The Application Security Podcast

Are your developers still reading their security findings, or are their agents answering for them? Ahmad Sadeddin, founder and CEO of Corgea, brings data from Corgea's customers: replies to security comments written with em dashes jumped from 2.5 percent in May to about a third, and once long, verbose replies are counted, somewhere between 35 and 60 percent come from agents. Chris and Ahmad dig into developers using agents to wave off findings as false positives, why commits per PR keep climbing, and what Ahmad calls headless AppSec, where agents review, triage, and fix for other agents. They debate what AI security review really costs, whether non determinism is a dealbreaker when human reviewers were never consistent either, and why roughly 45 percent of developer false positive calls are wrong.
This episode is sponsored by Corgea. Design it. Build it. Ship it. Corgea secures it.
About Corgea
Corgea is an AI-native application security platform that secures software from design to production. It brings together security design reviews, AI SAST, dependency and IaC scanning, code quality checks, and autonomous pentesting—helping security and engineering teams find risk earlier, fix what matters, and ship securely.
→ Learn more about Corgea
Connect with Ahmad Sadeddin:
→ Corgea
→ Corgea on LinkedIn
Mentioned in this episode:
→ GitHub stacked pull requests (public preview)
→ Claude Mythos Preview and Project Glasswing
→ Corgea Build vs. Buy SAST calculator
Follow the Application Security Podcast:
➜ Home: appsecpodcast.com
➜ X: @AppSecPodcast
➜ LinkedIn: The Application Security Podcast
➜ YouTube: @ApplicationSecurityPodcast
➜ Instagram: @appsecpodcast
➜ Facebook: Application Security Podcast
Chapters:
00:00:00 - Cold open: AppSec is going agent to agent
00:00:21 - Meet Ahmad Sadeddin
00:00:37 - Welcome and a sponsor disclosure
00:01:36 - Ahmad's security origin story
00:02:54 - From payments security to founding Corgea
00:05:01 - Security budget vs. security by design
00:07:57 - Will AppSec miss the boat on AI?
00:09:55 - Security is taste
00:10:49 - You can inform the model, but you can't mandate it
00:12:29 - Where autonomous agents should never run
00:13:53 - Inside Corgea's research on developer responses
00:16:11 - No human uses an em dash
00:17:28 - Good thing or bad thing?
00:18:16 - Weaponizing agents to mark false positives
00:20:41 - Are agents making developers worse at security?
00:22:36 - Long replies put agent responses at 35 to 60 percent
00:24:20 - Non determinism and an overnight agent loop
00:26:15 - The Miss America problem: AI reviews that never stop
00:28:32 - More commits per PR, and why
00:30:40 - Headless AppSec: agents talking to agents
00:32:44 - Token burn and AI budgets
00:34:34 - LLM courage and the real cost of AI security review
00:36:39 - Prediction: AI budgets get scrutiny
00:38:04 - Can AI ever be deterministic?
00:39:14 - Humans aren't deterministic reviewers either
00:41:52 - Takeaway: 45 percent of false positive calls are wrong
00:44:29 - A risk score on every PR
00:46:45 - Canary deployments for AI code review
00:47:28 - Wrap up: measure your own repos

What happens when a protocol goes from idea to everywhere before security can catch up? Vandana Verma Sehgal, leader of the OWASP MCP Top 10, returns to explain why most organizations cannot say how many MCP servers are running on their developers' machines. She walks Chris and Robert through how MCP turns a chatbot into a new execution layer, how four lines of malicious code in a tiny server can slip past everyone, and why shadow MCP servers are shadow IT with direct access to action. The three debate whether we are missing the window to build AI security in from the start, why consent fatigue is undermining human in the loop, and where command execution really happens. Plus: why a secure MCP server should be boring, and why no MCP server deserves trust on day one.
This episode is sponsored by Security Compass. Make modern software development secure, consistent, and provable.
About Security Compass
AI writes code faster than anyone reviews the design. Threats do not wait for an annual assessment. Security Compass models threats continuously and turns them into requirements developers act on, not a report read after ship.
→ Learn more about securing the AI-DLC with Security Compass
This episode is sponsored by Corgea. Design it. Build it. Ship it. Corgea secures it.
About Corgea
Corgea is an AI-native application security platform that secures software from design to production. It brings together security design reviews, AI SAST, dependency and IaC scanning, code quality checks, and autonomous pentesting—helping security and engineering teams find risk earlier, fix what matters, and ship securely.
→ Learn more about Corgea
Connect with Vandana Verma Sehgal:
→ Vandana Verma Sehgal on LinkedIn
Mentioned in this episode:
→ OWASP MCP Top 10
→ OWASP MCP Top 10 on GitHub
→ OWASP Top 10 for Large Language Model Applications
→ OWASP Top 10 for Agentic Applications for 2026
→ OWASP Agentic Skills Top 10
→ Model Context Protocol
→ EU AI Act (Regulation (EU) 2024/1689)
→ Singapore IMDA: Model AI Governance Framework for Agentic AI
Follow the Application Security Podcast:
➜ Home: appsecpodcast.com
➜ X: @AppSecPodcast
➜ LinkedIn: The Application Security Podcast
➜ YouTube: @ApplicationSecurityPodcast
➜ Instagram: @appsecpodcast
➜ Facebook: Application Security Podcast
Chapters:
00:00:00 - Cold open: with great power comes great responsibility
00:00:20 - Meet Vandana Verma Sehgal
00:00:34 - Welcome and what gets Vandana away from screens
00:03:05 - What is MCP, and why should AppSec teams care now?
00:06:56 - MCP moved faster than any protocol before it
00:10:30 - Are we missing the window to secure AI?
00:12:31 - Harnesses, an AI security manifesto, and the EU AI Act
00:17:50 - Why the world needed an OWASP MCP Top 10
00:21:02 - Where command execution really happens
00:23:57 - How the list was built: community feedback and CVE data
00:26:46 - MCP09: shadow MCP servers
00:29:39 - If you could fix only one: scope creep
00:30:48 - Authentication, authorization, and delegated authority
00:35:24 - Consent fatigue and the human in the loop
00:37:04 - What a secure MCP server looks like: boring by design
00:41:27 - How AppSec teams should engage developers building MCP
00:44:46 - How to contribute to the OWASP MCP Top 10
00:45:41 - Key takeaway: never trust an MCP server on day one

What happens when a tsunami of AI-written code meets a security industry that has spent decades chasing vulnerabilities? Brook S.E. Schoenfield, CTO of Rezliant and author of Securing Systems, returns to warn about "the illusion of omniscient perfection," the cheerful confidence that makes AI output feel finished, and the "learned fragility" that sets in when nobody understands the code anymore. He, Chris, and Robert debate whether an AI threat model that gets 90% of the way there is a win, how Brook now uses AI for reachability analysis, and why prompt injection traces back to a 1975 design principle we ignored. They ask what architecture even means in the age of AI, where the next generation of architects will come from if nobody writes code, and why the collapsing cost of fixes means it's time to stop chasing vulnerabilities.
This episode is sponsored by Security Compass. Make modern software development secure, consistent, and provable.
About Security Compass
AI writes code faster than anyone reviews the design. Threats do not wait for an annual assessment. Security Compass models threats continuously and turns them into requirements developers act on, not a report read after ship.
→ Learn more about securing the AI-DLC with Security Compass
This episode is sponsored by Corgea. Design it. Build it. Ship it. Corgea secures it.
About Corgea
Corgea is an AI-native application security platform that secures software from design to production. It brings together security design reviews, AI SAST, dependency and IaC scanning, code quality checks, and autonomous pentesting—helping security and engineering teams find risk earlier, fix what matters, and ship securely.
→ Learn more about Corgea
Connect with Brook S.E. Schoenfield:
→ Brook S.E. Schoenfield on LinkedIn
→ brookschoenfield.com
Mentioned in this episode:
→ Rezliant
→ Securing Systems: Applied Security Architecture and Threat Models by Brook S.E. Schoenfield
→ Saltzer and Schroeder: "The Protection of Information in Computer Systems" (1975)
→ Izar Tarandach on LinkedIn
→ Dwarkesh Patel: "The Rise and Fall of Agent Civilizations" (essay on the OpenAI–Hugging Face incident)
→ Kadrey v. Meta (2025 fair use ruling on AI training)
Follow the Application Security Podcast:
➜ Home: appsecpodcast.com
➜ X: @AppSecPodcast
➜ LinkedIn: The Application Security Podcast
➜ YouTube: @ApplicationSecurityPodcast
➜ Instagram: @appsecpodcast
➜ Facebook: Application Security Podcast
Chapters:
00:00:00 - Cold open — The illusion of omniscient perfection
00:00:48 - Welcome back, Brook S.E. Schoenfield
00:01:51 - AI is writing code and filling the security skills gap
00:06:18 - Can AI threat model as well as the experts?
00:08:46 - Is 90% of the way there good enough?
00:13:47 - Closing one weakness beats chasing perfection
00:16:33 - When AI threat modeling is enough, and when it isn't
00:17:54 - Learned fragility
00:19:26 - Embrace securing AI or be left in the dust
00:23:41 - Against set and forget: agent drift and AI ethics
00:29:30 - What does architecture mean in the age of AI?
00:30:29 - Mixing control and data planes: the root of prompt injection
00:32:49 - Reachability: how Brook threat models with AI today
00:35:08 - Diagram drift and inclusive threat modeling
00:38:46 - Will developers disappear and architects emerge?
00:41:00 - The cost of code has collapsed
00:44:33 - Where will the next architects come from?
00:49:15 - Final thoughts: stop chasing vulnerabilities

Jim Manico thinks the era of human code review is ending, and that clinging to it will hurt your company. The founder of Manicode Security returns to explain why AI didn't kill AppSec education but supercharged it, why vague prompting on frontier models turns companies into "token furnaces," and why prompt injection is the one genuinely new vulnerability class of the AI era. He walks Chris and Robert through his full AI coding workflow, from reverse engineering an architecture file to security rules and planning-mode build plans that make AI output deterministic. The three debate whether AI will finally eliminate SQL injection, whether AppSec vendors can survive without integrating cyber models, and when humans still need to step in: the moment an agent tries something its policy doesn't allow. Plus: the one habit every security leader should teach developers now.
This episode is sponsored by Security Compass. Make modern software development secure, consistent, and provable.
About Security Compass
AI writes code faster than anyone reviews the design. Threats do not wait for an annual assessment. Security Compass models threats continuously and turns them into requirements developers act on, not a report read after ship.
→ Learn more about securing the AI-DLC with Security Compass
This episode is sponsored by Corgea. Design it. Build it. Ship it. Corgea secures it.
About Corgea
Corgea is an AI-native application security platform that secures software from design to production. It brings together security design reviews, AI SAST, dependency and IaC scanning, code quality checks, and autonomous pentesting—helping security and engineering teams find risk earlier, fix what matters, and ship securely.
→ Learn more about Corgea
Connect with Jim Manico:
→ Jim Manico on LinkedIn
Mentioned in this episode:
→ Manicode Security
→ Manicode Forge
→ OWASP Artificial Intelligence Security Verification Standard (AISVS)
→ OWASP AISVS on GitHub
→ Claude Code
→ Ollama
Follow the Application Security Podcast:
➜ Home: appsecpodcast.com
➜ X: @AppSecPodcast
➜ LinkedIn: The Application Security Podcast
➜ YouTube: @ApplicationSecurityPodcast
➜ Instagram: @appsecpodcast
➜ Facebook: Application Security Podcast
Chapters:
00:00:00 - Cold open: the era of code review is ending
00:00:47 - Meet Jim Manico
00:01:03 - Welcome and what gets Jim away from screens
00:05:29 - How AI changed developer security education
00:07:03 - Teaching developers to use AI well
00:09:26 - Where AI and AppSec stand: the token furnace
00:12:08 - Separating signal from hype
00:14:24 - Integrate with cyber models or die: the future of AppSec tools
00:18:34 - Are AI coding assistants creating new vulnerabilities?
00:20:02 - Prompt injection: the one truly new class
00:21:15 - Will AI eliminate the OWASP Top 10?
00:24:18 - Local models and Apple's hardware edge
00:28:32 - Jim's AI coding workflow, step by step
00:33:57 - The end of human code review
00:38:31 - Can we trust AI code review, and when do humans step in?
00:44:56 - Where companies really are with AI
00:47:02 - One change for security leaders: planning mode
00:48:19 - Wrap up

Three years ago, Jeevan Singh mapped out what an application security engineer needed to know. AI has rewritten the job since. Jeevan, Director of Security Engineering at Rippling, returns to unpack how his team polices thousands of engineers shipping 10x more code: a "vulnerability jail" that locks non-compliant teams out of the main branch, AI-reviewed extension requests, and homegrown agents that hunt for entire classes of vulnerabilities instead of one bug at a time. He and Chris debate whether AI has killed classic SAST and DAST, whether code review still needs a human in the loop, and whether bug bounty programs still make sense when the researchers on both sides are running the same models. Plus: one concrete move every AppSec leader can make this quarter.
This episode is sponsored by Security Compass. Make modern software development secure, consistent, and provable.
About Security Compass
AI writes code faster than anyone reviews the design. Threats do not wait for an annual assessment. Security Compass models threats continuously and turns them into requirements developers act on, not a report read after ship.
→ Learn more about securing the AI-DLC with Security Compass
This episode is sponsored by Corgea. Design it. Build it. Ship it. Corgea secures it.
About Corgea
Corgea is an AI-native application security platform that secures software from design to production. It brings together security design reviews, AI SAST, dependency and IaC scanning, code quality checks, and autonomous pentesting—helping security and engineering teams find risk earlier, fix what matters, and ship securely.
→ Learn more about Corgea
Connect with Jeevan Singh:
→ Jeevan Singh on LinkedIn
Mentioned in this episode:
→ Rippling
→ Dwarkesh Patel: "The Rise and Fall of Agent Civilizations" (essay on the OpenAI–Hugging Face incident)
Follow the Application Security Podcast:
➜ Home: appsecpodcast.com
➜ X: @AppSecPodcast
➜ LinkedIn: The Application Security Podcast
➜ YouTube: @ApplicationSecurityPodcast
➜ Instagram: @appsecpodcast
➜ Facebook: Application Security Podcast
Chapters:
00:00:00 - Cold open: vulnerability jail
00:00:55 - Meet Jeevan Singh
00:01:11 - Welcome and Robert's AI lab
00:02:37 - What gets Jeevan away from the machines
00:04:51 - Hardware projects with his son
00:06:20 - What's changed for the AppSec engineer since AI
00:08:17 - Shipping production code and fixing whole vulnerability classes
00:09:13 - Why AppSec has to become less collaborative
00:10:02 - From democratized vuln management to vulnerability jail
00:11:50 - How engineering reacted and the feature flag jail precedent
00:14:05 - From manual jail to automated checks
00:15:30 - An AI bot that reviews SLA extensions
00:16:06 - Can AI wipe out an entire vulnerability class?
00:17:36 - Building an anti-SSRF library and rolling it out
00:19:40 - Which AppSec skills matter now
00:22:28 - Validating all that AI-generated code
00:22:57 - Agents that hunt for vulnerability classes
00:24:38 - Is this the death of classic AppSec tools?
00:26:51 - Code review and humans in, on, and out of the loop
00:28:00 - Objective-based agents that find RCEs
00:28:59 - Build vs. buy for AppSec teams
00:31:29 - Advice for teams of one to five AppSec engineers
00:32:58 - Cutting SLAs to 3, 5, 7, and 10 days
00:34:31 - Parachuted in as the only AppSec engineer
00:37:59 - One investment to make this quarter
00:39:09 - The Hugging Face and OpenAI agent incident
00:40:13 - Is bug bounty dead?
00:42:19 - Key takeaways: be an engineer, run toward AI
00:43:53 - Wrap-up