OWASP Global AppSec USA 2026: Full Schedule

arrow_back View All Dates

10:30am PST

Losing Context: Breaking & Binding MCP Sessions

Friday November 6, 2026 10:30am - 11:15am PST

Session Access Control – The Missing Validation Layer The Model Context Protocol (MCP) specification explicitly distinguishes sessions from authentication but provides minimal prescriptive guidance on authorization enforcement. This talk explores the theoretical security implications of this design, where session IDs function similarly to bearer tokens but often lack the granular security controls required for enterprise-grade deployments.

The SDK Security Gap: An analysis of current MCP SDK implementations reveals an inconsistency in how session security is handled. While the specification provides various validations, most SDK implementations provide only basic checks, leaving critical validation decisions to developers without clear documentation or guidance.

Session Hijacking in MCP – Attacks and Mitigations We will examine how session hijacking attacks apply to MCP’s stateful transport model. Through concrete architectural examples and demonstrations of three High Severity CVEs affecting officially supported MCP SDKs, we will analyze specific attack vectors that allow unauthorized parties to hijack valid session contexts. Additionally, we will briefly examine two further CVEs related to the broader MCP SDK ecosystem. We will also touch upon the upcoming MCP spec 2026-07-28 changes that eliminates protocol-level session management but the security problem remains in application-level state. We conclude with practical, defense-in-depth strategies, including duplicate connection prevention, user binding, strict session expiration mechanisms, and robust validation patterns that developers can implement to harden their MCP servers regardless of their chosen SDK.

Attendees will gain:
- A comprehensive understanding of MCP’s session model and the mechanics behind the two CVEs in MCP SDKs.
- Analysis of which SDKs provide built-in session security and which require custom implementation.
- Actionable security patterns for binding sessions to authenticated users.
- Practical mitigation strategies for preventing session hijacking and unauthorized resource access.

Speakers

Srikanth Ramu

Principal Security Engineer

I am an Application Security professional with extensive experience in product security, built on a solid foundation in development and QA. During the COVID-19 pandemic, I developed an interest in hunting bugs in open-source libraries specifically targeting Java Deserialization vulnerabilities... Read More →

Friday November 6, 2026 10:30am - 11:15am PST
Room: Grand Ballroom B (Street Level)

Implementation

Audience Intermediate

11:30am PST

The Hidden Effort Curve of Remediation: 15,000 Fixes, 500 Projects, 9 Languages

Friday November 6, 2026 11:30am - 12:15pm PST

Room: Grand Ballroom B (Street Level)

Every week brings another headline about a new way to find vulnerabilities in open-source and other code. The much-talked-about “Vulnpocalypse” is coming. But the bottleneck was never finding vulnerabilities, it is fixing them. We wanted to know how much effort this will take.

Every security team triages its backlog the same way: sort by CVSS, fix the criticals first. That ranking quietly assumes severity tells you how much work a fix will be. We tested that assumption against data and found it not to be true!!

Using AI-assisted analysis, we measured the remediation effort for 1,127 fixed vulnerabilities across 20 open-source projects: Firefox, Django, PostgreSQL, Keycloak, Tomcat and others that span nine languages. For each one we pulled the actual fix commits, scored the change on a three-part difficulty rubric, and sorted it into Low, Medium, High, or Extra High effort.
This talk walks through the data, shows where severity-first triage misjudges the work, and gives you a class-based way to estimate effort you can try on your own findings immediately. By November the dataset will cover 500+ projects and 15,000+ remediations. Given the timing, we will include data on vulnerabilities surfaced by Mythos-class models and techniques and whether that newer class of findings is harder or easier to remediate.

This is a data-heavy talk. If you are a data geek, you’ll enjoy it.

Speakers

Michael Cartsonis

Co-Founder, AppSecAI

Michael Cartsonis is a co-founder of AppSecAI . OWASP OASIS project and co-author of Two Cycles, One Codebase: A New Operating Model for Application Security.

At AppSecAI, Michael leads product strategy for the industry's first AI-powered Fix Automation system that generates valid... Read More →

Bruce Fram

CEO, AppSecAI

Bruce Fram is the CEO of AppSecAI, his and was a six-time venture-backed CEO before including being the CEO of Contrast Security. He started as a hands-on coder, spent two decades running companies instead of writing code, and credits GenAI with handing the ability to answer complex... Read More →

Friday November 6, 2026 11:30am - 12:15pm PST
Room: Grand Ballroom B (Street Level)

Implementation

Audience All

1:15pm PST

So you think AI writes secure code?

Friday November 6, 2026 1:15pm - 2:00pm PST

Room: Grand Ballroom B (Street Level)

Software development is becoming AI-assisted at every stage — design, coding, testing, bug fixing — and AI agents are increasingly doing it all. But do AI coding assistants actually write secure code by default? Most of the conversation around AI and security focuses on AI finding vulnerabilities. Far less attention goes to how state-of-the-art coding agents behave when they're the ones writing the software in the first place.

We built an automated harness to answer this directly — generating and evaluating over 2,500 code samples across multiple languages, models, and coding tasks, then scoring them with SAST tooling for introduced vulnerabilities. We tested vanilla generation against several security-steering approaches, from a single-line instruction file to a full set of layered security skills, to see which techniques move the needle, and at what cost.

In this talk, we'll walk through the harness architecture, share our full results — including where steering helped, where it hurt, and why — and lay out a practical framework for guiding coding agents toward secure defaults without paying an unsustainable token or performance tax. Attendees will walk away with a reusable methodology for evaluating their own AI coding assistants, and concrete, evidence-backed steering techniques they can apply immediately.

Key Takeaways
- A reusable methodology for benchmarking any coding assistant or model for security regressions before rolling it out to developers
- Evidence on which security-steering techniques actually reduce vulnerabilities, and by how much
- An understanding of the token-cost and latency tradeoffs of different steering approaches
- A practical framework for shifting security left into the AI-assisted SDLC

Speakers

Shruti Datta Gupta

Product Security Engineer, Adobe

Shruti Datta Gupta is a Product Security Engineer at Adobe where she works in the Security AI & Data Engineering team. Her current role involves building AI-powered tools to automate security processes and reduce engineering toil. She is passionate about applying AI to solve cool... Read More →

Joseph Seasly

Security AI & Data Engineer, Adobe

Joseph does Security AI and Data Engineering at Adobe. In his former life, he spent 13 years in the U.S. Intelligence Community working in a variety of agencies, technical roles, and missions.
linkedin.com/in/josephs1000
... Read More →

Friday November 6, 2026 1:15pm - 2:00pm PST
Room: Grand Ballroom B (Street Level)

Implementation

Audience Intermediate

2:15pm PST

When Nobody Wrote the Code: Engineering Lessons from Building AI-Native Application Security

Friday November 6, 2026 2:15pm - 3:00pm PST

Room: Grand Ballroom B (Street Level)

We didn't set out to rethink Application Security.

Our goal was much simpler: remove repetitive security work without reducing engineering confidence.

Like many security teams, we began introducing AI into parts of our AppSec workflow—reviewing pull requests, proposing remediation, assisting with threat modeling, validating findings, and helping developers move faster without sacrificing security.

Some things improved almost immediately.

Others became unexpectedly harder.

The first surprise wasn't model quality—it was review capacity. As AI started proposing fixes faster than engineers could reasonably validate them, we discovered that generating secure code was no longer the difficult part. Deciding whether that code could be trusted was.

We also found ourselves asking questions we hadn't expected. Why were experienced reviewers approving changes they couldn't realistically read? Why were different AI workflows confidently disagreeing with each other? Why were we spending less time finding vulnerabilities and more time deciding which results deserved human attention?

As these experiments accumulated, one theme kept reappearing. The biggest shift wasn't simply that AI generated more code—it reduced the cost of implementation while exposing new bottlenecks in review, verification, governance, and evidence. That, in turn, led us to question several engineering assumptions that quietly shape today's AppSec practices.

This session shares the implementation journey behind those discoveries. Through practical engineering experiments, implementation mistakes, and lessons learned, we'll explore how familiar AppSec practices—including secure coding, threat modeling, SAST, DAST, CI/CD security, and supply chain security—continue to matter while evolving for AI-assisted software engineering.

This isn't a talk about replacing today's AppSec practices.

It's about understanding which assumptions continue to hold, which ones deserve to be revisited, and how security teams can evolve their existing programs for a world where generating software is becoming easier while proving software is trustworthy is becoming the harder engineering problem.

Speakers

Manoj Kumar Yuvanesh

Senior Manager, Trust Data Platform, Autodesk Inc

Manoj Kumar Yuvanesh is a Senior Engineering Manager at Autodesk, where he leads the Trust Data Platform within the Trust Organization.

His work focuses on building large-scale data systems and security automation capabilities that help organizations understand and improve their security posture. With deep experience across security tooling, architecture, and cloud platforms, he drives initiatives that integrate security... Read More →

Uday Bhaskar Seelamantula

Principal Application Security Engineer, Autodesk

Uday is a principal security engineer at Autodesk, where he focuses on securing applications at the intersection of traditional software and emerging AI features. His work spans offensive research, fuzzing, threat modeling, building guardrails and integrating security into the SDLC... Read More →

Friday November 6, 2026 2:15pm - 3:00pm PST
Room: Grand Ballroom B (Street Level)

Implementation

Audience Intermediate

3:30pm PST

Pre-Flight Security Review for MCP Servers Using the OWASP MCP Top 10

Friday November 6, 2026 3:30pm - 4:15pm PST

Room: Grand Ballroom B (Street Level)

Since Anthropic released MCP as an open standard, enterprises have started adopting it as a common way to connect AI agents with tools, data sources, and business workflows. Many teams are now building MCP catalogs for internal developers, platform teams and external partners.

However, the security posture of these MCP servers is often not reviewed before they are added to a catalog or connected to an AI agent. In many cases, deeper security testing starts only after the MCP server is already in use.

Recent research has shown how a malicious or poorly reviewed MCP server can expose sensitive data, influence an agent’s behavior or override instructions given by the user. This makes MCP discovery an important early checkpoint for developer pre-flight checks, security approval, third-party MCP review, vendor or partner assessment and agent platform onboarding.

For traditional applications, software bills of materials (SBOMs) and configuration drift checks help teams understand what is being adopted and what has changed. MCP servers need a similar approach. In this talk, I will walk through a three-layer MCP BOM model: Discovery, Verified, and Runtime.

I will focus on the Discovery BOM and show how static MCP discovery can surface early indicators of tool poisoning, command injection and execution, context injection and over-sharing, credential-like inputs and risky tool capabilities. I will demonstrate this using an open-source tool that discovers MCP metadata and capabilities, runs static checks with YARA rules and maps findings to the OWASP MCP Top 10.

The goal is not just to scan an MCP server once, but to use discovery output as a pre-flight check: to review MCP servers before approval, detect MCP configuration and metadata changes in CI/CD, build safer MCP catalogs and create the first version of runtime monitoring and policy decisions.

Attendees will leave with a practical way to inspect MCP servers before agents use them, map exposed capabilities to OWASP MCP risks, compare MCP configuration drifts over time and answer a basic but important question during MCP security review: "What should be allowed, reviewed, or denied before the agent uses this MCP server?"

Speakers

Vinothini Raju

Founder & CEO, gopaddle.io

Vinothini Raju, is the Founder & CEO at gopaddle.io. She has been awarded the B2B Woman Tech Entrepreneur of the Year, 2023 by Women In Cloud & Insight Enterprises. Under her leadership, gopaddle focuses on building a next-generation platform for cloud native applications. Her... Read More →

Friday November 6, 2026 3:30pm - 4:15pm PST
Room: Grand Ballroom B (Street Level)

Implementation

Audience Intermediate

10:30am PST

11:30am PST

1:15pm PST

2:15pm PST

3:30pm PST

Get help with the event