Ethical Hacking Course in Bangalore — AI Pentest + CEH v13 · 2 Months

Month 2 is the work no other Bangalore institute is delivering at this depth. We've broken it into five blocks that mirror how product-company AI red teams actually structure their work.

Block 2.1 — AI-assisted vulnerability discovery (Week 5)

This is the easiest entry into the AI-pentest world because it builds directly on Month 1 Burp Suite skills. PortSwigger added AI-augmented vulnerability discovery to Burp Suite Pro in late 2024 and the feature has matured rapidly through 2025-2026. We cover the PortSwigger AI scanner workflow end to end — automatic vulnerability detection across the OWASP Top 10, AI-driven payload generation for context-aware injection attacks, exploit chaining suggestions where the AI proposes next-step attacks based on initial findings. The 5-10x speedup on manual Burp workflows that experienced pentesters report is real and we demonstrate it on real target environments.

We also cover the third-party AI extension ecosystem for Burp Suite Pro — the Autonomous Replicator extension that auto-generates exploit proof-of-concept from a Burp request, the AI-Assisted Exploit Chaining extension, and the contextual payload-generation extensions. Several of these extensions are paid (~$50-300 per year) and we cover the cost-benefit analysis for solo pentesters versus enterprise teams.

Beyond Burp, we cover lightweight CLI tools for AI-augmented recon — using GPT-4 / Claude APIs to summarise large attack surface inventories, auto-classify findings by severity, and generate reproducer scripts. This is the workflow Bangalore bug-bounty hunters use to triple their report-submission velocity. It's also exactly the workflow the Flipkart Bug Bounty Triage team uses internally — and the team they actively recruit from.

Block 2.2 — LLM red-teaming with garak (Week 5-6)

garak is NVIDIA's open-source LLM red-team framework. Released in 2023 and adopted heavily through 2024-2026, it's the de-facto standard for prompt-injection testing against deployed LLM applications. The framework ships with ~40 different probe categories ranging from basic prompt injection ("ignore previous instructions") through sophisticated multi-step jailbreaks (DAN, AIM, Crescendo), data exfiltration attacks (prompt-based PII extraction), and tool-use abuse for LLM applications that have function-calling capabilities.

We cover garak installation, configuration against a target LLM endpoint (whether it's a direct OpenAI / Anthropic API, an Azure OpenAI deployment, an AWS Bedrock model, or a custom-hosted vLLM / TGI deployment), probe selection methodology, custom probe development for application-specific attacks, and finding triage. The week culminates in a real garak red-team exercise against a vulnerable LLM application we've built specifically for the course — students get a complete pentest report deliverable that mirrors what they'd produce at Razorpay or Flipkart.

Block 2.3 — Microsoft Pyrit + OWASP LLM Top 10 (Week 6-7)

Pyrit (Promptflow Risk Identification Tool) is Microsoft's adversarial testing framework for AI systems. Open-sourced in 2024, it's the framework Microsoft AI Red Team uses internally and the toolkit any Microsoft / Azure-aligned AI security role expects familiarity with. Pyrit is structurally different from garak — it's an orchestration framework for chaining adversarial attacks rather than a probe library, which makes it more flexible but harder to start with. We cover both because the Bangalore hiring market expects both.

The OWASP Top 10 for LLM Applications (OWASP LLM Top 10) is the threat model that ties everything together. Released by OWASP in 2023 and updated through 2025, it covers LLM01 Prompt Injection, LLM02 Insecure Output Handling, LLM03 Training Data Poisoning, LLM04 Model Denial of Service, LLM05 Supply Chain Vulnerabilities, LLM06 Sensitive Information Disclosure, LLM07 Insecure Plugin Design, LLM08 Excessive Agency, LLM09 Overreliance, LLM10 Model Theft. We cover every entry with a hands-on lab. The OWASP LLM Top 10 is now the "OWASP Top 10" equivalent for AI red-teaming interviews at Bangalore product companies.

Complementary tools we cover this week: Promptfoo (for adversarial regression testing of production LLM features — what a security engineer would run weekly to catch new jailbreak techniques affecting their app), Lakera AI (commercial LLM firewall and red-team API — useful for testing your own LLM-firewall defences as well as attacking poorly-defended LLM applications), HiddenLayer (AI model security platform covering model tampering, extraction, evasion attacks — relevant for the model-theft and adversarial-example portion of the threat model).

Block 2.4 — Agentic AI red-teaming (Week 7)

This is the newest material in the curriculum and the area where Bangalore product companies are investing most heavily right now. Agentic AI systems — AI applications that can take multi-step actions, use external tools, and interact with APIs — present an attack surface that's qualitatively different from chat-only LLM applications.

We cover the agentic-attack taxonomy: tool-use abuse (getting an agent to call a tool it shouldn't be allowed to call), prompt-chain exploitation (manipulating one step in an agent loop to corrupt subsequent steps), reflection-loop manipulation (corrupting an agent's self-reflection step to break out of its sandbox), authentication boundary attacks (agents that mishandle which user's credentials they're acting on behalf of), excessive agency exploitation (LLM08 from the OWASP Top 10), and the supply-chain attack vector specific to agent frameworks (compromising the tool definitions or system prompts an agent depends on).

Hands-on labs include attacking a vulnerable LangChain agent, attacking a vulnerable AutoGen agent, attacking a vulnerable CrewAI multi-agent setup, and (the capstone of this block) attacking a vulnerable agentic application we've built specifically for the course that mirrors real production patterns. Students who complete this block well are immediately competitive for the AI Red Team L1 positions at Microsoft AI Red Team Bangalore and the equivalent roles at Razorpay, Cred, and the Bangalore satellite teams of US product companies.

Block 2.5 — Cloud-AI pentesting + Capstone (Week 8)

Final week covers cloud-AI pentest fundamentals — AWS Bedrock model red-teaming, Azure AI Studio adversarial testing, Google Vertex AI pentest. The fundamentals layer is shorter than students might expect because cloud-AI red-teaming is largely the application of Blocks 2.2-2.4 to cloud-hosted models, with cloud-specific authorisation considerations added in. The traditional cloud pentest topics (S3 misconfiguration, IAM privilege escalation, Lambda abuse, GuardDuty evasion) are covered briefly but the depth is in the 8-month flagship Cyber Security course for students who want AWS SCS-C02 or Azure AZ-500 certification preparation.

The capstone is the centerpiece of the course. Each student receives a real red-team engagement against one of the founder-owned product companies — QSecure (post-quantum payment security), 24Observe (observability platform), BrowserFog (browser security), AgentFog (agent security platform), or QSecNiti (security training platform). The engagement is structured as a real pentest — scope definition, attack-surface mapping, full pentest execution, written report deliverable in industry-standard format (executive summary + technical findings + CVSS scoring + remediation guidance), and a presentation to the actual engineering team that owns the target application. The capstone earns a verified 1-month work-experience certificate that students put on their resume — and several alumni have used the capstone deliverable as the centerpiece of their pentest portfolio when interviewing.

The standard Bangalore career trajectory for an AI-aware ethical hacker is: Junior Pentester / AI Red Team Analyst (₹7-12 LPA entry) → 18 months experience plus OSCP or another technical certification → Mid-level Pentester / AI Red Team Engineer (₹12-22 LPA) → 3-4 years experience plus a track record of published findings or bug bounty earnings → Senior Pentester / Red Team Lead (₹22-35 LPA) → 5-7 years total → Principal Red Team Engineer or AI Security Architect (₹35-55 LPA).

This trajectory assumes the student stays in technical individual-contributor roles. A separate management trajectory exists — pentest manager → security manager → CISO — and pays similarly at senior levels but requires less technical depth and more programme management skill. We focus on the IC trajectory in this course because it pays better for the first 6-8 years of career and the AI red-team skill set transfers more cleanly into senior IC roles than into management roles.

Alongside the salaried trajectory, the bug bounty trajectory is a real and growing alternative. Bangalore's bug bounty community is the largest in India — actively used by Razorpay (which runs a public bounty programme), Flipkart, PhonePe, Postman, Cred, MakeMyTrip, and most major BFSI captives. Active bug bounty hunters at the top of the Bangalore market report ₹3-12 LPA in passive bounty income on top of their day job, and a smaller but real cohort of full-time independent bug bounty hunters report ₹15-30 LPA total income with no fixed employer. The bug bounty path requires sustained effort and is genuinely competitive — we set realistic expectations during counselling rather than promising easy income.

Networkers Home was founded in Bangalore in 2007 by Vikas Swami, who holds dual CCIE certification (#22239 in both Routing & Switching and Security). Over 19 years of operation, the institute has placed 45,000+ engineers across the cyber security and networking industry. The placement team maintains active relationships with 800+ pan-India hiring partners.

The case for taking the ethical hacking course here specifically rests on three things. First, the founder's own product portfolio includes BrowserFog (browser security), AgentFog (agent security), QSecure (post-quantum payment security), 24Observe (observability with security focus), and QSecNiti (security training platform). The capstone red-team engagements happen against these real products, which means students get a verified work-experience reference for their resume. No other Bangalore institute can match this.

Second, the lab infrastructure is real production hardware accessed 24×7 — Cisco IOS-XE routers, Catalyst 9000 switches, Palo Alto PA-440 and VM-Series firewalls, FortiGate 80F, Check Point R82, Cisco ASA with Firepower, real AWS production accounts, real Azure tenants for cloud-AI pentest exercises. We use Packet Tracer for none of the labs. We use GNS3 for none of the labs. We use EVE-NG for none of the labs. Real hardware, real configurations, real recovery from real misconfigurations — and the GPU-accelerated infrastructure for the LLM red-teaming exercises in Month 2.

Third, the curriculum revision velocity matches the rate at which the AI pentest market is changing. Most Bangalore institutes update their syllabus once every 12-24 months. We've updated the ethical hacking curriculum three times in the last 18 months — adding the OWASP LLM Top 10 in late 2024, adding garak and Pyrit in mid-2025, adding agentic AI red-teaming in early 2026. This rate of update is sustainable because the founder is personally engaged in security product development through the founder-owned products and stays current with the threat landscape as a working practitioner, not as a former practitioner who's now full-time on instruction.

Month 1 (CEH v13 foundation) is delivered by senior pentest practitioners holding active credentials in CEH, OSCP, and CompTIA PenTest+. The lead Month 1 trainer has 12+ years of pentest practice across Bangalore product companies and consulting firms, and currently holds an OSCP certification with active Burp Suite Pro and Cobalt Strike licenses.

Month 2 (AI pentest) is co-delivered by Vikas Swami (Founder, Dual CCIE) and a senior trainer specializing in LLM security and agentic AI red-teaming. The Month 2 trainer's background includes contribution to the OWASP LLM Top 10 working group and active red-team engagement work for two Bangalore product companies (under NDA — references provided on request to enrolled students). Real practitioners, not full-time instructors who left field work years ago — that's the hiring criteria we apply to every trainer on the programme.

Eligibility is open to any graduate of any discipline (B.Tech, BCA, B.Sc, B.Com, B.A, BBA, MBA, M.Tech, M.Sc), final-year students of any undergraduate or postgraduate programme, and working professionals across IT and non-IT functions. No prior ethical hacking experience is required.

The only real prerequisite is networking knowledge at roughly CCNA level — understanding of OSI model, TCP/IP, subnetting, basic Linux command line, basic familiarity with HTTP and web application architecture. If you have a BTech CS / IT background you almost certainly have this knowledge already; if you don't, we provide a free 4-week pre-course track on NHPREP.com (the Networkers Home learning management system) that covers the necessary fundamentals. Students who complete the pre-course track perform indistinguishably from BTech-background students in the ethical hacking course itself.

Working professionals make up about 35% of every batch. Weekend intensive batches (Saturday-Sunday 10 AM-2 PM IST) are designed for this audience and avoid weekday work conflicts entirely. Many working professionals from Cisco India, Wipro EC, Infosys EC, Tech Mahindra Whitefield, IBM India ITPL, and the BFSI captives have taken this course on weekend intensive while staying full-time employed.