BEGIN:VCALENDAR
VERSION:2.0
X-WR-CALNAME:owasp25thanniversaryvirtualconfe
X-WR-CALDESC:Event Calendar
METHOD:PUBLISH
CALSCALE:GREGORIAN
PRODID:-//Sched.com OWASP 25th Anniversary Virtual Conference (September)//EN
X-WR-TIMEZONE:UTC
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T160000Z
DTEND:20260922T165000Z
SUMMARY:Opening Remarks and Keynote
DESCRIPTION:\n
CATEGORIES:KEYNOTE
LOCATION:
SEQUENCE:0
UID:8afdb633cfbcaea0257456940959dc87
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/8afdb633cfbcaea0257456940959dc87
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T165000Z
DTEND:20260922T165500Z
SUMMARY:Chapter Highlight
DESCRIPTION:\n
CATEGORIES:OWASP CHAPTER HIGHLIGHT
LOCATION:
SEQUENCE:0
UID:7801f0e134b0cbccc5a4aac32318e1dd
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/7801f0e134b0cbccc5a4aac32318e1dd
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T170000Z
DTEND:20260922T175500Z
SUMMARY:From Silos to Alliances: Cryptographic Threat Hunting in OT Environments
DESCRIPTION:Operational Technology (OT) environments face a critical paradox: sophisticated attacks like TRITON\, CRASHOVERRIDE\, and INCONTROLLER routinely target multiple facilities\, yet operators remain blind to cross-site attack patterns due to strict privacy regulations\, competitive secrecy\, and an inherent lack of trust. The current "share after detection" model—where threat intelligence is exchanged only after a breach is confirmed—creates a deadly information asymmetry. Attackers see the entire battlefield\, while defenders fight isolated skirmishes.This talk introduces a cryptographic framework that flips this paradigm to "share to detect." Aligned with OWASP's focus on Privacy Controls and IoT/OT Threat Intelligence\, this session will demonstrate how multiple OT sites (refineries\, power plants\, water utilities) can collaboratively identify globally significant threats before individual sites recognize them as localized attacks. Crucially\, this is achieved without exposing sensitive operational data\, process telemetry\, or revealing which facility discovered the threat.By deploying autonomous "hunter agents" at historian databases and SCADA systems\, the proposed architecture leverages commutative encryption and secure multi-party computation (SMC). It safely answers the question: "Is this anomalous PLC behavior a coordinated\, industry-wide attack?"We will walk through a practical scenario demonstrating how an alliance of sites can collectively validate a suspicious Modbus command sequence. We will show how a weak signal—appearing at only 15% local prevalence—can be cryptographically verified as a global Indicator of Compromise (IoC) active across 87% of participating sites. This validation triggers an immediate\, coordinated defense while mathematically guaranteeing that Site A never learns Site B's process parameters\, alarm rates\, or asset inventory.Target Audience: Security architects\, OT/ICS defenders\, and threat hunters looking to implement privacy-preserving intelligence sharing without centralizing sensitive telemetry.Attendees will learn:The Pitfalls of Centralization: Why traditional\, centralized threat intel sharing and data lakes fail in highly regulated OT environments (and the lessons learned from those failures).Applied Cryptography for Blue Teams: A functional breakdown of the cryptographic primitives enabling "origin-anonymous" threat artifact exchange.Practical Deployment: How to deploy autonomous threat-hunting agents directly within existing ICS historian infrastructure.Measurable Impact: Real-world attack scenarios where cryptographic collaborative detection provides 10-100x faster response times.
CATEGORIES:IMPLEMENTATION
LOCATION:
SEQUENCE:0
UID:17e2c48fd21e0e52c240efa98ed2a6ff
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/17e2c48fd21e0e52c240efa98ed2a6ff
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T170000Z
DTEND:20260922T175500Z
SUMMARY:Closing the AI Visibility Gap: Why SBOM Alone is No Longer Enough
DESCRIPTION:The shift toward Software Bill of Materials (SBOM) and its extension\, the Artificial Intelligence Bill of Materials (AIBOM)\, is a fundamental change in how we manage risk\, security\, and compliance in the modern digital world. As an organization\, adopting both of these frameworks doesn't just check a box\, it provides a crucial\, non-negotiable layer of transparency that is essential for both operational excellence and legal defense.\nIn short\, SBOM gives you a complete\, structured inventory of the code and libraries in your software\, allowing for fast vulnerability response and license management. AIBOM takes this concept further\, providing an inventory of the non-code components of an AI system\, the models\, training data\, and configurations\, to manage risks unique to artificial intelligence like bias\, data leakage\, and adversarial attacks.
CATEGORIES:PLANNING AND DESIGN
LOCATION:
SEQUENCE:0
UID:aff970db32021a94b20c727d47c077d5
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/aff970db32021a94b20c727d47c077d5
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T180000Z
DTEND:20260922T185500Z
SUMMARY:Guardrails First: Building AI Agents That Won’t Leak Your Secrets
DESCRIPTION:As generative and agentic AI rapidly enters security workflows\, practitioners face a difficult choice: leverage AI to enhance efficiency\, or risk exposing sensitive data to systems that weren’t designed with security in mind. For me\, as a security engineer and pentester\, this challenge is especially important - pentesting often involve confidential data\, proprietary code\, and high-impact vulnerabilities that cannot leave controlled boundaries.\nIn this talk\, I would like to share my own practical lessons learned from designing and deploying AI agents specifically for security testing use cases. When building your own agent for security testing purposes\, you often face a lot of issues\, related to privacy\, data protection\, efficiency and cost-optimization. In my talk we’ll explore how to build AI agents with strong guardrails from the ground up: isolating execution environments\, minimizing data exposure\, utilizing obfuscation practices without a negative impact on performance\, implementing secure prompt handling\, and enforcing strict boundaries between sensitive inputs and model interactions. I’ll also cover architectural patterns that enable safe augmentation of pentesting workflows without introducing new attack surfaces or compliance risks and what is more important\, do not cost you an arm and a leg.\nAttendees will gain insights from practical experience into how to safely integrate AI into daily workflows\, whether they are building internal tools\, experimenting with agentic systems\, or securing AI-enabled applications. This session is designed for security professionals\, developers\, DevOps engineers and everyone who want to utilize the power of AI without turning it into a new source of security risks.\nThe goal is simple: build AI agents that work for you\, not against you.
CATEGORIES:IMPLEMENTATION
LOCATION:
SEQUENCE:0
UID:1e053e6c32f6ca4c8abf88b8cc50217d
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/1e053e6c32f6ca4c8abf88b8cc50217d
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T180000Z
DTEND:20260922T185500Z
SUMMARY:OWASP Cornucopia - Gamifying AI Threat Modeling and Security Requirement analysis
DESCRIPTION:Shift-left doesn't start with scanning the code for security vulnerabilities\; it begins with design.Too often\, the shift-left mantra consists of implementing (AI-powered) code scanning and applying AI-powered security fixes for remediation. Also\, don't forget to implement the AI-powered benchmark for AI-powered Security Fixes. Now\, to be clear\, I am not actually telling you to stop using these tools — if they work for you — instead\, we should ask ourselves:What are we working on?What can go wrong?What are we going to do about it?Did we do a good job?In order to support that second question in particular\, we have created the next version of OWASP Cornucopia (see:&nbsp\;https://cornucopia.owasp.org/card/webapp/AZ2/3.0/en).OWASP Cornucopia is a mechanism in the form of a card game to assist software development teams in identifying security requirements in Agile\, conventional\, and formal development processes. It is language\, platform\, and technology-agnostic.The formerly titled “Cornucopia — Ecommerce Website Edition” is now “Cornucopia — Website App Edition”. This edition was originally created in August 2012\, released as v1.0 in February 2013\, and has undergone several minor updates/releases over the following ten to fifteen years. This has been substantially updated in v2.0\, in which the most noticeable change was an update of the OWASP ASVS mapping from ASVS v3.0 to v4.0\, together with the creation of translations into six languages (EN\, ES\, FR\, NL\, NO-NB\, and PT-BR) due to the efforts of past and current volunteers.The new version\, available in 10 languages (EN\, ES\, FR\, HI\, NL\, NO-NB\, PT-PT\, PT-BR\, RU\, UK)\, will include all new cards and text that cover all OWASP ASVS 5.0 requirements and connect them to more than 200 unique common attack patterns (CAPEC). Each of the common attack patterns will have a unique set of ASVS requirements\, which means that you never need to stop playing the game! You will always be able to return to the same card to discover new threats and security requirements to consider when building your software. Additionally\, we are publishing the OWASP Cornucopia Companion Edition (see:&nbsp\;https://cornucopia.owasp.org/edition/companion/AAIA/1.0/en&nbsp\;that comes with 6 companion suits (see:&nbsp\;https://cornucopia.owasp.org/edition/companion&nbsp\;) covering new topics: Agentic AI (AAI)\, Automated Threats (BOT)\, Cloud (CLD)\, Frontend (FRE)\, Large Language Models (LLM)\, and DevOps (DVO). A suit in the companion deck may replace (or be used in addition to) suites in the existing Website Edition so that the players can add a specific focus to their threat modeling: For example\, say you are building an LLM application and want to perform threat modeling specifically for LLM. You would then use the OWASP Cornucopia Website Edition and the LLM companion suite as your elected OWASP Cornucopia focus area.What’s more\, it is now possible to create your OWASP Cornucopia Threat Model in OWASP Threat Dragon using their brand new EoP Games diagram (see:&nbsp\;https://www.threatdragon.com/
CATEGORIES:PLANNING AND DESIGN
LOCATION:
SEQUENCE:0
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URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/afaf6e1c280e6a5810d210e4d7af198d
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T185500Z
DTEND:20260922T190000Z
SUMMARY:Chapter Highlight
DESCRIPTION:\n
CATEGORIES:OWASP CHAPTER HIGHLIGHT
LOCATION:
SEQUENCE:0
UID:38b4bfa536a4c107f59f492acfe547a9
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/38b4bfa536a4c107f59f492acfe547a9
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T190000Z
DTEND:20260922T200000Z
SUMMARY:Lunch Break
DESCRIPTION:\n
CATEGORIES:
LOCATION:
SEQUENCE:0
UID:9b6c41c9f8e3fcd0100c26e35ccfbc70
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/9b6c41c9f8e3fcd0100c26e35ccfbc70
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T195500Z
DTEND:20260922T200000Z
SUMMARY:Chapter Highlight
DESCRIPTION:\n
CATEGORIES:OWASP CHAPTER HIGHLIGHT
LOCATION:
SEQUENCE:0
UID:3ae8fc648e2298b65a83ee64d608df20
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/3ae8fc648e2298b65a83ee64d608df20
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T200000Z
DTEND:20260922T205500Z
SUMMARY:How a Clean Security Audit Became a Breach Notification Six Months Later
DESCRIPTION:Pre-deployment security reviews cover what you configured. They do not cover what your environment looks like six months later after multiple teams have touched it\, new services have been granted access\, and permissions have accumulated in ways nobody explicitly decided. Most organizations treat a clean security review as a checkpoint rather than a snapshot\, and that distinction matters a great deal when something goes wrong.This session is built around a real incident. A cloud environment passed its security review. IAM configurations were reasonable at the time of review. What the review did not cover was any mechanism to detect when those configurations drifted over time through legitimate activity: new role bindings added by different teams for different features\, each individually justifiable\, collectively dangerous. Six months later that drift became the entry point for a breach.The talk walks through the full incident arc: what the environment looked like before and after\, what the attack activity looked like in audit logs and why existing alerts did not fire\, and what the architecture looked like after being rebuilt with configuration drift detection as a first-class concern. All tooling demonstrated is native to the cloud platform\, no third-party products. Attendees leave with the specific log queries\, alerting configurations\, and policy controls that would have caught this incident before it became one.
CATEGORIES:DEPLOYMENT AND MAINTENANCE
LOCATION:
SEQUENCE:0
UID:a9b34fca9b00fcb77cf0e09b438c1790
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/a9b34fca9b00fcb77cf0e09b438c1790
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T200000Z
DTEND:20260922T205500Z
SUMMARY:Install Once\, Exploit Forever: The MCP Plugin Supply Chain Attack Surface
DESCRIPTION:Every time we set up an MCP server\, something felt off. Adding one is as simple as adding a JSON entry that points to a third-party process. Restart your client\, and that server's outputs now flow directly into your agent's context — treated with the same trust as your own instructions. It can access whatever you've granted it — files\, API tokens\, tool outputs — with no verification that it's still the same code you originally approved. There are no signature checks\, no permission reviews\, and no clear way to know if what you installed today is still what's running next week.That gap in trust is what this talk is about.MCP servers are starting to show up everywhere as a way to extend AI agents with external tools. Unlike traditional plugins\, they run inside the agent's workflow\, which means they can see task context and credentials passed between tools.Through live demos\, we'll show two attack paths:- A rogue server that looks legitimate from day one- A remotely hosted server that operates correctly until a server-side update changes its behavior with no client notification and no re-authorization promptIn both cases\, nothing is "exploited" in the traditional sense. These attacks work because of the system's design. We demonstrate that the same malicious server is running in both Anthropic Claude Desktop and Visual Studio Code\, showing this isn't tied to a single client but to a broader architectural issue.You'll see how an attacker could exfiltrate sensitive data\, access credentials\, and observe or even influence multi-step agent workflows.Then we'll walk through what you can actually do about it. That includes server allowlisting\, version pinning\, monitoring outbound connections from agent processes\, auditing permissions\, and treating MCP updates the same way you treat third-party code changes.We'll close with a few things the ecosystem still needs to fix\, such as signed updates\, better visibility into permission changes\, and stronger guarantees for plugin integrity.
CATEGORIES:IMPLEMENTATION
LOCATION:
SEQUENCE:0
UID:80a1b5879781b08eb725ee2d19d5ed01
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/80a1b5879781b08eb725ee2d19d5ed01
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T210000Z
DTEND:20260922T215500Z
SUMMARY:Securing Distributed Systems with Privacy-Aware Governance and ML Controls
DESCRIPTION:Distributed systems increasingly face security and privacy risks as data flows across services without sufficient visibility or enforcement. Regulatory actions have highlighted how combining user data without informed consent can lead to exploitative outcomes\, reinforcing the need for real-time\, security-driven controls rather than retrospective audits. This session presents a privacy-aware infrastructure that embeds compliance and security enforcement directly into distributed architectures.\n\nThe framework uses Policy Zones and metadata-driven controls to segment data flows and enforce purpose limitations across services. Automated classification pipelines assign sensitivity attributes at ingestion\, enabling consistent enforcement as data moves through systems. Template-based policies and simplified APIs support scalable implementation while maintaining strong governance controls.\n\nMachine learning techniques enhance detection capabilities by classifying sensitive data\, identifying cross-service violations\, and detecting anomalous patterns in data movement. Methods such as entity recognition\, clustering\, and temporal anomaly detection enable continuous monitoring of complex\, distributed environments.\n\nA provenance-aware auditing layer provides traceability of data lineage and processing history\, supporting verification and forensic analysis. These controls help prevent unauthorized data combinations and ensure that usage aligns with declared purposes across system boundaries.\n\nThe session also examines enforcement across microservices and multi-jurisdiction deployments\, highlighting patterns that strengthen system security while maintaining compliance. This approach provides a practical blueprint for building secure\, privacy-aware distributed systems aligned with modern application security principles.\n\n
CATEGORIES:IMPLEMENTATION
LOCATION:
SEQUENCE:0
UID:0ae2e101ead0472815ff3d53608dbc18
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/0ae2e101ead0472815ff3d53608dbc18
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T210000Z
DTEND:20260922T215500Z
SUMMARY:Rethinking how we evaluate security agents for real-world use
DESCRIPTION:Security agents are gaining momentum across industry\, but the way we evaluate them remains rooted in narrow\, outcome-only benchmarks. These evaluations tell us whether an agent produced a correct answer\, but not “how” it arrived there or whether that behavior will remain stable once deployed.\nIn practice\, enterprise security is not a sequence of isolated tasks. It is a connected\, end-to-end workflow that follows a find → confirm exploit → patch → validate loop. Agents that perform well on task-specific benchmarks often fail in these multi-stage settings due to contextual loss and brittle transitions across steps.\nThis talk introduces a practical framework for evaluating security agents by mapping agentic capabilities (planning\, reasoning\, memory\, perception\, tool use) to security functions (reconnaissance\, exploit confirmation\, root-cause analysis\, patching\, validation) across the full lifecycle. We also share insights from our large-scale survey of existing agentic systems\, highlighting which capabilities consistently drive success at each stage. Finally\, we present a lightweight\, unified end-to-end scoring perspective that teams can use to assess an agent’s readiness for real operational environments.
CATEGORIES:TESTING
LOCATION:
SEQUENCE:0
UID:36a71594969b31b6be5c11fc2b1af657
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/36a71594969b31b6be5c11fc2b1af657
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T220000Z
DTEND:20260922T225500Z
SUMMARY:I Don't Trust AI Agents (And Neither Should You): Building Production-Ready Architectures
DESCRIPTION:Your AI agent works great in the demo. Then you deploy it and it hallucinates a refund policy that costs you $10K\, or exposes customer data\, or just loops endlessly burning tokens.This session explores how to build AI agents you can trust in production using Amazon Bedrock AgentCore and the Strands Agents SDK.We’ll walk through a layered approach to agent safety that spans guardrails at multiple levels\, including input validation\, output filtering\, and action approval\, along with observability patterns that make agent behavior transparent and auditable.You’ll also see how multi-agent architectures can be designed so agents steer and check one another\, and how security policies combined with deliberate prompt design reduce risk across the system.We'll walk through a reference architecture that combines these layers\, and you'll learn how each layer can catch failures.You should have basic familiarity with LLMs and AI agents. You'll leave with architectures pattern you can adapt and a clearer picture of what can go wrong and how to address common issues with AI agent trust and reliability.
CATEGORIES:IMPLEMENTATION
LOCATION:
SEQUENCE:0
UID:6a7441b410cb4a9271df2719c5f8d358
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/6a7441b410cb4a9271df2719c5f8d358
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T220000Z
DTEND:20260922T225500Z
SUMMARY:AMMF: Attention-Driven Multi-Feature Fusion for Scalable Cross-Architecture Binary Vulnerability Det
DESCRIPTION:Detecting vulnerabilities in compiled binaries remains a major challenge for security teams\, especially when software is reused across different architectures\, compilers\, and optimization settings. These variations significantly alter binary representations\, making traditional detection techniques brittle and difficult to scale.This talk introduces AMMF (Attention-Driven Multi-Feature Fusion)\, a novel approach for cross-architecture binary vulnerability detection that combines semantic understanding with structural analysis. AMMF leverages assembly-level embeddings to capture instruction semantics\, while integrating control-flow and function-level attributes to model program behavior. An attention-enhanced neural architecture unifies these diverse features into a robust representation that generalizes across heterogeneous environments.To improve both scalability and precision\, AMMF employs a two-stage detection pipeline. First\, a deep similarity model efficiently identifies high-risk candidate functions from large binary corpora. Then\, a graph-matching refinement step analyzes control-flow structures to confirm vulnerabilities and reduce false positives.In experimental evaluations\, AMMF achieves 95.79% accuracy and 97.06% recall\, outperforming current state-of-the-art methods across cross-architecture\, cross-compiler\, and cross-optimization scenarios.This session will demonstrate how combining machine learning\, attention mechanisms\, and program analysis can significantly improve vulnerability detection in real-world software supply chains—where code reuse and platform diversity are the norm.
CATEGORIES:TESTING
LOCATION:
SEQUENCE:0
UID:e063fb01bd44ec212815a0e708b00274
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/e063fb01bd44ec212815a0e708b00274
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T230000Z
DTEND:20260922T235500Z
SUMMARY:The Sentinel-Aura Architecture: Orchestrating Agentic AI for Autonomous Endpoint Remediation
DESCRIPTION:As infrastructure grows beyond human scale\, traditional manual patching is no longer a viable security posture. This session introduces a research-driven framework for Autonomous Infrastructure Healing.Instead of treating security as a static checklist\, we explore a model where the system functions as a self-correcting organism. By wrapping Microsoft Intune and Microsoft Entra with a custom Agentic AI orchestration layer\, we can transform Windows 11 endpoints into self-healing assets. I will discuss the methodology of the "Red-to-Green" transition—using Automation and Agentic AI to interpret security telemetry and execute sub-60-second remediations without human intervention. This is a visionary look at how Microsoft Security Copilot and autonomous agents will redefine the future of the regulated workplace.
CATEGORIES:PLANNING AND DESIGN
LOCATION:
SEQUENCE:0
UID:0266fb750571001ca4320ed9736c9149
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/0266fb750571001ca4320ed9736c9149
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T230000Z
DTEND:20260922T235500Z
SUMMARY:Self-Healing Security Test Automation for OWASP AppSec: Adaptive Defense Against Evolving Threats
DESCRIPTION:Self-healing security test automation introduces a resilient approach to application security testing\, addressing one of the most critical challenges in modern AppSec programs: maintaining effective test coverage in rapidly evolving systems. As applications undergo continuous updates\, traditional security test scripts frequently fail due to UI\, API\, or infrastructure changes\, leading to gaps in vulnerability detection and increased risk exposure.This session explores how self-healing mechanisms—powered by machine learning\, intelligent element recognition\, and adaptive execution strategies—can be applied to security testing within OWASP-aligned frameworks. By automatically adjusting to application changes\, these systems ensure consistent validation of security controls\, including authentication flows\, input validation\, and access control mechanisms.The proposed framework demonstrates high accuracy in identifying modified application elements and recovering failed test cases without human intervention. This capability significantly reduces maintenance overhead while improving the reliability of detecting vulnerabilities such as injection flaws\, broken authentication\, and misconfigurations.Aligned with OWASP tracks including Testing\, Implementation\, and Process & Culture\, this approach also supports the development of sustainable security practices by reducing operational friction for security and DevOps teams. Real-world implementations highlight measurable improvements in test stability\, reduced false positives\, and faster feedback loops.Ultimately\, self-healing security automation enables organizations to maintain continuous security assurance\, strengthen AppSec programs\, and adapt effectively to the evolving threat landscape.
CATEGORIES:TESTING
LOCATION:
SEQUENCE:0
UID:d6f46df2d26727aff47393ec0f6111c7
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/d6f46df2d26727aff47393ec0f6111c7
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260726T233437Z
DTSTART:20260922T235500Z
DTEND:20260923T001000Z
SUMMARY:Closing Remarks
DESCRIPTION:\n
CATEGORIES:
LOCATION:
SEQUENCE:0
UID:8fd5bd24955b67dbce7ebeae452c6028
URL:http://owasp25thanniversaryvirtualconfe.sched.com/event/8fd5bd24955b67dbce7ebeae452c6028
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