The integration of autonomous AI models into cybersecurity compresses the vulnerability lifecycle and challenges existing regulatory and institutional frameworks. Critically examine.

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UPSC Mains: AI Models in Cybersecurity Analysis

CRITICALLY EXAMINE (State the claim → What works/holds true (brief) → Where it fails/falls short (dominant) → Contradictions, gaps, missing dimensions → Verdict)

Intro = Mythos-class AI → autonomous discovery + exploit development + compressed lifecycle ≠ earlier AI-assisted tools
Holds → discovery accelerated + bug bounty efficiency ↑ + defensive dividend possible + open-source models = democratised defence
Falls short → discovery ≠ bottleneck + real gap = N-day patching backlog + enterprises ≠ ready for AI-scale vulnerability flood
Contradiction → AI finds faster ≠ orgs patch faster + non-experts using Mythos = attack surface ↑ ≠ defence capacity ↑
Gap 1 → India = no AI-cybersecurity integration policy + CERT-In capacity ≠ AI-era threat model
Gap 2 → DPDPA 2023 = data liability ≠ AI-assisted breach vectors + CII protection framework = outdated
Gap 3 → state-sponsored actors (Pegasus-type) + Mythos-class tools = strategic national security risk ≠ just technical problem
Missing dimension → workforce: lower-level work commoditised + contextualisation + validation = new human premium
Verdict → AI is accelerant ≠ rupture + response must shift: find faster → protect faster + smarter + governance must catch up

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