{"data":{"id":"bcf8150a-788c-49b5-9bb4-cc919943ab97","title":"Make the Adversary Spend More Energy: Generative Deception against Language-Model Attackers in Critical Infrastructure","summary":"The authors evaluate an autonomous language-model attacker against a decoy whose defending language model analyzes attacker commands and selects defensive responses. Across 330 sessions on identical GPUs, the attacker-to-defender energy ratio exceeded one with a 95% interval in 41 of 48 configurations under the excluding-diagnostics allocation, and in all 48 when diagnostic calls were included. Enabling thinking on both sides raised defender energy by 8 to 17 times and reversed the exchange for one model pair.","solution":"N/A -- no mitigation discussed in source.","labels":["research","security"],"sourceUrl":"https://arxiv.org/abs/2610.27739v1","publishedAt":"2026-10-20T07:04:05.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["other"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","headline":null,"headlinePromptVersion":null,"cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"epssCheckedAt":null,"kevDateAdded":null,"advisoryAliases":null,"affectedPackagesSource":null,"affectedPackagesCheckedAt":null,"patchAvailable":null,"disclosureDate":"2026-10-20T07:04:05.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["availability"],"aiComponentTargeted":"agent","llmSpecific":true,"classifierConfidence":0.8,"researchCategory":"preprint","atlasIds":null}}