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Absolute AppSec

Ken Johnson and Seth Law

A weekly podcast of all things application security related. Hosted by Ken Johnson and Seth Law.

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  • 23 episodes
  • weekly
  • English

Episodes 23

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  • February 24 · length unknown

    Episode 314 - LLM AppSec Disruption, Limitations of AI in Security, AppSec Oversight

    In this episode, the hosts discuss the seismic shift in the application security landscape triggered by the rise of Large Language Models (LLMs) and Anthropic’s "Claude Code". They highlight the massive economic repercussions of these AI advancements, noting that billions in market value were wiped from traditional cybersecurity stocks as investors begin to believe frontier models might eventually write perfectly secure code. The hosts critique the industry's historical reliance on "checkbox" compliance tools like SAST, DAST, and SCA, arguing that these "archaic" methods are being replaced by AI-native strategies capable of reasoning through complex logic flaws. While they acknowledge that AI can suffer from "reasoning drift" and still requires deterministic validation to avoid false positives, they emphasize that security professionals must adapt by building custom "skills" and focusing on governance and observability. The discussion concludes that as developers move to "AI speed," the traditional role of the AppSec professional is evolving into a "Jarvis-like" orchestrator who manages automated workflows and infuses institutional knowledge into AI agents to maintain oversight without slowing down production.

  • February 17 · length unknown

    Episode 313 - AppSec Role Evolution, AI Skills & Risks, Phishing AI Agents

    Ken Johnson and Seth Law examine the intensifying pressure on security practitioners as AI-driven development causes an unprecedented acceleration in industry velocity. A primary theme is the emergence of "shadow AI," where developers utilize unauthorized AI coding assistants and personal agents, introducing significant data classification risks and supply chain vulnerabilities. The discussion dives into technical concepts like AI agent "skills"—markdown files providing specialized directions—and the corresponding security risks found in new skill registries, such as malicious tools designed to exfiltrate credentials and crypto assets. The hosts also review 1Password’s SCAM (Security Comprehension Awareness Measure), highlighting broad performance gaps in an AI's ability to detect phishing, with some models failing up to 65% of the time. To manage these unpredictable systems, the hosts advocate for a shift toward high-level validation roles, emphasizing the need for Subject Matter Expertise to combat "reasoning drift" and maintain safety through test-driven development and periodic "checkpoints". Ultimately, they conclude that while AI can simulate expertise, human oversight remains vital to secure the probabilistic nature of modern agentic workflows.

  • February 10 · length unknown

    Episode 312 - Vibe Coding Risks, Burnout, AppSec Scorecards

    In episode 312 of Absolute AppSec, the hosts discuss the double-edged sword of "vibe coding", noting that while AI agents often write better functional tests than humans, they frequently struggle with nuanced authorization patterns and inherit "upkeep costs" as foundational models change behavior over time. A central theme of the episode is that the greatest security risk to an organization is not AI itself, but an exhausted security team. The hosts explore how burnout often manifests as "silent withdrawal" and emphasize that managers must proactively draw out these issues within organizations that often treat security as a mere cost center. Additionally, they review new defensive strategies, such as TrapSec, a framework for deploying canary API endpoints to detect malicious scanning. They also highlight the value of security scorecarding—pioneered by companies like Netflix and GitHub—as a maturity activity that provides a holistic, blame-free view of application health by aggregating multiple metrics. The episode concludes with a reminder that technical tools like Semgrep remain essential for efficiency, even as practitioners increasingly leverage the probabilistic creativity of LLMs.

Showing 21–23 of 23 episodes