defenses fail consistently under low-ASR conditi...
Researchers loaded five systems with a revoked policy and its replacement, then measured retrieval and downstream action across nine policy scenarios, nine models and six defense conditions. Wherever the revocation label was visible to the retrieval layer, the revoked fact cam...
~248 stars today, 1,251 total, Rust, AGPL-3.0, unifying email, chat, docs, tasks, agents, calls and CRM with @-linking across all of them backed by shared memory (GitHub). The claim is that agent usefulness is bounded by context fragmentation, so you collapse the tools instead...
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