Red Teaming Generative AI
Why prompts are payloads, and what an adversarial test plan looks like for systems that 'reason' over untrusted text.
cat ./talks
I accept four to six speaking invitations a year. The sessions that work best are the ones that match my practice: threat modeling, adversary simulation, secure architecture, secure code review, and the current focus on red teaming AI systems and MAESTRO-aligned ML security.
If any of these feel right for your audience, email me with what you have in mind.
Why prompts are payloads, and what an adversarial test plan looks like for systems that 'reason' over untrusted text.
Why classical frameworks miss EchoLeak-class attacks, and the five-zone methodology that finds them.
CSA's layered framework, applied. What it catches that classical AppSec doesn't, and how to build it into your ML platform without slowing the team.
How to stand up the controls, runbooks, and culture for organizations shipping generative AI features, without reinventing the wheel.
Input/retrieval, reasoning, action, state, coordination. A practitioner's map for agentic AI threat modeling that goes beyond enumeration.
A few of the recent ones. Happy to talk about any of these in more detail over email.
Maharshi Markandeshwar University
Practitioner walk-through of red-teaming methodology for LLM-powered applications and ML systems, with reproducible exercises.
Industry roundtable (private)
Invited briefing for senior security leaders on threat modeling for agentic AI, the gaps between framework guidance and production deployments, and concrete remediation patterns.
VC investor briefing
Conversation on the state of AI security tooling, where the market is genuinely under-served, and how technical due diligence should change for AI-native companies.
Vapra.shiksha
Hosted a series of talks on cybersecurity craft and applied AI security for an engineering audience.
> 30–45 minutes
Conferences, summits, industry events.
> ½ or full day
Hands-on, methodology transfer.
> 45–60 minutes
Industry panels, moderated discussions.
> 60 minutes
For your team, on-site or remote.
Manish Pandey is a Cybersecurity Architect and Researcher based in Bengaluru. 13+ years across application security, infrastructure, cloud, code review, vulnerability management, and ML security. M.Tech in Data Science, BITS Pilani. Writes on threat modeling, red teaming, and the security of AI systems.
Manish Pandey is a cybersecurity architect and researcher with 13+ years across the security stack: application security testing, secure code review, vulnerability management, adversary simulation, cloud security, DevSecOps. He has spent the past several years extending this practice into ML security and threat modeling for agentic AI, aligned to the CSA MAESTRO framework. He holds an M.Tech in Data Science from BITS Pilani, which lets him read the underlying ML math rather than the security press releases about it. Long-form practitioner writing on the security implications of LLM-driven and agentic architectures sits alongside notes on classical security craft. Based in Bengaluru.
> Need a high-resolution headshot or logos? Email me and I'll send the media kit.
> For organizers: short / long bios above, headshot on request via email.