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Highlights from Cyber Tech Series, Part-1

CTO Community India: Software Vulnerability Assessment in the Era of AI

The CTO Community India recently hosted its fifth milestone series, pivoting from its previous explorations of AI , Quantum and Startups to the pressing frontier of Cyber Security in the AI Era.

Led by Anupama Itikirala, Founder of Mayuk Enterprises, and moderated by Richa Kumari , the session provided a masterclass in navigating the “new normal” where code is generated in seconds, but vulnerabilities can last a lifetime.

 The Session Agenda:

  • Career Resilience: Anupama’s 30-year journey from Enterprise Architect to a “Tech for Good” consultant.
  • The New Stack: Understanding vulnerabilities in the Generative AI architecture (Infrastructure vs. Model vs. App layer).
  • The “Why” of Security: A panel discussion on why automated cycles still need human-in-the-loop governance.
  • Deep Dive: Decoding the OWASP Top 10 for LLMs (Prompt Injection, Model Poisoning, etc.).
  • Demo: A first look at Garuda, a cost-effective, NLP-driven code scanning tool for startups.
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A Journey of Resilience and “Tech for Good”

Anupama Itikirala opened the session with a powerful personal narrative. With 30 years in the industry—including stints at Intel, Oracle, and GE—she shared her journey of restarting her career after a 2016 break.

Now a celebrated consultant and mentor, Anupama’s work is driven by “Tech for Good.” she emphasizes that technology must be inclusive, ethical, and, above all, secure.

The New Threat Landscape: Gen AI & the OWASP Top 10

The transition from predictive analytics to Generative AI has drastically expanded the attack surface. Anupama, broke down the critical evolution of the tech stack.

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Key Technical Takeaways:

  • Vulnerability vs. Risk: Vulnerability is the weakness; Threat is the actor; Risk is the impact.
  • The LLM Vulnerability Shift: Unlike traditional relational databases, Gen AI relies on unstructured data and complex “orchestration” layers, creating new backdoors.
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  • The OWASP Top 10 for LLMs: The session highlighted critical risks:
    • Prompt Injection: Malicious inputs designed to override AI safety guards.
    • Model Poisoning: Manipulating training data to create systemic biases or backdoors.
    • Excessive Agency: Granting AI “agents” too much power without a “human-in-the-loop” to verify actions.
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“Security is no longer a ‘nice-to-have’ in industries like automotive, a Bluetooth backdoor isn’t just a data leak; it’s a life-threatening risk.” — Abhishek Nema (CTO Community Member)

Innovation Spotlight: Project Garuda

In a standout segment, she demonstrated Garuda, her custom-built code scanning tool. Designed specifically for small companies and startups that find enterprise licensing (like SonarQube) prohibitive, Garuda offers:

  • NLP-Driven Heuristics: Uses programming language parsers to build abstract syntax trees.
  • Real-time Intelligence: Syncs with the National Vulnerability Database (NVD) twice daily.
  • Cost-Effectiveness: A service-based model that prioritizes resource support over expensive tool licenses.

Looking Ahead: What’s Next for the Community?

As the session concluded, the room buzzed with ideas for future deep dives. The community is looking toward:

  1. Testing LLMs: Addressing the “Black Box” nature of model outputs.
  2. RAG Implementation: Refining Retrieval-Augmented Generation for better information reliability.
  3. Indic Languages: Solving the security gap for non-English NLP databases.

A Note of Gratitude

We extend a heartfelt Thank You to our guest speaker, Anupama Itikirala, for sharing her deep technical expertise and inspiring career journey. Her passion for mentorship and “tech for good” is a beacon for our CTO community.

We also thank our active participants, whose insights into business continuity and automotive safety added invaluable layers to the discussion. It is your engagement that makes these sessions a powerhouse of collective wisdom.

Call to Action: Secure Your Future

Don’t let your innovation be derailed by a late-night security alert.

Join the Next Deep Dive: We are currently planning sessions on LLM Testing and RAG Implementation. Stay tuned for the invite!

Adopt “Secure by Design”: Whether you are a solo founder or an enterprise lead, integrate security filters and “human-in-the-loop” checkpoints today.

We encourage all members to adopt “Secure by Design” principles—especially those in the startup phase where ROI often overshadows safety.

47 thoughts on “Highlights from Cyber Tech Series, Part-1”

  1. The distinction between vulnerability, threat, and risk—and the warning about excessive agency—really stood out. Garuda’s focus on practical, affordable scanning for startups is especially valuable. I also appreciate the reminder that security needs human oversight, even as automation accelerates.

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    The distinction between vulnerability, threat, and risk—and the reminder that AI agents need human oversight—made this especially useful. I also appreciated the focus on Garuda as an affordable option for startups. Clear planning matters in any complex system; even WoW Forever Talent’s build calculator labels unverified preview ranks so players can

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  3. The session’s point about AI-generated code expanding the attack surface—and the need for human oversight—really stood out. Garuda sounds especially valuable for startups. For teams managing physical inventory or device labels, a browser-based barcode generator can also help create traceable labels without sending data to a server.

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    The distinction between vulnerability, threat, and risk really clarifies why AI security needs more than automated scans. I also appreciated the focus on Garuda’s practical value for startups and the reminder that human oversight matters when AI agents can take consequential actions.

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  5. The distinction between vulnerability, threat, and risk—and the examples of prompt injection and excessive agency—made the session especially practical. I also liked Garuda’s focus on affordable scanning for startups; thoughtful human oversight is essential as AI tools become more capable.

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  6. The point that AI-generated code can be produced in seconds while its vulnerabilities may persist for years really stood out. Garuda’s NLP-driven scanning sounds promising for startups, and clear, distinctive text styles could also help make security findings easier to highlight in reports and awareness materials.

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  7. The distinction between a vulnerability, a threat, and the resulting risk was especially clear, as was the reminder that AI agents need human oversight. For teams discussing topics like prompt injection or model poisoning, Unprompted could also be a handy way to spark fresh research and practice speaking through new security scenarios.

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  8. Motion Transfer

    The discussion of prompt injection, excessive agency, and keeping humans in the loop makes the risks of AI feel very concrete. I also appreciated the focus on practical, affordable security through Garuda—especially for startups that can’t justify enterprise tooling.

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  9. Marcus from Veo 3.1

    The shift toward automated vulnerability scanning in AI workflows is becoming unavoidable, especially as deployment cycles get tighter. The discussion on catching security flaws before models hit production touches on a real bottleneck most engineering leads are trying to balance right now.

    On the comms side of our dev updates, I occasionally test tools like Veo 3.1 Video Generator when we need to создать ии видео for quick internal explainers. Feeding it a straightforward prompt like “a glowing server rack flashing amber alerts” gave me a usable five-second backdrop in about two minutes; it won’t replace custom motion design for client-facing work, but it gets the point across during team syncs.

  10. Burning Bridges AI

    The discussion of prompt injection, model poisoning, and human-in-the-loop oversight makes the risks of generative AI feel very concrete. I also appreciated the focus on accessible scanning tools like Garuda for startups. For event recaps, Burning Bridges AI could turn a lead photo and supporting shots into a short video that brings the session hig

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  11. Jordan from Kling 4.0

    Vulnerability assessment is definitely getting trickier as more teams plug automated models directly into their development pipelines, especially when edge cases and unvetted dependencies slip through before deployment.

    On the media side, when I put together internal awareness clips explaining basic data hygiene, the Kling 4.0 tool I use saves me hours by letting me lock a reference image of a server room so the slow push-in shot stays consistent. It still requires some manual cleanup afterward, but setting that initial keyframe helps keep the shot grounded.

  12. The point about code being generated in seconds while vulnerabilities linger really hits home. It’s wild how fast AI is reshaping every layer of tech, and audio is no exception. I’ve been experimenting with sound scene creation lately, and tools like Seed Audio 1.0 can spin up entire scenes—dialogue, ambience, effects—from a single prompt. Curious how security concerns might apply to AI-generated media too. sound scene creation

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  17. The point about ‘Excessive Agency’ really resonates — granting AI agents too much autonomy without a human-in-the-loop seems like the risk teams most often overlook. Curious how the community plans to approach testing the ‘Black Box’ nature of LLM outputs in future sessions.

  18. Elena from GPT Image

    The discussion around vulnerability assessments in AI-driven workflows hits close to home. Teams are adopting internal tools faster than ever, and mapping out the actual surface area and access levels during security reviews has become much more complicated over the past year.

    From my end building front-end prototypes, that usually means keeping visual assets and wireframes strictly sandboxed. When I needed a quick sample dashboard for our security audit deck, I used GPT Image 2.5 to generate the interface cards; it took two or three tries to get the spacing right, but the status labels on the panels rendered legibly enough to use without redrawing them in Figma.

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  20. The discussion regarding software vulnerability assessment highlights the critical need for robust security frameworks as generative AI tools accelerate the development process.

  21. The discussion on software vulnerability assessments during the AI era highlights the critical need for robust security frameworks. Balancing the speed of automated code generation with long-term safety protocols is a significant challenge for modern engineering teams.

  22. Focusing on The Session Agenda: Career Resilience: Anupama’s 30-year journey from Enterprise Architect clarifies the trade-off better than a vague summary. Separately, if you want a short break, krillion.me is a free browser word game with no download.

  23. The point about “excessive agency” really hit home—giving AI agents too much autonomy without human verification is a disaster waiting to happen. I’ve been experimenting with an ai flyer maker lately, and even that makes me double-check outputs before publishing. Garuda sounds promising for startups priced out of enterprise tools.

  24. Focusing on The Session Agenda: Career Resilience: Anupama’s 30-year journey from Enterprise Architect clarifies the trade-off better than a vague summary. Separately, if you want a short break, noillirk.app is a daily word-guessing game with no download.

  25. The discussion on balancing the speed of AI-generated code with the long-term security implications highlights a critical challenge for modern software development. I work on CloneCut, an AI video tool.

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