{"data":{"id":"21d83f81-62c8-4f6d-89d8-9b1137c4cf5e","title":"The Cost of Being Wordy: Detecting Resource-Draining Prompts","summary":"Attackers can exploit large language models (LLMs) through \"sponge attacks,\" which are denial of service (DoS) attacks that craft prompts designed to generate extremely long outputs, exhausting the model's resources and degrading performance. Researchers are developing methods to predict how long an LLM's response will be based on a given prompt, creating an early warning system to detect and prevent these resource-draining attacks.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"https://protectai.com/blog/detecting-resource-draining-prompts","publishedAt":"2025-06-17T19:03:34.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["denial_of_service"],"issueType":"news","affectedPackages":null,"affectedVendors":["OpenAI","Google"],"affectedVendorsRaw":["OpenAI","Google"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":"2025-06-17T19:03:34.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"trivial","impactType":["availability"],"aiComponentTargeted":"inference","llmSpecific":true,"classifierConfidence":0.92,"researchCategory":null,"atlasIds":null}}