AI-Augmented Offensive Security
Recon, intel, app attacks, and adversarial AI red teaming — all AI-accelerated.
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AI-Augmented Offensive Security
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Description
This is a 3-month course for offensive practitioners who want to fold AI into every stage of an engagement — and treat attacking AI systems themselves as a genuine red-team discipline rather than an afterthought.
- Opens with AI-assisted recon and exploit scripting, moves through AI-driven threat intelligence, then covers application security focused on AI-agent auth flaws, and closes with adversarial AI red teaming — jailbreaks, prompt injection, and model evasion as their own attack techniques.
- One of the only courses that dedicates real depth to attacking AI itself, rather than simply using AI as a productivity tool for traditional pentesting.
- Natural next step after AI Security Foundations for learners specializing toward offense.
- Prepares graduates for emerging roles like AI red-teamer or offensive AI security researcher, alongside traditional penetration testing positions.
Course Content
Skills You'll Gain
What You'll Learn
Secure the ML pipeline against data poisoning, model theft, and supply-chain risk
Execute and defend against evasion, extraction, and membership-inference attacks
Identify and remediate prompt injection, insecure output handling, and agentic tool-call abuse
Apply traditional AppSec practice to the APIs fronting AI systems
Red-team and then patch a deliberately vulnerable AI application end to end
Operate as an AI security engineer across the full ML pipeline, not just the application layer
Lab Details
- OSINT Target Profile — Build a passive recon profile of a lab target using public records, DNS/WHOIS, and social footprint data before touching a single port.
- Active Enumeration Sweep — Run active scans to map live hosts, open services, and versions across a lab network.
- Exploit & Escalate — Exploit a vulnerable lab host and chain a privilege-escalation technique to full control.
- AI-Assisted Recon Script — Direct an AI copilot to build a Python recon script, then debug and extend it against a live target.
- OWASP Top 10 Lab Walkthrough — Break a deliberately vulnerable web app across multiple OWASP Top 10 categories and document each finding.
Why Us
Why Choose eSecurityIN?
One of the few programs teaching MLOps security as its own engineering discipline, not a bolt-on to AppSec
The adversarial ML deep dive goes beyond theory into extraction and membership-inference attacks specifically
The hands-on vulnerable-AI-app lab means you patch real, deliberately broken systems, not just read case studies
Positions graduates for the emerging AI security engineer / ML security specialist role category
Builds directly on the AI-Augmented Offensive and Defensive tracks for a natural specialization path
Industry recognized certificate issued on course completion
Requirements
A few things to have ready before you begin — nothing complicated.
Who This Course Is For
Built for a range of learners and professionals ready to break into or level up in cybersecurity.
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eSecurityIN Certified Faculty
VerifiedCybersecurity Trainers & Industry Practitioners
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Our certified cybersecurity faculty bring real-world industry experience across penetration testing, network security, and compliance — dedicated to hands-on, practical training that gets you job-ready.
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