{"product_id":"ai-secureops-attacking-defending-ai-applications-agents-abhinav-singh-dclv2026","title":"AI SecureOps: Attacking \u0026 Defending AI Applications \u0026 Agents - Abhinav Singh - DCTLV2026","description":"\u003cp dir=\"ltr\"\u003e\u003cmeta charset=\"utf-8\"\u003e\u003cstrong\u003eName of Training\u003c\/strong\u003e\u003cspan\u003e\u003cstrong\u003e:\u003c\/strong\u003e AI SecureOps: Attacking \u0026amp; Defending AI Applications \u0026amp; Agents\u003cbr\u003e\u003c\/span\u003e\u003cstrong\u003eTrainer(s)\u003c\/strong\u003e\u003cspan\u003e\u003cstrong\u003e:\u003c\/strong\u003e Abhinav Singh\u003cbr\u003e\u003c\/span\u003e\u003cspan\u003e\u003cmeta charset=\"utf-8\"\u003e \u003cstrong\u003eDates\u003c\/strong\u003e\u003cstrong\u003e:\u003c\/strong\u003e \u003cmeta charset=\"utf-8\"\u003eAugust 10-11, 2026\u003cbr\u003e\u003cstrong\u003eTime:\u003c\/strong\u003e 8:00 am to 5:00 pm \u003cbr\u003e\u003cstrong\u003eVenue\u003c\/strong\u003e\u003cstrong\u003e:\u003c\/strong\u003e \u003cmeta charset=\"utf-8\"\u003eLas Vegas Convention Center\u003cbr\u003e\u003c\/span\u003e\u003cstrong\u003eCost\u003c\/strong\u003e\u003cspan\u003e\u003cstrong\u003e: \u003c\/strong\u003e$2,000\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cstrong\u003eShort Summary:\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eStep into the front lines of securing enterprise AI with an immersive, CTF-style training built around realistic attack-and-defense scenarios for AI applications, agents, and MCP-connected systems. Through hands-on labs, participants will explore how prompt injection, agent abuse, poisoned context, unsafe tool use, and authorization failures can lead to backend compromise, data exposure, and infrastructure impact. The course focuses on the enterprise realities of securing AI apps \u0026amp; agentic systems, covering red and blue teaming, guardrails, monitoring, incident response, and Responsible AI. Designed for security practitioners, builders, and defenders, this training helps attendees understand how modern AI systems fail, how those failures chain into larger enterprise risks, and how to implement practical controls to secure AI deployments at scale.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003eTop 3 Takeaways\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eLearn how to identify, exploit, and defend against real-world attacks on AI applications, agents, and tool-connected systems, including prompt injection, jailbreaks, agent abuse, and chained compromise paths.\u003c\/li\u003e\n\u003cli\u003eBuild practical defensive capabilities for enterprise AI, including guardrails, security scanners, monitoring, and response patterns for public, private, and MCP-enabled AI services.\u003c\/li\u003e\n\u003cli\u003eGain hands-on experience using modern AI techniques for security testing, validation, and red\/blue teaming, including judge-LLM workflows, attack automation, and securing agentic AI supply chains.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp dir=\"ltr\"\u003e\u003cstrong\u003eCourse Description: \u003c\/strong\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eCan prompt injections lead to complete infrastructure takeovers? Could AI agents, MCP-connected tools, or poisoned external context be abused to compromise backend services? Can data poisoning in AI copilots impact a company’s stock? Can jailbreaks create false crisis alerts in security systems? This immersive, CTF-styled training in GenAI, LLM, agent, and MCP security dives into these pressing questions. Engage in realistic attack-and-defense scenarios focused on real-world threats, from prompt injection and remote code execution to backend compromise, tool abuse, unsafe agent orchestration, and MCP-specific trust and authorization failures. Tackle hands-on challenges with live AI applications to understand vulnerabilities and build robust defenses. Learn how to create a comprehensive security pipeline, master AI red and blue team strategies, secure tool-connected and agentic systems, build resilient guardrails for LLMs, and handle incident response for AI-based threats. You will also explore governance, Responsible AI, and enterprise security patterns for modern AI ecosystems.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eBy 2027, Gartner, Inc. predicts that over 80% of enterprises will engage with AI applications, up from less than 5% in 2023. This rapid adoption presents a new challenge for security professionals. This training provides essential AI and LLM security skills through an immersive CTF-styled framework, bringing you from an intermediate to an advanced level. Delve into sophisticated techniques for mitigating AI threats and engineer robust defense mechanisms to address the complex security challenges posed by AI's rapid expansion. You will be provided with access to a live playground with custom-built AI applications replicating real-world attack scenarios covering use-cases defined under the OWASP LLM top 10 framework and mapped with stages defined in MITRE ATLAS. This dense training will navigate you through areas like the red and blue team strategies, create robust LLM defenses, incident response in LLM attacks, implement a Responsible AI (RAI) program, and enforce ethical AI standards across enterprise services, with the focus on improving the entire AI supply chain.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eThis training will also cover the completely new segment of Responsible AI (RAI), ethics, and trustworthiness in AI services. Unlike traditional cybersecurity verticals, these unique challenges such as bias detection, managing risky behaviors, and implementing mechanisms for tracking information are going to be the key challenges for enterprise security teams.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eBy the end of this training, you will be able to:\u003c\/span\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli dir=\"ltr\"\u003e\n\u003cspan\u003eExploit vulnerabilities in AI applications to achieve code and command execution, uncovering scenarios such as instruction injection, agent control bypass, remote code execution for infrastructure takeover, and chaining multiple agents for goal hijacking.\u003cbr\u003e\u003c\/span\u003e\u003cspan\u003e\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003eConduct AI red-teaming using adversary simulation, OWASP LLM Top 10, and MITRE ATLAS frameworks, while applying AI security and ethical principles in real-world scenarios.\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003eExecute and defend against adversarial attacks, including prompt injection, data poisoning, jailbreaks, agentic attacks, and insecure tool-connected workflows.\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003ePerform advanced AI red and blue teaming through multi-agent auto-prompting attacks, implementing a 3-way autonomous system consisting of attack, defend, and judge models.\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003eBuild and deploy enterprise-grade LLM defenses, including custom guardrails for input\/output protection, security benchmarking, penetration testing of LLM agents, and defensive controls for MCP-enabled integrations.\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003eUnderstand MCP \u0026amp; agent fundamentals and assess how they expand the attack surface of modern AI systems.\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003eEstablish a comprehensive LLM SecOps process to secure the supply chain from adversarial attacks. Create a robust threat model for enterprise applications, including AI systems connected to external tools and data sources through MCP-like architectures.\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003eImplement an incident response and risk management plan for enterprises developing or using GenAI services.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cdiv dir=\"ltr\"\u003e\n\u003cdiv class=\"gmail_quote\"\u003e\n\u003cdiv dir=\"ltr\"\u003e\u003cspan id=\"m_4537920884060312m_4557477349097280137m_-2991987330191836870gmail-docs-internal-guid-81f1794d-7fff-aac0-e0e1-98237d64c6cd\"\u003e\u003c\/span\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cp\u003e\u003cspan\u003e\u003cmeta charset=\"utf-8\"\u003e \u003cstrong\u003eCourse Outline: \u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e### Introduction \u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eIntroduction to LLM and AI\u003c\/li\u003e\n\u003cli\u003eTerminologies and architecture\u003c\/li\u003e\n\u003cli\u003eTransformers, Attention \u0026amp; their security implications (hallucinations, jailbreaks, etc)\u003c\/li\u003e\n\u003cli\u003eAgents, multi-agents and multi-modal models\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eIntroduction to tool-connected AI systems and MCP as an emerging standard for connecting agents to external tools, data, and workflows\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e### Elements of AI Security (1 lab)\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eUnderstanding AI vulnerabilities with case studies on AI security breaches\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eOWASP LLM Top 10 and MITRE mapping of attacks on AI supply chain  \u003c\/li\u003e\n\u003cli\u003eThreat modeling of AI Applications, tool-connection and MCP-enabled architectures, including trust boundaries across hosts, clients, servers, tools, resources, and external systems  \u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e### Adversarial LLM Attacks and Defenses (6 labs)\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e(What, Why \u0026amp; how’s)Direct and indirect prompt injection attacks and their subtypes \u003c\/li\u003e\n\u003cli\u003eAdvanced prompt injections through obfuscation and cross-model injections\u003c\/li\u003e\n\u003cli\u003eBreaking system prompts and their trust criteria\u003c\/li\u003e\n\u003cli\u003eIndirect prompt injections through external input sources\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e### Responsible AI \u0026amp; Jailbreaking (6 labs)\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eJailbreaking public LLMs covering adversarial AI, offensive security, and CBRN use-cases\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003eResponsible use and governance implications of increasingly autonomous, tool-connected AI systems\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003eModel alignment, system prompt optimization, and defense\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e### Building Enterprise-grade LLM Defenses (2 labs)\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eDeploying LLM security scanner, adding custom rules, prompt block-lists, and guardrails.\u003c\/li\u003e\n\u003cli\u003eWriting custom detection logic, trustworthiness checks, and filters.\u003c\/li\u003e\n\u003cli\u003eBuilding security log monitoring and alerting for models using open-source tools.\u003c\/li\u003e\n\u003cli\u003eLLM security benchmarking and continuous reporting.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e### Red \u0026amp; Blue Teaming of Enterprise AI applications (4 labs)\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eBusiness control flow testing for risky responses \u0026amp; misaligned behavior of applications\u003c\/li\u003e\n\u003cli\u003eUsing Colab notebooks for automation of API calls and reporting\u003c\/li\u003e\n\u003cli\u003eVector database and model-weight tracing for root-cause investigation\u003c\/li\u003e\n\u003cli\u003eRainbow teaming through a 3-way LLM implementation: target, attacker, and judge with self-improving attack prompts\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e### MCP Security \u0026amp; Defensive Architecture (1 lab)\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eMCP fundamentals \u0026amp; security for agentic systems: protocol basics, trust-boundary changes, key risks like malicious servers and over-broad permissions, plus a browser-based exploit-and-defend lab\u003c\/li\u003e\n\u003cli\u003eDefense patterns for MCP-enabled systems with protection architectures\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e### Attacking \u0026amp; Defending Agentic Systems (5 labs)\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eThreat modeling of agentic and multi-agent systems, including planning loops, memory, tool invocation, delegation, trust boundaries, and escalation paths\u003c\/li\u003e\n\u003cli\u003eAttacking LLM agents for task manipulation, risky behavior and PII disclosure in RAG\u003c\/li\u003e\n\u003cli\u003eInjection attacks on AI agents for code and command execution\u003c\/li\u003e\n\u003cli\u003eCompromising backend infrastructure by abusing over-permissioning and tool usage in agentic systems\u003c\/li\u003e\n\u003cli\u003eMulti-agent attacks causing privilege too calls, goal manipulation \u0026amp; chained escalations\u003c\/li\u003e\n\u003cli\u003eDefense patterns for agentic systems, including observability, approval gates, scoped permissions, secure delegation, and runtime tracing for high-risk actions.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e### Building AI SecOps Process\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eSummarizing the learnings into a SecOps workflow\u003c\/li\u003e\n\u003cli\u003eMonitoring trustworthiness, safety and security of enterprise AI applications\u003c\/li\u003e\n\u003cli\u003eImplementing NIST AI Risk Management Framework (RMF) for security monitoring\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp dir=\"ltr\"\u003e\u003cstrong\u003eDifficulty Level:\u003c\/strong\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003eIntermediate - The student has education, some experience in the field and familiarity with the topic being presented. The student has foundational knowledge that the course will leverage to provide practical skills on the topic.\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cstrong\u003eSuggested Prerequisites:\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cb\u003e\u003c\/b\u003eComplete the simple pre-training instructions: create a paid OpenAI API key, set up a Google Colab notebook, and read the Introduction document. No local setup is needed. All the training materials and lab access will be provided during the training.\u003cbr\u003e\u003c\/p\u003e\n\u003cp\u003eWho Should Take This Course\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eSecurity professionals who need to understand how modern AI systems fail and how to defend them\u003c\/li\u003e\n\u003cli\u003eRed and blue teamers looking to add AI applications, agents, and tool-connected systems to their offensive and defensive workflows\u003c\/li\u003e\n\u003cli\u003eAI\/LLM developers and engineers who want to build more secure applications, agents, and integrations\u003c\/li\u003e\n\u003cli\u003eSecurity architects, detection engineers, and defenders responsible for securing enterprise AI deployments\u003c\/li\u003e\n\u003cli\u003eAI safety, governance, and risk professionals who need a practical understanding of how technical failures map to real enterprise risk\u003c\/li\u003e\n\u003cli\u003eProduct leaders, founders, and technical decision-makers who want to better understand the attack surface of AI-enabled products and agentic systems\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp dir=\"ltr\"\u003e\u003cstrong\u003eWhat Students Should Bring: \u003c\/strong\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cb\u003e\u003c\/b\u003e\u003cspan\u003e\u003c\/span\u003eA laptop with browser access is ideal, preferably a personal laptop without network restricting tools.\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003eComplete the pre-training setup prior to the class which includes setting up:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli dir=\"ltr\"\u003e\u003cspan\u003eAPI key for OpenAI.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003eGoogle Colab account.\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003eComplete the pre-training setup before the first day.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp dir=\"ltr\"\u003e\u003cstrong\u003eWhat the Trainer Will Provide:\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli dir=\"ltr\"\u003e\u003cspan\u003eOne year access to a live interactive playground with various exercises to practice different attack and defense scenarios for GenAI and LLM applications.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003e\u003cspan\u003e\"AI SecureOps\" Metal coin for CTF players.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003e\u003cspan\u003eComplete course guide containing 200+ pages in PDF format. It will contain step-by-step guidelines for all exercises and labs, and a detailed explanation of concepts discussed during the training.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003e\u003cspan\u003ePDF versions of the slides that will be used during the training.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003e\u003cspan\u003eAccess to the Discord server for continued engagement, support, and development in the field of AI Security \u0026amp; Safety.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli dir=\"ltr\"\u003e\u003cspan\u003eAccess to HuggingFace models, datasets, and transformers.\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp dir=\"ltr\"\u003e\u003cstrong\u003eTrainer(s) Bio:\u003c\/strong\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cmeta charset=\"utf-8\"\u003e\u003cspan\u003e\u003cstrong\u003eAbhinav Singh\u003c\/strong\u003e is an esteemed cybersecurity leader \u0026amp; researcher with over 15 years of experience across technology leaders and financial institutions, as well as an independent trainer and consultant. Author of \"Metasploit Penetration Testing Cookbook\" and \"Instant Wireshark Starter,\" his contributions span patents, open-source tools, and numerous publications. Recognized in security portals and digital platforms, Abhinav is a sought-after speaker \u0026amp; trainer at international conferences like Black Hat, RSA, DEFCON, BruCon, and many more, where he shares his deep industry insights and innovative approaches in cybersecurity. He also leads multiple AI security groups at CSA, responsible for coming up with cutting-edge white papers and industry reports on the safety and security of AI.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eReview a few examples of Abhinav's previous courses at the links below:\u003c\/span\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cspan\u003e \u003c\/span\u003e\u003cspan\u003e2026:\u003ca href=\"https:\/\/sg.shop.defcon.org\/collections\/singapore-2026\/products\/ai-secureops-defending-ai-applications-and-services-abhinav-singh-dcsg2026\" target=\"_blank\"\u003e DEF CON Singapore,\u003c\/a\u003e\u003ca href=\"https:\/\/training.defcon.org\/collections\/def-con-training-las-vegas-2026\/products\/ai-secureops-attacking-defending-ai-applications-agents-abhinav-singh-dclv2026\" target=\"_blank\"\u003e \u003c\/a\u003e\u003ca href=\"https:\/\/insomnihack.ch\/workshops\/ai-secureops-attacking-defending-ai-applications-agents\/\" target=\"_blank\"\u003eInsomni’hack\u003c\/a\u003e,\u003ca href=\"https:\/\/hackmiami.com\/training-ai-secureops-attacking-defending-genai-applications-and-services.html\" target=\"_blank\"\u003e HackMiami\u003c\/a\u003e,\u003ca href=\"https:\/\/www.x33fcon.com\/#!t\/AbhinavSingh.md\" target=\"_blank\"\u003e x33fcon\u003c\/a\u003e,\u003ca href=\"https:\/\/owasp.glueup.com\/event\/owasp-global-appsec-eu-2026-vienna-austria-162243\/training.html\" target=\"_blank\"\u003e OWASP Global AppSec EU\u003c\/a\u003e\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli role=\"presentation\"\u003e\n\u003cspan\u003e2025:\u003ca href=\"https:\/\/insomnihack.ch\/workshops\/ai-secureops-attacking-defending-genai-applications-and-services\/\" target=\"_blank\"\u003e Insomni’hack\u003c\/a\u003e, BruCon, Hack Miami, \u003ca href=\"https:\/\/www.rsaconference.com\/experts\/abhinav-singh\" target=\"_blank\"\u003eRSA Conference\u003c\/a\u003e,\u003ca href=\"https:\/\/training.defcon.org\/collections\/def-con-training-las-vegas-2025\/products\/abhinav-singh-ai-attacks-defense-las-vegas-2025\" target=\"_blank\"\u003e DEF CON Vegas\u003c\/a\u003e, Nsec\u003c\/span\u003e\u003cu\u003e\u003cspan\u003e, Lacson, \u003ca href=\"https:\/\/events.humanitix.com\/owaspnz2025-training\"\u003eOWASP Auckland\u003c\/a\u003e\u003c\/span\u003e\u003c\/u\u003e\u003cspan\u003e\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli role=\"presentation\"\u003e\u003cspan\u003e2024:\u003ca href=\"https:\/\/blackhatmea.com\/trainings-list\/2024\/ai-secureops-genai-and-llm-security-enterprises\" target=\"_blank\"\u003e Black Hat MEA\u003c\/a\u003e,\u003ca href=\"https:\/\/www.rsaconference.com\/Library\/presentation\/USA\/2024\/Blueprint%20for%20Data%20Defense%20in%20the%20Public%20Cloud%20Strategies%20and%20Playbooks\" target=\"_blank\"\u003e RSA San Francisco Workshop\u003c\/a\u003e, Hack Miami, Florida,\u003ca href=\"https:\/\/appsec.org.nz\/conference-2024\/training-ai_secure_ops\" target=\"_blank\"\u003e OWASP New Zealand\u003c\/a\u003e, LASCON 2024,\u003ca href=\"https:\/\/deepsec.net\/archive\/2024.deepsec.net\/speaker.html#WSLOT693\" target=\"_blank\"\u003e DeepSec Austria\u003c\/a\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli role=\"presentation\"\u003e\u003cspan\u003e2023:\u003ca href=\"https:\/\/blackhatmea.com\/trainings-list\/2023\/cloud-security-masterclass-defenders-guide-securing-aws-azure-infrastructure\" target=\"_blank\"\u003e Black Hat\u003c\/a\u003e, DEF CON Las Vegas, OWASP AppSec Days New Zealand,\u003ca href=\"https:\/\/www.rsaconference.com\/Library\/presentation\/USA\/2023\/Defender%20Guide%20to%20Securing%20Data%20in%20Public%20Cloud%20Infrastructures\" target=\"_blank\"\u003e RSA Conference\u003c\/a\u003e, Insomni’hack Geneva,\u003ca href=\"https:\/\/www.infosecworldusa.com\/isw23\/workshops\/\" target=\"_blank\"\u003e InfoSec World\u003c\/a\u003e, BruCon (virtual), BruCon 2023, OWASP LASCON\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp dir=\"ltr\"\u003e\u003cstrong\u003eProficiency Exam Option:\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003eThis course has the option for a proficiency certificate add-on. To earn the proficiency certificate, students will have to score at least 1400 out of 2200 on the course capture the flag (CTF). Only students who purchase the proficiency certificate will have their work evaluated by the instructor to certify mastery of the course material.\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003ePlease reach out to training@defcon.org for any questions related to the proficiency exam and certificate option.\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cstrong\u003eRegistration Terms and Conditions: \u003c\/strong\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eTrainings are refundable before July 11, 2026, minus a non-refundable processing fee of $250.\u003c\/span\u003e\u003cspan\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eBetween July 11, 2026 and August 5, 2026 partial refunds will be granted, equal to 50% of the course fee minus a processing fee of $250.\u003c\/span\u003e\u003cspan\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eAll trainings are non-refundable after August 5, 2026.\u003c\/span\u003e\u003cspan\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eTraining tickets may be transferred to another student. Please email us at training@defcon.org for specifics.\u003c\/span\u003e\u003cspan\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eIf a training does not reach the minimum registration requirement, it may be cancelled. In the event the training you choose is cancelled, you will be provided the option of receiving a full refund or transferring to another training (subject to availability).\u003c\/span\u003e\u003cspan\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eFailure to attend the training without prior written notification will be considered a no-show. No refund will be given.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eDEF CON Training may share student contact information, including names and emails, with the course instructor(s) to facilitate sharing of pre-work and course instructions. Instructors are required to safeguard this information and provide appropriate protection so that it is kept private. Instructors may not use student information outside the delivery of this course without the permission of the student.\u003c\/span\u003e\u003cspan\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eBy purchasing this ticket you agree to abide by the \u003c\/span\u003e\u003ca href=\"https:\/\/defcon.org\/html\/links\/dc-code-of-conduct.html\"\u003e\u003cspan\u003eDEF CON Training Code of Conduct\u003c\/span\u003e\u003c\/a\u003e\u003cspan\u003e and the registration terms and conditions listed above.\u003c\/span\u003e\u003cspan\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eSeveral breaks will be included throughout the day. Please note that food is not included.\u003c\/span\u003e\u003cspan\u003e\u003cb\u003e\u003c\/b\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp dir=\"ltr\"\u003e\u003cspan\u003eAll courses come with a certificate of completion, contingent upon attendance at all course sessions. Some courses offer an option to upgrade to a certificate of proficiency, which requires an additional purchase and sufficient performance on an end-of-course evaluation.\u003c\/span\u003e\u003c\/p\u003e","brand":"Las Vegas 2026","offers":[{"title":"Course only - Aug 10-11","offer_id":47664227647706,"sku":null,"price":2000.0,"currency_code":"USD","in_stock":true},{"title":"Course + Proficiency Exam - Aug 10-11","offer_id":47664227680474,"sku":null,"price":2300.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0629\/2088\/4442\/files\/Abhinav_image_2.png?v=1749137036","url":"https:\/\/training.defcon.org\/products\/ai-secureops-attacking-defending-ai-applications-agents-abhinav-singh-dclv2026","provider":"defcontrainings","version":"1.0","type":"link"}