Artificial Intelligence is increasingly being integrated into cryptanalysis, vulnerability research, and offensive security practices, prompting new discussions about the speed at which vulnerabilities can be identified and exploited. In the most recent episode of Season 2.0 of Security Pill, The Cyber Express interviewed Rahul Singh Choudhary, a Cyber Security Analyst, regarding the implications of AI in cryptanalysis, vulnerability research, penetration testing, and the evolving responsibilities of security professionals.
Rahul’s role encompasses penetration testing, vulnerability assessment (VAPT), application security, and red teaming. He has been closely observing the rapid advancements in AI-assisted cryptanalysis, particularly its implications for discovering vulnerabilities within wallets, exchanges, and smart contracts for both researchers and malicious entities.
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From Security Tool to Research Collaborator
The discussion begins with an important inquiry: is AI’s expanding role in cryptanalysis indicative of a transition from merely supporting security research to actively engaging in it?
This distinction holds particular significance for the crypto and Web3 sectors — the security of wallets, exchanges, and smart contracts relies on the cryptographic principles they are built upon, which AI-assisted research is beginning to scrutinize.
AI-Assisted Cryptanalysis ≠ AI Breaching Current Encryption
Occasionally, headlines proclaim that an AI model has “broken” a particular cipher or cryptographic system, and just as frequently, security experts challenge the narrative surrounding such claims.
This episode delves into the nuances of these assertions: what the actual technical outcomes indicate, why sensational reports often exaggerate the implications, and the authentic, less dramatic consequences for those involved in developing or securing crypto infrastructure.
AI in the Pen Tester’s Toolkit — and Beyond
Rahul highlights how AI is becoming a vital aspect of offensive security strategies, enhancing tasks such as reconnaissance, code evaluation, vulnerability identification, and initial exploit development.
When asked about the tangible impact on penetration testing as a field, he is further probed: If a system can detect a vulnerability, craft an exploit, and adapt through its experiences, how close are we to fully autonomous offensive operations with limited human oversight?
Job Displacement or Evolution?
Given the automatable nature of many discussed tasks, the dialogue shifts to a familiar question among security professionals: is AI threatening these jobs? Rather than a straightforward answer, the episode emphasizes the specific transformations within security roles as AI starts managing the routine aspects, leaving more complex tasks for humans.
Identifying Core Weaknesses: AppSec, Judgment, and Attack Surface
The latter part of the episode focuses on Rahul’s expertise in application security and VAPT, posing several crucial questions targeted at practitioners:
- How should organizations prioritize thousands of security alerts?
- What differentiates red teaming from standard penetration testing?
- Which attack vectors do organizations commonly undervalue?
- What role will human discretion play as AI takes on more security responsibilities?
Together, these inquiries challenge the sensational headlines surrounding AI and redirect attention toward fundamental issues — scope, prioritization, and the irreplaceable aspect of human judgment in the process.
The episode wraps up with a segment called Express Shots, where Rahul shares spontaneous insights on AI-driven hacking, contrasts red teams with blue teams, weighs manual testing against automation, and discusses web versus cloud security, bug bounties versus penetration testing, Linux versus Windows, his essential security tool, the crucial skill every novice should acquire, and the single word that captures the future direction of cybersecurity.
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