#secure coding

Master AI security with these 17 essential steps! #AISecurity #DataProtection #CyberSecurity

In today’s digital landscape, securing AI applications is crucial for maintaining trust and ensuring data integrity. Here’s a comprehensive guide to the 17 essential steps for fortifying your AI application. 1. Encrypt Data Ensure that all data, both in transit and at rest, is encrypted. Use industry-standard encryption protocols like AES (Advanced Encryption Standard) for data at rest and TLS…

Rethinking LLM Integration: The Junior Developer Mental Model for AI Security

RSAC 2026 highlights a critical shift in software engineering: moving from blind trust in AI toward a rigorous 'junior developer' review framework to mitigate security and logic errors.

"[...] I have immersed myself in AI-driven development, accumulating over 633 million tokens with Claude in just a month, resulting in a total spend of $522, primarily on Opus 4.5 for complex coding tasks. What started as a vibe has evolved to a systematic product management and delivery system, leveraging agents, skills, and commands to deliver high quality and secure solutions. There's an incredible opportunity to enable people to produce high quality work at speeds we've only dreamt of."

This to me is a deeply troubling thought. So he starts by boasting how little thinking he has done and how much money it cost him to not think. Notice the trumpeting of $522 and the number of token being handed over to and from Claude. Then he follows up by saying that it produces high quality work at speed. On what metric does it do that? Is this just better than what he can create, or is this good as far as he is concerned? Is this objectively amazing code? I can tell you it's not. If it was then why are there so many developers who say that it creates work for them more often than it saves them work?

"This hands-on experience has enhanced my focus on integrating security with AI innovation. I have been developing projects where agentic security reviews are triggered via GitHub Actions, utilizing Claude to automate vulnerability scans and compliance checks. Additionally, I maintain customized system prompts that direct Claude to proactively incorporate security best practices—such as input validation, encryption, and access controls—during the implementation phase."

The first sentence just makes me chortle. Calling an LLM "AI" is like calling your shoe a hammer. Then he talks about "agentic security reviews" and vulnerability scans this to me is hilarious. I have significant experience in the realm of static code analysis, and I can tell you for a fact that tools get the job part of the way, and people part of the way, and then there is all the stuff that is missed. This is the reality of this problem–it is hard and it is unsolved and LLMs have not moved that problem into the solved category.

Here is the real issue: writing secure code is hard. Every project is different and the way secure code is going to look is also going to be a bit different. Furthermore, what is required for a given application is not a fixed point. For example: is it a problem that I run a Python SimpleHTTP server in my home lab, for a static page that is only accessed in my network? Probably not, but if I was to put that on the internet–big problems.

LLMs don't understand–anything. They have no judgement. They have no experience. They are simply plagiarizing others work and giving you the endorphin rush of accomplishment without any effort of skill gains.

This idea that making customized prompts and this fiddling he is doing is anything more than an exercise in delusion is just sad.

"Looking forward, I recognize significant opportunities in AI-enhanced threat detection, such as real-time anomaly detection in logs, and secure agentic workflows for DevSecOps teams. This approach is transforming how we create safer systems without compromising speed."

This is not a new idea. People have been using "AI" for security and log analysis for years. In fact this has been the case long before this LLM fad drove the world up the wall.

His final analysis is just so out of touch with reality. That LLMs are improving speed and safety. For example, you can look here where the vendor lays out some of the risks of AI generated code. Remember this guy is using the AI to write the code and review the code to make him feel good that it is secure and that he accomplished something–without any effort or thought.

If you actually do research into the topic what you find is that at best LLM code is as secure as human code–occasionally more so. However, if the LLM is doing rarely better than a human, but the perception is that it is doing far better than a human consistently than the LLM is actually worse than a human coder.

Perception drives actions, and if we delude ourselves into thinking LLM generated code is better than people, then we are just inviting the same bad code and insecure code into our projects that a person would make. Remember these LLMs are just generating the most likely result. This is based on human and LLM code. This means that you are getting results that are going to represent the most common best and worst mixed with possible or even likely hallucination. Does that sound like a recipe for better than human code with better than average security and practices?

By 2025, security shouldn’t be an afterthought in your pipeline—it should be baked in from Day 1. As someone who’s broken builds and fixed late-night exploits, I can tell you that DevSecOps Certification is much more than just another line on your resume. It’s the turning point into a safer, smarter development mindset.

From “Fast” to “Secure and Fast”

I started my career in DevOps, racing to ship features as fast as possible. But a single security incident—an exposed API key in a pull request—changed everything. That moment taught me that shipping without secure coding checklists is like leaving your front door unlocked.

That’s when I decided to invest in DevSecOps Certification. I didn’t want to just patch vulnerabilities—I wanted to evolve how my team builds and deploys, securely.

What You Actually Learn (Not Just Buzzwords)

Here’s what diving into DevSecOps certs actually equips you to do:

· CI/CD Security: Automatically scan for vulnerabilities before deploy,no more manual gatekeeping.

· Cloud Security: Understand IAM roles, avoid misconfigurations, and add encryption builds into Terraform.

· Application Security: Embed SAST checks, validate input properly, and avoid dangerous dependencies.

· Secure Coding: Learn to write code that defaults to deny, not allow.

After my certification (I took SANS SEC540), I rewrote error-handling in our microservices and found two major vulnerabilities before prod. That alone repaid the course fee—but the confidence boost was priceless.

Certifications That Serve You, Not the Other Way Around

Here are the ones I’ve found eye-opening:

1. Certified DevSecOps Professional (CDP) Hands-on labs where you break and fix pipelines intentionally—that “aha!” moment stays with you.

2. SANS SEC540 My personal favorite for cloud-native security. Walks you through real-world misconfigs and remediation.

3. CSSLP (Certified Secure Software Lifecycle Professional) Ideal if you're deep into application architecture and writing code—focuses on application security and secure development lifecycles.

4. PMI-ACP with DevSecOps Focus If you're part of a product or process-heavy environment, this brings cloud security and Agile frameworks into one plan.

How to Turn Certification into Habit

Programming certificate online are great, but habits keep you secure. Here’s what worked for me:

· Immediately apply new checks in live projects—not placeholder tutorials.

· Teach or mentor teammates. Sharing is learning.

· Get active in communities. GitHub, Slack channels, meetup groups—we all learn faster together.

· Maintain a “security diary” : log small wins like "caught an open S3 bucket" or "added vault-based secrets."

Final Thoughts: DevSecOps Is a Journey, Not a Checklist

By now, you’ve hopefully seen why DevSecOps Certification feels different—and meaningful. It’s not just about studying; it's about shifting your role into a security champion.

Learn how to secure your Django applications with this comprehensive guide. Follow best practices for secure configurations, user authentication, preventing common threats, and more.

Introduction Security is a critical aspect of web application development. Django, being a high-level Python web framework, comes with numerous built-in security features and best practices. However, developers must be aware of additional steps to ensure their applications are secure. This guide will cover essential security practices for securing Django applications, including setting up secure…

Best Practices For Secure Coding: Tips To Enhance Application Security

🔒✨ Strengthen your code fortress! Discover the 9 essential principles for secure software development.

LEE’s Web Hacking (SQL-injection AND SECURE-CODING Skills)

Dziś z ranku złapałem kolejny , tym razem chwilowo darmowy kurs. Polecam serdecznie:

https://www.udemy.com/course/lees-web-hacking-sql-injection-and-secure-coding-skills/

Pamiętajcie , w każdej chwili promocja może zniknąć.