ResearchShadow APIs Real Money Fake Models 47 Percent Performance DivergencearXiv·high signal17 shadow APIs audited across 187 academic papers. Up to 47.21% performance divergence from official APIs. 45.83% identity verification failure.SourceSource pagearXiv↳ Follow the threadStack layer / Threat patternMCPZoo Study: Scanners Call 96.89% of MCP Servers 'Risky' — But Under Half of Those Alerts Are RealarXivStack layer / Threat patternStudy of 44 Developers: AI Code Assistants Barely Improve Secure API UsagearXivStack layer / Update threadAgentLens: Open-Source Benchmark Scores the Whole Coding-Agent Trajectory, Not Just Pass/FailarXivStack layerReliable, Developer-Aligned Evaluation of SE Agents: 279-Paper Review Finds an 'Illusion of Competence'arXivStack layerDistributed Backdoors Prove Per-Step Agent Monitors Can Be Right on Every Step and Still Miss the AttackarXivStack layerAria: A General Code Agent + Verification Harness Proves All 4,257 Core Iris Lemmas Fully AutomaticallyarXivStack layer'Coding Agents Think Ahead of Time': Latent Probes Predict Outcomes 25 Steps EarlyarXiv / Hacker NewsPolicy dependency / Threat patternZhipu/Z.ai Founder Tang Jie's Internal Memo 'The Giant Wave Has Arrived': Frontier AI Must Stay Open — a Direct Rebuke of China's Rumored CurbsBloomberg