AI is moving deeper into cryptanalysis, vulnerability research and offensive security, raising new questions about how quickly vulnerabilities can be discovered and exploited. In the latest episode of Security Pill Season 2.0, The Cyber Express spoke with Rahul Singh Choudhary, Cyber Security Analyst, about AI-assisted cryptanalysis, vulnerability research, penetration testing and the changing role of security professionals.
Rahul’s day-to-day sits across penetration testing, vulnerability assessment (VAPT), application security, and red teaming. Alongside that, he’s been tracking a narrower but fast-moving thread: AI-assisted cryptanalysis, and what it could mean for how vulnerabilities in wallets, exchanges, and smart contracts get found — by researchers and attackers alike.
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From Security Tool to Research Partner
The conversation opens on a framing question rather than a settled answer: is AI’s growing footprint in cryptanalysis a sign that it’s moved from assisting security research to genuinely participating in it?
That distinction matters to crypto and Web3 specifically — wallets, exchanges, and smart contracts are only as secure as the cryptographic assumptions underneath them, and those assumptions are exactly what AI-assisted research is starting to probe.
AI-Assisted Cryptanalysis ≠ AI Breaking Modern Encryption
Periodically, a headline claims an AI model has “cracked” some cipher or cryptographic scheme — and just as often, security researchers push back on how that claim is being framed.
The episode digs into that gap directly: what these results actually demonstrate technically, why the sensational version of the story usually overstates it, and what the real, less dramatic significance is for people building or securing crypto infrastructure.
AI in the Pen Tester’s Toolkit — and Beyond It
Rahul explains how AI is already being incorporated into offensive security workflows, from reconnaissance and code analysis to vulnerability discovery and early-stage exploit development.
Rahul is asked how much of a practical difference this makes to penetration testing as a discipline, and then pushed further: if a system can find a flaw, write an exploit for it, and adapt based on what it learns, how far away is that from autonomous offensive operations running with minimal human involvement?
Replacing Security Jobs, or Redefining Them?
Given how much of the above sounds automatable, the conversation turns to the question every security professional has heard by now — is AI coming for these jobs? Rather than a yes/no, the episode uses this as a chance to explore what specifically changes in a security role once AI can handle the mechanical parts of the work, and what that leaves for humans to own.
The Real Weak Points: AppSec, Judgment, and Attack Surface
The back half of the episode stays closer to Rahul’s core discipline — application security and VAPT — and asks a few pointed, practitioner-level questions:
- How should organizations prioritize thousands of security findings?
- What separates red teaming from conventional penetration testing?
- Which attack surfaces are organizations consistently underestimating?
- What role will human judgment play as AI automates more security tasks?
Taken together, these questions push past the AI headline and back toward the fundamentals — scope, prioritization, and where human judgment still can’t be automated out of the process.
The episode closes with Express Shots, Security Pill’s rapid-fire round — no explanations, just instinct. Rahul takes a position on AI-assisted hacking vs. traditional exploitation, red team vs. blue team, manual testing vs. automation, web vs. cloud security, bug bounty vs. penetration testing, Linux vs. Windows, his one indispensable security tool, the one skill every beginner should learn, and the single word he’d use to describe where cybersecurity is headed.
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