In this episode, a debate about hacker movies turns into a deeper conversation about AI, security, and the human-in-the-loop illusion. We explore how approval fatigue and AI-generated code can create a false sense of security and why fundamentals still matter.

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Are we improving security, or just automating bad decisions faster?

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In this episode, we break down the “AI Vulnerability Storm” and what happens when AI can find—and exploit—vulnerabilities faster than humans can fix them.

We explore how compressed OODA loops are shifting the balance toward attackers, why traditional scoring like CVSS may start to break down, and whether “just patch faster” is even realistic anymore. The team also questions the push toward AI agents everywhere—and whether fighting AI with more AI actually solves the problem.

At the end of the day, it comes back to fundamentals: reduce your attack surface, simplify your systems, and focus on what actually matters.

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Is this a real shift in security—or just faster chaos?

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In this episode, we explore a simple but surprisingly deep question: what would application security look like if generative AI never existed? We break down how AppSec might still rely on deterministic, rule-based approaches, what we might gain in structure and rigor, and what we’d lose in speed, scale, and accessibility. Along the way, we debate whether AI is truly improving security or just accelerating existing problems, from “vibe coding” and false confidence in results to the growing gap between finding and fixing vulnerabilities.

We also get into the tension between human-driven security practices and AI-assisted workflows, and whether the biggest challenges in AppSec are actually technical at all or still rooted in people and process. Plus, things take a turn as we let AI weigh in…and roast us a bit in the process.

Per usual, it’s a mix of thoughtful discussion, strong opinions, and a little chaos.

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We made it to 100 episodes, so naturally, we decided to look back and see how wrong we’ve been. In this episode, we revisit some of our past topics, predictions, and hot takes to figure out what still holds up and what didn’t quite land. From “we don’t know what we don’t know” to the evolution of security tools, we reflect on what’s changed, what hasn’t, and why some problems never seem to go away. Along the way, we compare where we were then to where things stand now, calling out a few wins, a few misses, and everything in between. After all this time, are we actually any smarter, or just better at explaining the same problems? This episode is part reflection, part reality check, and a look at what 100 episodes have really taught us.

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In this episode, we dive into the messy reality of AI agents acting inside your systems and what that means for modern security. We explore the idea of agents as actors with real access—credentials, APIs, and permissions—and why this isn’t as new as it sounds (hint: it’s just applications all over again). We unpack where things actually get risky, from over-permissioned agents to unpredictable behavior driven by prompts, and why “it won’t go rogue” might be missing the point entirely. We also question the growing hype around AI governance, whether security teams are actually gaining control or just making more lists, and what happens when agents start talking to each other… and running up your bill. Per usual, the conversation is filled with sarcasm, skepticism, and a healthy dose of “maybe just add parental controls.”

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In this episode, we dive into the strange world of invisible Unicode attacks and what they could mean for modern software security. We explore how hidden characters can be used to conceal malicious code within packages, why this isn’t entirely a new problem, and whether current tools, such as linters and SAST, are equipped to detect it. We also question the role of LLMs in both enabling and detecting these attacks, and whether this is a real emerging threat or just another overhyped security scare. Per usual, the conversation is filled with sarcasm, skepticism, and a healthy dose of “just don’t do it.

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In this episode, we discuss the implications of AI technologies like OpenClaw and Moltbot, exploring the potential threats and societal changes that may arise from their integration into daily life. We talk about the nature of AI communication, the concept of agentic AI, and the philosophical questions surrounding the future of human and machine interaction. Per usual our conversation is laced with humor and skepticism about the rapid advancements in AI and their impact on society.

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Are cybersecurity technologies really dead, or are reports of their demise greatly exaggerated? Today’s episode is a discussion on how AI is reshaping the classic build vs. buy debate, empowering non-engineers to create working prototypes and potentially reviving the DIY coding culture of pre-open-source days. We also talk about how developers trained on open source are now leveraging AI built from that same foundation, raising questions about innovation and originality in modern programming.

Build vs Buy is Dead - AI Just Killed It

Traditional Code Review is Dead

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