Application Security & Gen AI
GenAI is changing how applications are built, developers can generate code faster, but it also amplifies software supply chain risk new dependencies, copied snippets, and inconsistent security patterns. Point tools can flood teams with findings, the future of AppSec is an integrated program that reduces noise and prioritises what matters.

Application Security (SCA, SAST & ASPM)
Problems
Building applications introduces code vulnerabilities, and adding AI amplifies these risks—especially in an industry crowded with fragmented tools rather than holistic solutions.
Solution
Application Security tooling can scan the code or software that has been complied to check for any vulnerabilities that can be fixed before being introduction into production.
Software Resource Manager
Problems
Lot’s of alerts in individual tooling, manual searching.
Solution
Prioritises security risks across security stack.
Our Vendors of Choice

Firstly...
First, shift security into the developer workflow. Snyk/BlackDuck/Invicti adds AI powered workflows to help teams find, prioritize, and fix issues early. Black Duck strengthens software composition analysis by identifying open source and third party components, enforcing policy, and producing SBOMs plus the ability to trace copied or AI generated snippets back to source projects.

Secondly...
govern what gets built and shipped. JFrog Artifactory becomes the system of record for packages and container images, while JFrog Xray/ Snyk/BlackDuck provides enterprise grade SCA to identify, prioritize, and remediate vulnerabilities and license compliance issues.


Finally...
Bring context and validation Apiiro/Invicti’s ASPM layer applies a contextual, risk based approach to correlate and prioritize risks across the SDLC, and Snyk/BlackDuck/Invicti validates real exposure with DAST against running web applications and APIs.
Together, these platforms enable secure, AI accelerated delivery without slowing engineering.



Is this Relevant to you?
Industry
Which of my customers care about The future of Application Security & GenAI? Typically, organisations with 50+ developers, high release velocity, heavy open source usage, and strong compliance drivers especially:
Financial services/FinTech
Insurance
Healthcare
Public sector
Telecommunications
Energy
Retail/Ecommerce
Technology/SaaS/ISVs
Transportation/Logistics
Roles
Who cares about The future of Application Security & GenAI?
Platform Engineering Manager
CISO/Head of Security
Head of Application Security (AppSec)
Product Security Lead
VP Engineering/CTO
Platform Engineering Manager
Developer Platform Owner
DevSecOps Lead/CI/CD Owner

Key Discovery Questions
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1 |
Are developers using GenAI coding assistants today, and what guardrails exist (secure patterns, review controls, policy)? |
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2 |
How do you currently find and manage risk across code, open source dependencies, containers, and APIs and is “too many findings” a problem? |
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3 |
Do you have a single source of truth for artifacts and images, and do you scan + gate what gets pushed into production? |
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4 |
Are you generating SBOMs today, and can you meet customer or regulatory expectations for provenance and compliance? |
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5 |
How do you validate real exploitable issues in running apps (DAST) and ensure findings map to owners, with measurable remediation time? |

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