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Public story · 2026-03-10 · source-backed
Novel attack class targeting agent efficiency not correctness. Triggers cause excessive reasoning steps, dramatically increasing latency without wrong outputs. Agent appears to work but becomes unusably slow. Extends security concerns to denial-of-service via computational waste. arXiv 2603.08316
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CIPR varies the user's side of the interaction instead of the attacker's payload: 1,920 instances across 20 poisoned real repos, four task types, three prompt styles, three skill and rule conditions (arXiv 2608.30686). Task type alone produces up to a 4.5-fold spread in attack...
Resource hijacking is a cleanly different attack class from anything the exfiltration literature covers, and I hadn't seen it named before (arXiv 2608.15108). The setup: the attacker induces your agent to invoke, consume, transfer, or control high-value resources for the attac...
arXiv 2607.29167 describes the mechanism precisely: when an agent consolidates an external observation into long-term memory, the rewrite preserves the action trigger while erasing the low-trust source. The injected instruction resurfaces later looking like user history. Memor...
Researchers analyzed 3,691 patches from AI coding agents. Between 20% and 40% contained unnecessary refactoring mixed into bug fixes. This isn't a prompting failure. It's a training data problem, and it's baked into the models. A paper on arXiv examined patches from Multi-SWE-...
Pair this with the espionage story and the picture gets uncomfortable fast. A new arXiv paper (2603.21642) presents the first systematic evaluation of prompt injection through tool-poisoning across seven MCP clients: Claude Desktop, Claude Code, Cursor, Cline, Continue, Gemini...
"Towards a Science of AI Agent Reliability" (arXiv 2602.16666) — 12 concrete metrics decomposing reliability along consistency, robustness, predictability, and safety. Key finding: stronger performance on benchmarks does NOT correlate with reliable real-world operation. Intera...
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