Name: How Generative AI is Changing the SDLC
Start: 2025-03-26T19:38:00Z
End: 2025-03-26T19:38:51.000Z
Location: BrightTALK
Rating: 5

Black Duck is now defining the next frontier of application security. With the avalanche of AI-generated code plus expanding regulatory pressure, you need solutions that can scale, adapt, and keep pace with the demands of your business.

Black Duck meets the demands of modern software development with True Scale Application Security. In the cloud or on-prem, 100,000 lines of code or 100 million. For safety-critical systems with stringent compliance requirements or modern web apps deploying 100 times per day. Our flexible, scalable, high-precision solutions enable you to code with confidence.

AI coding assistants and open source AI models are revolutionizing productivity and innovation. But these new resources introduce a systemic challenge that impacts the entire pipeline. How do we embrace innovation without introducing invisible risk at astonishing scale? Does AI-enabled development threaten the value of the assets that drive your business? This session shows the results of a new study on this shared reality. It shows a way to get security and compliance done that doesn’t stop development teams.
We’ll address the main worries of technology executives and effective approaches to handling risks caused by AI. It's time to align development and security teams. You may ask how? Through integrated tools that make secure coding a natural part of daily workflows.
What’s in it for you?
• Gain exclusive insights from new research on AI adoption and its security implications
• Learn practical strategies to manage AI-generated risks in development pipelines
• Discover how to align Security and Development for frictionless, secure innovation

Secure or Sorry? What AppSec Leaders Must Know About AI Adoption

Open source software powers modern development—but it also introduces risks. From direct and transitive dependencies to container images, these risks can enter your applications in many ways, often without full visibility. 

Join this webinar to learn

• The common entry points for open source in your applications
• The risks of unmanaged open source, including vulnerabilities and license issues
• Best practices for securing and governing open source usage
• Tools and strategies for maintaining compliance and visibility

Whether you're a developer, security professional, or compliance lead, this session will help you build safer, more resilient software.

The Open Source Wildcard: Don't Roll the Dice on Risk

The tech M&A landscape is rapidly evolving with the pervasive integration of AI into target company applications. As machine learning, Generative AI, and other intelligent technologies become central to innovation, traditional software due diligence is no longer enough. This session addresses the critical new dimensions of risk and opportunity that AI introduces to acquisitions.

Join us for a practical framework designed to equip M&A principals and legal counsel with the tools to thoroughly assess AI-driven targets. We’ll dive into the essential areas you must explore, from evaluating model provenance and performance to navigating complex data governance and ethical considerations.

Key takeaways will include how-to effectively assess:

• AI Footprint: Understanding the strategic implementation and problem-solving capabilities of AI.
• Security Risks: Comprehensive data protection, access control, and penetration testing for AI systems.
• Legal & IP Risks: Clarifying model and training data ownership, alongside API terms.
• Quality & Reliability Risks: Ensuring performance, effective retraining, and model explainability.
• Regulatory & Compliance Risks: Navigating emerging regulations like the EU AI Act and critical data privacy concerns.

M&A's New Frontier: Assessing AI Software Risk in Your Next Deal

AI-enabled development tools and coding assistants are pushing CI pipelines, fueling innovation, and iterating business-critical software faster than ever before. Security teams are now forced to catch up. The burden to remedy AI tools often weak coding practices and to overcome their ignorance to third-party vulnerabilities and licenses is further complicated by developers' implicit trust in their output and an intrinsic incompatibility between AppSec and Dev teams' primary role: to ship functional code quickly.  

Enterprises can no longer treat development and AppSec workflows as separate entities. To unify them, however, requires fast, reliable, automated ways to evaluate every line of code that flows through the pipeline and to provide immediate access to fix methods. This only manifests with integrated security gates across CI/CD pipelines, aligned to risk-tolerance standards and optimized to maintain the speed benefits of AI-enabled development.  

Join us as we analyze DevSecOps in the age of AI and structure a viable strategy that accounts for:  

- Software security and license compliance issues introduced, at speed, by AI coding assistants  
- The dissonance between the adoption of AI-enabled dev tools and AppSec's preparedness to secure their output  
- Business priorities that span development, security, legal, and executive requirements

AI's IOU: Maximizing value from AI without paying for it later

With software development accelerating in the AI era, there are even more sources of vulnerabilities to track. Managing this is an enormously complex task, as organizations are already struggling to unify data across disparate tools for testing, SCM, and reporting. As more organizations adopt AI-assisted development, existing issues with fragmented risk visibility will only get bigger. 
 
In this webinar, you will learn about capabilities for achieving a high-fidelity, organizational view of risk posture to better streamline auditing, visualize AppSec gaps, and identify your most vulnerable software. We will talk about necessary capabilities for aggregating key sources of data, standardizing risk scoring, and how you can set up the right technical foundations for success.

Contextualizing Risk in the Age of AI Development

AppSec teams are being stretched to the limit trying to keep up with the pace, volume and complexity of modern application development. Current trends in software development – the transformative role AI, the increasingly complex and vulnerable software supply chain, and the mounting requirement to both scale and focus security issue remediation – help shed light on what measures organizations need to put in place to stay ahead.     

In this session we will outline these trends and provide data and insights from our research into them. We will also outline practical steps you can take now to position yourselves to manage the evolving requirements of Application Security.

The State of AppSec & Beyond

Join two of our cybersecurity experts for a lightning round that cuts through the hype and addresses the immediate challenges of AI in software development. We'll explore the paradigm shift that is reshaping creativity and problem-solving in development, the new frontier of AI-influenced software risk, and discuss ways in which AI coding assistants and open source AI models form the next evolution of the software supply chain crisis.
 
This session charts a course from high-level business concerns directly to the developer experience, examining:
- The business and contractual liabilities that arise when AI-generated code enters your products.
- New, instinct-driven "vibe programming" and the debate over whether this emerging methodology is a sustainable path to innovation or a source of unpredictable risk.
- How AI coding assistance alters hiring strategies and the critical role of code review by security-capable developers in an AI-driven workflow.
- Emerging attack vectors tied to the growing use of open-source AI models.
- Viable paths forward to harness the power of AI, manage its inherent risks, and minimize organizational disruption by establishing resilient and scalable safety nets within your pipeline.

AI-Assisted Disruption: How Change Impacts Dev and Sec as Organizations Pivot to AI

Application security hasn’t gotten any simpler—especially as AI accelerates the way software is built. More code, more complexity, and more fragmented tooling make it harder to answer a basic question: Where are we exposed?  

This session explores how teams can regain clarity at the first step of any risk management program. That means identifying what’s running, what’s been tested, and what needs attention. We’ll look at how automation, speed, and policy can work together to improve visibility without slowing delivery.  

As part of Black Duck’s broader approach to application risk management, we’ll also show how solutions like Black Duck Polaris™ Platform scales with the way modern teams build software.

Identifying Risk in the Age of AI-Assisted Development

Security is the result of implementing the tools, personnel, and insight necessary to make informed decisions to mitigate risks within the software you create and the assets you consume through the software supply chain. While this process can be elaborate, rapid releases and CI/CD methodologies require that AppSec move at the speed of DevOps.

Achieving this is only possible with integrated controls and mechanisms to detect, prioritize, and address security issues at every stage in the SDLC and CI/CD pipelines. But how do you get there?

Join us as we recommend ways to establish security within DevOps without sacrificing efficiency. We’ll discuss:
- Pitfalls that can derail an organization’s AppSec initiative
- Strategies for overcoming obstacles to efficient, effective DevSecOps
- Recommendations for realizing integrated DevSecOps at scale

Integrating AppSec for Efficient DevSecOps

AI technologies are compelling teams to accelerate software development and to explore innovations previously regarded as unattainable. While 67% of organizations use AI coding assistants at least weekly to realize these goals, 57% feel that using AI coding assistants has introduced new security risks or has made it harder to detect issues in their codebase. AppSec teams are scrambling to keep pace.  

Join us for an in-depth exploration of today's DevSecOps landscape based on our yearly Global State of DevSecOps report and findings from independent research institute, SANS. We'll examine the delicate balance between AI-assisted development and modern DevSecOps strategies, focusing on: 
* The impact of AI coding assistants on development pipelines and security workflows 
* How AI-ready organizations maximize AppSec coverage and agility 
* The evolution of traditional application security testing (AST) to AI-enabled AST 
* Prerequisites for a scalable, robust DevSecOps program purpose-built for AI-enabled development

From Code to Security: The DevSecOps Frontier

Securing your software supply chain begins with knowing what’s in your code. With AI-generated code and ubiquitous open source software use, it’s never been more critical to understand what risks your software may contain. In fact, last year alone we found that 81% of codebases contained a high-/critical risk vulnerability.
 
Join this webinar as we explore the findings from the 2025 “Open Source Security and Risk Analysis” report. We’ll cover:
 
• The state of open source software security
• Tips for mitigating risks and keeping vulnerabilities out of your supply chain
• How to protect against security and IP risks from AI coding tools

The 2025 Guide to Open Source Security and Risk

Evaluating a target’s software development process, software architecture, and code quality are becoming a must do in M&A software due diligence. Acquiring poorly designed software or buggy code could derail your post-close plans. 

Join this webinar to learn how to sidestep the tech debt trap. We’ll cover: 

      - The dimensions of software quality 
     - Norms for typical tech M&A targets 
     - How to uncover and mitigate tech debt and post-close “gotchas” 
     - Software due diligence best practices around software quality

Avoid Buggy Deals: Evaluating Software Quality in M&A Due Diligence

There are three regulations that every software development team should be aware of: NIST Secure Software Development Framework (SSDF), the EU Cyber Resilience Act (CRA), and the FDA Cybersecurity Requirements for Medical Devices. What’s your regulation IQ? 

Join this webinar to learn how to navigate these regulations to secure your software supply chain. We’ll cover:  

- Key requirements, commonalities, and differences across the three regulations  
- The importance of an SBOM in dependency tracking and risk management 
- Best practices for complying with these cybersecurity standards  

Register now.

How to Navigate NIST, CRA, and FDA Regulations

Software is essential in everyday products like cars, medical devices, airplanes, and IoT devices. Bugs and security flaws can have serious impacts on safety, the environment, and your reputation. As AI speeds up software development, it's more important than ever to keep your policies, coding standards, and testing up to date.

In this webinar, we’ll discuss:
- Trends that offer innovation but also increase the risk of costly errors
- Updates to functional safety standards that improve software reliability
- How to reduce supply chain risks by getting a full view of your software
- Strengthening software with thorough testing techniques

Register now to learn practical tips for creating secure, reliable functional safety software in 2025 and beyond.

Building Safe and Reliable Software in 2025

Developers have utilized source code management (SCM) tools since the 1980s to track, control, and manage changes across the software development life cycle. But the use of SCM tools is even more widespread now due to the emergence of distributed version control systems such as Git.

For DevSecOps though, it is essential to seamlessly integrate application security testing (AST) into the SCM environment, without compromising on fidelity and scalability. This gives organizations complete control over AST in their CI/CD pipelines.

What you'll learn:
- Onboard new projects easily from GitHub
- Get a centralized view of all your projects
- Orchestrate AST within GitHub actions & workflows
- Monitor all of your GitHub organizations continuously

Getting high fidelity AppSec results within your SCM environment

The Bridge CLI, Coverity CLI, and cov-build offer different ways to run your Coverity Static Analysis.  Join us as we explore how these tools complement each other and help you discover the right one for your CI/CD pipelines, pull request workflows, and ad-hoc scans. This session will include a live demonstration followed by a brief Q&A.  This webinar is targeted for developers, DevOps, or anyone responsible for configuring Coverity Analysis.

The CI/CD Plugin Playbook: How Bridge CLI, Coverity CLI, and cov-build Fit Together

Any tech acquisition target worth its salt is not only using generative AI tools to write code, but also incorporating AI technology into its products. As AI transforms these companies’ applications, and how they develop them, potential investors and acquirers face a new set of risks and questions. 

Join our panel of tech lawyer/AI experts for sage advice on how-to up your software due diligence game. Whether you’re an acquirer, an investor, or expect to be on the sell-side one of these days, learn about:

• The evolving state of risks associated with non-human written code
• Important considerations for integrators of AI models, evaluating the chain of custody and legal hygiene of datasets
• How due diligence is evolving to help investors and acquirers assess and plan for risks
• Market reps and warranties to complement derisking through due diligence 

Register today.

Intelligent Software Due Diligence in the Age of Artificial Intelligence

Join us for an exclusive insider session! We’ll explore the latest trends and challenges in embedded software development. “The State of Embedded Software Quality and Safety” report uncovers key issues in the industry. It highlights the fast rise of AI, potential new risks to software quality, and a shift in what’s driving Software Bill of Materials (SBOMs) requirements.

Here's what you can expect to learn
• How “shadow AI” introduces new risks to governance, security, and IP
• The evolving skillset required for modern embedded developers
• The rising demand for SBOMs as a commercial requirement
• Strategies for balancing speed and quality in software development
• How leading organizations are managing the risks associated with AI and open source software

Get key insights into embedded software development. You'll learn to handle quality, safety, and security in an AI-driven world.

The Rise of AI and New Risks to Embedded Software Development

As you start down the path of using generative artificial intelligence (GAI) in software development to improve efficiency, reduce costs, and increase revenue, you must also be aware of the associated legal issues. How can you leverage AI and minimize the risk it presents?

Join this webinar in which a panel of legal experts and practitioners will answer your questions about the rise of AI in software development, and how you can responsibly leverage this new technology. We’ll cover:

• The benefits and risks for using AI in software development 
• The evolving legal and regulatory landscape 
• Practical advice for using AI today and into the future

Ask the Experts: AI and Software Development

Generative artificial intelligence (GAI) will fundamentally change the way that software is built. Whether they are developing or using AI tools, organizations must understand the opportunities and risks involved, and evolve governance, policies and processes to address those risks.

Join this webinar for a deep dive into the issues that arise when using GAI in software development. We’ll cover:

• Open source data and software licenses and risks with AI
• Licensing and clearance considerations for materials used to train AI models
• Licensing considerations in building, training, and using AI models
• A deep dive on GitHub Copilot, including implications of the class action suit

Generative AI, Training Data, Open Source, and GitHub Copilot, Oh My!

There is no shortage of buzz around generative artificial intelligence (GAI). GAI can be used in software development to generate and augment code which saves times and reduces development cycles. But using AI in software development comes with its own set of risks.

Join this webinar to get an introduction to GAI and how you can minimize risk when using it in your organization. We’ll cover:

• What GAI is and how machines learn
• Legal issues with AI including copyright, web scraping, and more
• Overview of current litigation
• Practical approaches to using GAI while minimizing risk

Best Practices for Using AI in Software Development

The Board and C-Suite are starting to take notice of the opportunities and risks inherent with powerful new generative artificial intelligence (GAI) tools that can quickly create text, code, images, and other media. Product Development and Engineering teams want to use such tools to increase productivity by at least one order of magnitude. In response, the Security, Legal, and Compliance teams typically raise legitimate concerns about the risks involved. What role can the Board and C-Suite play in this situation?
 
Join this live Synopsys webinar to get a jump start on what AI strategy, security, and governance looks like from the Board-level and C-suite. We’ll cover:
 
• Fundamentals of AI, types of models, and data used to inform them
• Expanding existing processes and procedures to address the security risks of GAI
• The top three questions the Board and C-Suite should be asking about GAI
• How to navigate the existing and evolving legal and regulatory landscape

Fundamentals of AI Strategy, Security, and Governance

AI coding assistants, such as Microsoft CoPilot and ChatGPT, will fundamentally change the way teams build software, much like open source software has over the last decade. As with open source, teams seeking the benefits of AI will also need to take precautions to address the security, quality, and intellectual property risks that come with the use of AI-generated code. Is your team ready for AI? 

In this webinar, we'll explore: 

Key risks teams might encounter using coding assistants 

Safeguards needed for confident use of AI-generated code

Managing the risks of AI-generated code

Security remains a leading concern for businesses in this multi-cloud era. With the increasing cloud-native deployment and use of generative AI in application software development, along with proliferation of tools, data and applications distributed across various cloud platforms, ensuring a consistent and robust security posture and at the same time, keep pace with the fast DevOps CI/CD pipeline can be daunting.

The  webinar will explore some of the challenges organizations face when navigating the complex landscape in securing their applications from code to cloud in a fast-paced DevOps CI/CD environment. Attendees will gain insights into how companies overcome these challenges and implement robust and effective application security solutions that align to their DevSecOps initiatives.

Key Takeaways: 

- Recognize the security challenges in this high pace, evolving technology landscape
- The importance of adopting an integrated “Essential Three” app security strategy
- Practical solutions for DevSecOps alignment from a customer perspective

Cloud-native and Generative AI Implications in DevSecOps

AI-powered development has greatly increased the rate at which software evolves. But using artificial intelligence as a proxy for security-aware developers introduces a variety of risks to the business.

Organizations must prepare for the complexities of AI-powered development. This requires establishing consistent and scalable DevSecOps initiatives. The discussion will cover

• Innovation and trends in AI-powered software development
• The inherent risks to application security and business operations of using AI and third-party digital artifacts
• Best practices for establishing application security testing and issue remediation within DevOps workflows that include AI
• Ways to use AI to empower developers and reduce the opportunity of an attack

Preparing DevSecOps for AI Development

Do you know how to navigate the risks of AI-powered development? How can you establish secure DevSecOps initiatives?  
  
This presentation will highlight key aspects of the latest AI-trends and the risk implications for business operations. Get crucial insights from a roundtable discussion with industry leaders from NTT DATA Italy and AppSec Application Security Services. Key takeaways include
 
- Understanding the potential security risks of AI-powered development 
- Strategies for establishing consistent and scalable DevSecOps initiatives in AI-powered development 
- Empowering developers to create secure software

Navigating the Risks of AI-Powered Development for Secure Software

Join this webinar to learn how Black Duck® snippet matching can help identify open source software and the potential license risk that tools like GitHub CoPilot and OpenAI's ChatGPT can introduce into your codebase. With Black Duck you can

- Identity components as one of over 2,700 licenses tracked in our KnowledgeBase
- Understand license requirements in simple terms so development can quickly assess the impact of including a component in their code
- Flag potential license conflicts so teams stay in compliance with policy

Black Duck Snippet Matching and Generative AI Models

As with all things tech, software development has been in a constant state of evolution since its infancy. Generative AI, however, has the potential to disrupt software development as we know it.
There are significant benefits offered by generative AI, but there are risks as well, including security risks. In its brief history, AI has generated buggy code, taken code from open source repositories without licensing considerations, and generated incorrect code.
In this webinar, you will learn
• What AI is and how it is used in the SDLC
• The ways AI is changing how software is being built
• The risks, drawbacks, and concerns of using AI
• How to benefit from AI while managing risks

How Generative AI is Changing the SDLC

AI Strategy, Security, and Governance: The View from the Top

Artificial Intelligence, Real Security: Preparing DevSecOps for AI Development

In the complex world of software development, generative artificial intelligence (GAI) coding tools appear as a beacon of productivity and effectiveness. When handled with precision, they brighten the path to innovation, cutting through the intricacies of coding. However, as with any unchecked flame, such tools must be carefully managed to avoid endangering an organization's valued IP, impacting its bottom line or introducing risk into an M&A transaction.

Join this webinar to get an introduction to GAI coding tools and how you can minimize risk when using these in your organization. We’ll cover:

- Introduction to GAI coding tools (from code completion to code generation)
- Legal, operational, and M&A risks arising from GAI coding tools (e.g., IP ownership, IP infringement, cybersecurity) 
- Establishing a general AI policy with provisions specifically tailored to issues arising in using AI for coding  
- Managing risk arising from GAI coding tools - this includes a mix of technical, operational and administrative safeguards (e.g., usage policies, auditing tools, optimal selection and implementation of tools) 

This presentation is intended for legal and technical teams involved in software development and M&A software due diligence.

Managing Software Risks in the Age of AI-Generated Code

Artificial intelligence (AI) continues to push the frontiers of technology - and it's here to stay. It's influence on cybersecurity reveal a double-edged sword. AI is becoming a formidable enhancer of security measures. But with all new technologies, there is a downside to consider. AI is already used as a core tool in the arsenal of cybercriminals and its capabilities are harnessed to refine every aspect of cybercrime.

The more we see criminals that leverage AI, the more we realize that our defences are not yet equipped to counter Malicious-AI. So where does this leave us?

This session will shed light on how criminals exploit AI to elevate their malicious endeavours. Gain practical insights into the evolving landscape of cybercrime and the pivotal role of AI within it. Let's take a glimpse into a future where AI dominates the cybercrime landscape! Are you ready for the move?

How to Protect Yourself from AI Cybersecurity Nightmares

As you start down the path of using generative artificial intelligence (GAI) in software development to improve efficiency, reduce costs, and increase revenue, you must also be aware of the associated legal issues. How can you leverage AI and minimize the risk it presents?

Join this live Synopsys webinar in which a panel of legal experts and practitioners will answer your questions about the rise of AI in software development, and how you can responsibly leverage this new technology. We’ll cover:

• The benefits and risks for using AI in software development 
• The evolving legal and regulatory landscape 
• Practical advice for using AI today and into the future

Keeping Pace: Managing the risks of AI-generated code

Although AI has been around for decades, recent advances, including the development of generative AI tools, mean that AI-related stories are hitting the headlines on an almost-daily basis. This includes the copyright infringement proceedings brought by a group of American novelists against OpenAI in relation to use of their novels as training data, the ban by Samsung on using generative AI tools on its internal networks and company-owned devices, and the Hollywood writers’ strike over the use of AI in the film industry. 

More than half of organisations (52%) recently polled by Gartner reported that risk factors are a critical consideration when evaluating new AI use cases. So before spending time and money on the development of software by using AI, it is important for a company to understand the potential risks of doing so and how to mitigate such risks. Companies will need to rethink how development gets done, with the focus needing to be on evolving operations and training people as much as on technology. In addition, if looking to be acquired later down the line, that company will need to be ready to answer questions from prospective buyers.

Join this webinar, in which a panel of legal experts from CMS UK  will focus on two hot topics in relation to AI: intellectual property and governance. They will cover:

•         IP issues relating to the use of third party content to train AI tools
•         questions around subsistence, authorship/inventorship and ownership of any IP
•         the risk of the output infringing third party IP rights
•         key IP considerations in the context of a potential acquisition
•         how to manage development of software with the help of AI through effective governance
•         how ISO Standards and standardisation can play a significant role in mitigating the risks associated with AI and establishing robust governance frameworks

AI and Software Development: IP and Governance

The Rise of AI in Software Development

Artificial Intelligence

DevOps

DevSecOps

SDLC

Software Development

Security Risk

Open Source

Application Development

Application Security

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How Generative AI is Changing the SDLC

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