{"data":{"id":"4cce8185-cee6-48e7-a179-3000ae867739","title":"Can LLMs Keep Up? Evaluating Phishing Detection on Telegram","summary":"This research paper evaluates whether large language models (LLMs, AI systems trained on vast amounts of text data) can effectively detect phishing messages (fraudulent messages designed to steal information) on Telegram, a messaging platform. The study examines how well LLMs perform at this security task compared to traditional detection methods.","solution":"N/A -- no mitigation discussed in source.","labels":["security","research"],"sourceUrl":"https://dl.acm.org/doi/abs/10.1145/3829369?af=R","publishedAt":"2026-09-11T12:01:08.788Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":[],"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":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity","safety"],"aiComponentTargeted":"model","llmSpecific":true,"classifierConfidence":0.75,"researchCategory":"peer_reviewed","atlasIds":null}}