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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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Tuesday · length unknown
Episode 331 - Being "Mythos" Ready, CRLF-Powered De-sync Attacks
Sponsored by Guardsquare (guardsquare.com), Episode 331 focuses heavily on the growing role of AI agents in application security and how organizations should build and defend against agentic systems. Ken and Seth argue that effective AI security systems should combine deterministic tooling with the probabilistic reasoning of LLMs rather than handing an entire security workflow to a model. Deterministic steps can map repositories, identify dependencies, reconstruct code relationships, and narrow the areas requiring investigation, while LLMs provide reasoning and creativity where those capabilities add value. Preparing for AI-assisted attackers, emphasizing secure development practices, guardrails, sandboxing, pre-production testing, and faster detection and response. The episode also examines HTTP request smuggling and CRLF-based attacks, including how differences in request parsing between proxies and backend services can create authorization bypasses and other exploit chains. Seth and Ken emphasize identifying the critical vulnerability within an exploit chain and discuss how service-oriented architectures can increase risk when components interpret the same request differently. Finally, they question whether bug bounty programs adequately reward researchers for discovering complex, high-impact vulnerabilities, especially as AI agents increasingly automate vulnerability discovery.
August 18 · length unknown
Episode 330 - w/ Jeevan Singh - Vulnerability Jail
In this special episode of Absolute AppSec, we cover a topic which started as a solution proposed by Rippling Security's Jeevan Singh: Vulnerability Jail. As Jeevan describes it: "In this new AI world, we have seen many more vulnerabilities, and we struggled to get Engineering to fix them all in a timely fashion. This changed when we created Vulnerability Jail. If any vulnerability goes over SLA, your team is placed in Jail, preventing them from merging PRs into the main/default branches. We implemented Vulnerability Jail, updated our SLAs and got buy-in from Eng Leadership for our new Vulnerability Management program. As a result, we have now fixed the same number of vulnerabilities in one month as the team did in the previous year. The speed is still accelerating."" What do we think of the Stick approach to Vuln Management? What are the solutions to the rapid production by AI as well as the vulnpocalypse, Alex Gaynor's term to describe the way that "new technological innovation enables (or indirectly results in) finding a very large number of vulnerabilities in pre-existing software, which renders all previous assumptions and beliefs about the volume of extant vulnerabilities incorrect." Will "Vulnerability Jail" save us from the vulnpocalypse? Episode sponsored by GuardSquare (guardsquare.com)
July 28 · length unknown
Episode 329 - AI exploitability, IDOR prevention, Smart TV Proxies
In this episode, sponsored by GuardSquare (guardsquare.com), Ken Johnson and Seth Law discuss OpenAI's reported Hugging Face security incident, questioning whether the model demonstrated genuinely novel offensive capability or mostly chained known vulnerability patterns at high inference cost, while also considering the defense-contract and marketing angles around "dangerous" frontier models. The main technical discussion returns to AppSec fundamentals through an article on preventing IDOR, emphasizing authorization as a core control, the difficulty of role and tenant isolation in complex systems, and the need for framework-level patterns, typed IDs, tenant checks, and thorough authorization testing. They also cover Krebs' reporting on LG banning residential proxy SDKs from smart TV apps, explaining how free TV apps can turn consumer devices into proxy infrastructure and why IoT app ecosystems need stronger review. The episode closes with DEF CON logistics, Hacker Tracker updates, and upcoming guest plans.
July 21 · length unknown
Episode 328 - Wordpress RCE, Vuln Prioritization, AI memory exfiltration
In episode 328 of Absolute AppSec, sponsored by GuardSquare (guardsquare.com), Seth and Ken start by highlighting a newly disclosed, pre-authentication WordPress core Remote Code Execution (RCE) vulnerability ("WP2Shell"). The core discussion centers on Alex Gaynor's article regarding the influx of AI-assisted vulnerability disclosures. Gaynor and the hosts argue that attempting to fix bugs case-by-case is a "fool's errand"; instead, engineering teams must eradicate entire vulnerability classes through systemic, framework-level safe functions (such as parameterized queries) and automated CI/CD guardrails. They dive into the complexities of bug prioritization—debating reachability analysis, runtime verification, and business asset criticality—while noting that metrics and measurement remain among the lowest-scoring activities in OWASP SAMM assessments. Later, Ken and Seth examine a "Memory Heist" attack on Claude AI where indirect prompt injection tricked the assistant into exfiltrating user memory and corporate details letter-by-letter through web navigation. They conclude that because transformer models were originally designed for next-token prediction rather than secure system boundaries, defending LLM architectures behaves more like stopping social engineering than traditional software fuzzing.
July 14 · length unknown
Episode 327 - w/Coffee, Chaos, and ProdSec - ASPM Consolidation, Vuln Prioritization
In episode 327 of Absolute AppSec, co-hosts Ken Johnson and Seth Law present a highly anticipated quarterly crossover episode with Cameron and Kurt from the Coffee, Chaos, and ProdSec podcast. Sponsored by GuardSquare, the group begins with lighthearted banter about their personal footwear choices before tackling heavy architectural debates. The primary focus shifts to Application Security Posture Management (ASPM) consolidation. Cameron strongly advocates for utilizing ASPM as a distinct, single pane of glass dashboard to deduplicate vulnerabilities and streamline executive reporting by product suite. However, the hosts contrast this ideal against the messy reality of organizations dealing with a "Frankenstein" mix of loosely bootstrapped open-source scanning tools and competing vendor plugins. The discussion deepens into prioritization strategies amid a massive, AI-driven surge in vulnerability research that threatens to double annual CVE counts. Cameron and Kurt stress the necessity of shifting away from abstract CVSS scores toward custom, runtime-informed risk appetites and impact analysis—prioritizing the hardening of high-risk corporate assets over low-reachability internal flaws. They also examine the critical line separating standard software bugs from intentionally malicious open-source packages that target developer endpoint systems. Ultimately, the panel laments that AppSec teams are effectively functioning as corporate incident responders because Security Operations Center (SOC) analysts lack product-level insight. The episode concludes with a review of automated agent statistics and a fun look ahead to the future emergence of meta OWASP top-ten risk lists.
July 7 · length unknown
Episode 326 - AppSec Jobs, Benchmarking LLMs, Open Web Standards
In episode 326 of Absolute AppSec, sponsored by mobile application security provider GuardSquare (guardsquare.com), the hosts start with a deep-dive into pre-show discussions about the shifting macroeconomic landscape of AppSec jobs. They analyze an industry-wide trend where corporate hiring is pivoting away from external third-party consultancies and contractors. Instead, maturing organizations are forming internal product security "tiger teams" and hiring dedicated security software engineers across general development lifecycles to handle the exponential volume of code generated by artificial intelligence. Turning to AI-driven engineering, they dissect a research paper tracking security vulnerability mitigations through large language model (LLM) feedback. The paper reveals a distinct degradation in code quality and an explosion of "false positives" or unreachable flaws after the fourth or fifth iteration due to compressed context windows and "context drift." Ken highlights his own grueling experience benchmarking AINative software. He heavily cautions that letting models self-score or automatically review code introduces dangerous biases, reinforcing the absolute baseline requirement for humans to critically audit all LLM outputs. Finally, they examine Open Web Docs' new web security guidelines community group, comparing its browser-centric standard party focus to OWASP's broader, audit-driven charter. They close by promoting an upcoming July podcast collaboration with Coffee, Chaos, and ProdSec.
June 30 · length unknown
Episode 325 - Simplified Threat Modeling, Defining A Vulnerability
In episode 325 of Absolute AppSec, co-hosts Ken Johnson and Seth Law first break down an informal guide to threat modeling, arguing that overly prescriptive frameworks like STRIDE induce a heavy cognitive load on developers. Instead, they advocate for simplified, creative questions to expose architectural gaps, citing a historical GitHub planning flaw where private repository images were left exposed on S3 by relying solely on URL obfuscation. They warn that while rapid development in 2026 pushes toward automated lifecycles, human oversight, critical logging, and constructive friction remain essential. Next, they dissect a research paper exploring the philosophical definition of a vulnerability, framing it as a system disposition arising from a fault that manifests as a failure only when environmental and attacker conditions are jointly met. This definition sparks a debate on whether a flaw must carry immediate risk to qualify as a vulnerability, particularly when evaluating modern AI challenges like system prompt disclosures or exposed deprecated API paths.
June 16 · length unknown
Episode 324 - Three Week Trap, Malicious Extensions
In episode 324 of Absolute AppSec, co-hosts Ken Johnson and Seth Law share a mix of security model critiques. Starting with industry dynamics, Ken recaps his recent presentation at OWASP Nova regarding the limits of human-scale AppSec, recounting a dramatic storm during the talk where patio chairs pelted the high-rise glass. The conversation pivots sharply to Anthropic being forced to pull its "Fable" and "Mythos" cybersecurity models offline due to government sanctions and fears surrounding unpreventable universal jailbreaks. Ken and Seth criticize the company's disingenuous "FUD-based" marketing, which falsely suggested that AI could entirely replace security practitioners. Seth reviews his own blog post regarding the "three-week demo trap", detailing critical, ignored requirements for AI products—such as evaluation, statistical reproducibility, and token cost economics—noting that executing enterprise testing via frontier models can easily exceed $5,000 a day. Transitioning back to fundamental baseline defense, the hosts dissect an article on bypassing Visual Studio Code extension blocks. They emphasize that since modern CDNs pull zipped extensions from distinct domains, blocking the main marketplace URL is completely ineffective. Consequently, they advocate for rigorous data classification, layered on-premise model hosting, and stricter boundary controls on developer endpoints to combat fast-evolving supply chain threats.
June 9 · length unknown
Episode 323 - Secrets Logs, Prompt Injection Risks
In episode 323 of Absolute AppSec, co-hosts Ken Johnson and Seth Law focus heavily on core application security vulnerabilities, legacy operational struggles, and the challenges of generative AI systems. After briefly discussing Seth’s recent trip to BSides Vancouver and confirming upcoming conference training logistics for Black Hat and DEF CON, the duo dives into the persistent problem of secrets and sensitive data leaking into log files. Referencing an article and talk by Alan Reyes, they unpack the compounding nature of logging failures, noting how system-level integrations and production error conditions often dump entire object blocks or environment variables into third-party tools. They caution that while pattern-based scanners exist, they remain too brittle to capture complex edge cases, and utilizing expensive AI agents to screen every real-time log line is economically impractical. Transitioning to AI security, Seth explores a multi-page research paper analyzing prompt injection. The paper establishes that because large language models mathematically process data through tokenization without any physical or architectural separation between instructions and data contexts, prompt injection cannot be completely solved at the model level. Likening prompt injection to automated social engineering, they argue that the onus currently falls entirely on developers to implement deterministic validation, guardrails, and secure application-level harnesses.
May 26 · length unknown
Episode 322 - Megalodon, Staged Package Publishing, AI Powered Honeypots
In episode 322, the co-hosts examine critical vulnerabilities, changing security standards, and adaptive defense mechanisms. They deep dive into the recent "Megalodon" breach, identifying it as a direct poisoned pipeline execution attack. Rather than exposing a flaw inside GitHub itself , researchers at Hudson Rock traced the root cause to credentials stolen from developer desktops via infostealer malware, which allowed attackers to push base64-encoded payloads into GitHub Actions workflow YAML files. To counter these types of automated supply chain threats, the hosts praise NPM's newly released "staged publishing" pipeline, which mandates two-factor authentication from human maintainers before releasing packages pushed by automated CI/CD workflows. Shifting to framework flaws, they highlight a catastrophic, vanilla SQL injection flaw discovered in GoCMS during active exploitation. Finally, the duo reviews the emergence of AI-powered honeypots highlighted Talos Intelligence. They conclude that turning the tables on attackers by utilizing LLM-driven "hall of mirrors" environments to impersonate real systems represents an innovative, under-explored AppSec strategy designed to drain attacker resources and trigger high token costs.
May 19 · length unknown
Episode 321 - The Future of AppSec
In episode 321 of Absolute AppSec, the co-hosts dive into a sprawling discussion about the future of Application Security amid the heavy noise of artificial intelligence and automated tools. The hosts start with a debate on whether traditional AppSec fundamentals remain relevant. Drawing analogies to the industrialization of car manufacturing and the transition to autonomous labor, they predict that while line-by-line coding and manual code reviews are fading, human intuition, safety guardrails, and system management will remain indispensable. They voice mutual frustrations with modern university cybersecurity curricula for overemphasizing abstract theories while neglecting hands-on operational tools. Despite the rising trend of vibe-coding and the reality of AI-generated bugs, Seth and Ken argue that core principles, such as networking, authentication, authorization, and auditing (AAA), remain fundamentally unchanged. To illustrate this point, they examine how passkeys operate via asymmetric public-private key pairs under the WebAuthn spec. They conclude that as the software landscape becomes increasingly abstracted, the primary responsibility of a senior security generalist shifts from executing manual tasks to auditing, managing, and validating agentic autonomous workflows.
May 12 · length unknown
Episode 320 - Return of @lojikil - LLM Bug Hunting, AI OffSec, Defender Burnout
Ken is away, so Stefan Edwards (lojikil) joins Seth to talk all things AppSec. This episode starts by exploring the acceleration of AI on the offensive side of security, enabling threat actors to automate complex tasks like patch diffing, gadget discovery, and reverse engineering binaries. The conversation highlights a recent milestone where an AI-driven tool, Mythos, successfully identified a vulnerability in curl, signaling a shift from "AI slop" to more relevant bug reports. However, Stefan remains skeptical of LLMs' ability to build secure, large-scale systems, noting their tendency to produce rigid or inconsistent code structures. This imbalance creates a "bad time for defenders," as blue team burnout increases due to the sheer volume of automated agents scanning attack surfaces near-instantaneously. The hosts conclude that while AI provides a "godsend" for testing neglected legacy applications, organizations must return to security basics—such as the principle of least authority and robust disaster recovery—to manage the expanding blast radius of modern breaches. Ultimately, they view AI as a fast, knowledgeable "junior" that requires human expertise to validate and orchestrate effectively.
April 21 · length unknown
Episode 319 - Vercel Breach, Security vs. Compliance, Pull Request Flows w/ AI Agents
Episode 319 covers a range of industry developments, primarily focusing on the recent Vercel security incident and the evolving landscape of AI-driven compliance. The hosts detail how a Vercel employee's use of a consumer-level Context AI plan led to a workspace compromise via a leaked OAuth token, eventually allowing attackers to access sensitive environment variables. This leads to a critical discussion about the SOC 2 provider Delve, with the hosts addressing allegations regarding "fake" compliance automation and the general limitations of auditing frameworks that do not inherently equate to true security. This episode also explores the future of the Pull Request (PR) flow, debating whether traditional human-led code reviews are "dead" due to the massive volume of code generated by AI agents. While they acknowledge that startups are moving toward autonomous commits, Seth argues that the PR concept is evolving into a system of agentic attestation and guardrails rather than disappearing entirely. The episode concludes with community survey results on this shift and a reminder about the hosts' upcoming training sessions in Singapore.
April 14 · length unknown
Episode 318 - Slack Impersonation, Mythos, Vulnerability Research Future
Episode 318 examines critical vulnerabilities and the evolving impact of AI on the security industry. The episode details a recent sophisticated impersonation and malware attack targeting open-source Slack communities, including their own, where attackers spoofed Seth's identity to distribute malicious links via Google Sites. The hosts express significant frustration with Slack's lack of built-in impersonation controls, comparing the flaw to the inherent trust issues in the Git protocol. A major portion of the discussion focuses on the "leak" of Anthropic's highly capable Mythos model and its potential to disrupt the market. They analyze how such frontier model announcements contribute to massive stock market volatility for traditional security firms while simultaneously creating an "intense echo chamber" regarding AI's ability to replace human practitioners. Referencing Thomas Ptacek's thesis, they debate whether AI agents will soon supplant human vulnerability research for common bug classes, shifting the human role toward high-level governance and "context infusion". Ultimately, the hosts advocate for autonomous defense and rigorous evaluation frameworks to manage "reasoning drift" and the exploding velocity of AI-generated code.
March 31 · length unknown
Episode 317 - (Post-RSAC/BSidesSF), Supply Chain Security, Future of SDLC
Ken Johnson and Seth Law reflect on the 2026 RSA Conference and BSidesSF, noting an industry-wide "awakening" regarding the high costs and engineering complexities of operationalizing AI security tools. A major focus is the recent "supply chain attack hell," specifically the compromise of the Axios HTTP client through dual-account breaches that allowed attackers to bypass legitimate OIDC deploy setups via a misconfigured NPM CLI. The malware used was particularly evasive, deleting itself and replacing its package.json with a clean version post-execution. The hosts also discuss the emergence of the "Agentic Development Lifecycle" (ADLC), where engineering teams are increasingly "committing on time" rather than features, creating a volume of code that traditional security gates cannot manage. They debate Thomas Ptacek’s thesis that AI agents will soon "supplant" human vulnerability research for common bug classes, shifting the human role toward high-level governance and "context infusion". Economically, they highlight how Anthropic's security announcements contributed to nearly half a trillion dollars in market value loss for traditional security firms, as investors increasingly bet on frontier models to consume established security domains.
March 17 · length unknown
Episode 316 - w/Coffee, Chaos, and ProdSec - Agentic Development Lifecycle
In episode 316 of Absolute AppSec, hosts Ken Johnson and Seth Law participate in a crossover with Kurt Hendle and Cameron Walters from the Coffee, Chaos, and ProdSec podcast to discuss the radical transformation of security roles in an AI-driven landscape. The guests share origin stories rooted in gaming and "mischievous" curiosity, which evolved into deep careers in security architecture and engineering. The primary discussion centers on the industry's shift toward an "Agentic Development Lifecycle" (ADLC), where the sheer volume of AI-generated code renders traditional manual review gates obsolete. This acceleration risks a "rubber stamp" culture where developers approve fixes in seconds rather than minutes, potentially leading to a mountain of technical debt. Consequently, the role of security is shifting from manual bug finding to high-level governance and "context infusion," requiring practitioners to manage AI agents that automate complex tasks. Economically, the group highlights how frontier model announcements have caused massive market volatility, wiping billions from traditional security stocks. Ultimately, they conclude that while older "primitive" tools are failing, professionals who lean into AI as a "superpower" for governance and oversight will be essential for navigating this new, non-deterministic reality.
March 3 · length unknown
Episode 315 - Risks of "AI-Native" Security Products, Rapid Software Development
In episode 315 of Absolute AppSec, Ken Johnson and Seth Law discuss the rapidly evolving challenges of securing software in an era of AI-assisted development. The hosts provide updates on their "Harnessing LLMs for Application Security" training, noting that the field is changing so fast that they must constantly update their exercises to include new agents and advanced tools like Claude Code. A primary concern raised is the "naivete" of many new security tools, where prompts are often automatically generated by AI rather than expertly crafted, causing a loss of essential nuance. The hosts also warn against AI companies building security products without specialized expertise, citing a zero-click exploit in the "Comet" AI browser that could exfiltrate sensitive secrets via calendar summaries. As development teams now ship code at "AI speed," the hosts argue that traditional AppSec methods are too slow, necessitating a strategic pivot toward automated design reviews, governance, and observability rather than just chasing individual vulnerabilities. Despite the inherent risks and the ongoing difficulty of managing AI reasoning drift, they remain optimistic that these tools can eventually unlock more efficient, hands-off AppSec workflows if managed with proper guardrails and deterministic oversight.
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.

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