Accelerated Innovation

Ensuring You Have the Security Vulnerabilities Testing Capabilities to Win

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Ensuring You Have the Security Vulnerabilities Testing Capabilities to Win

Description

Security Vulnerabilities Testing is the ongoing process of probing GenAI systems to detect flaws, misconfigurations, or weaknesses that may expose them to exploitation. This capability focuses on continuously validating the security posture of GenAI models, APIs, and infrastructure through targeted testing strategies.

Why it's Important

GenAI solutions introduce dynamic and complex risks that traditional testing methods may not catch-ranging from prompt injection and data leakage to model inversion and hallucination-induced vulnerabilities. Without continuous testing, even well-designed systems can become brittle, exposing organizations to regulatory, reputational, or operational harm. Security Vulnerabilities Testing helps product and security teams proactively identify and close these gaps before they are exploited. It reinforces secure-by-design practices, builds trust in GenAI adoption, and ensures alignment with evolving threat models and compliance expectations.

Why it's Challenging @ Scale

  • Rapidly evolving threat surfaces: New vulnerabilities in GenAI models can emerge suddenly as use cases, data inputs, and model behaviors shift.
  • Lack of standardized GenAI test protocols: Existing security testing tools often fail to account for GenAI-specific risks like prompt leakage or model manipulation.
  • Difficulty simulating real-world attacks: Traditional pen tests may not reflect how malicious actors exploit conversational AI or adaptive model behavior.
  • Siloed testing responsibilities across teams: Fragmented ownership between security, engineering, and product leads to inconsistent coverage and oversight.
  • Tooling gaps for GenAI-specific validation: Many organizations lack purpose-built tools for testing model-specific vulnerabilities at scale.

Complexity

High: Testing GenAI vulnerabilities requires cross-functional expertise, evolving test strategies, and specialized tooling that is not yet widely adopted or standardized.

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Taking Action

Though most organizations begin their GenAI journey with significant knowledge gaps, there are targeted actions that can be taken to accelerate the process. Select your group’s current maturity, based on your assessment results, and act today.

The most important part of any journey is starting… To move from “Exploring” to “Experimenting”, focus on the following key actions:
  • Explore Key Concepts & Best Practices: Complete the Secure AI Best Practices workshop (2 hrs.) to understand foundational key concepts and explore applied best practices.
  • Introducing Secure AI Design Principles
  • Framing Security in AI Lifecycle Context
  • Mapping Threat Surfaces in GenAI Systems
  • Identifying Roles and Responsibilities in Secure AI
  • Linking Security to AI Governance Goals
  • Define Your Action Plan: Outline concrete, prioritized steps your organization will take to implement GenAI Strategy.
  • Align on your Current State and define your Target State
  • Create an actionable enablement plan
  • Define target timeline and measures of success
  • Deliver Quick Wins: Small, high-impact GenAI projects that can demonstrate tangible value in a short time frame.
  • Pilot security testing on a low-risk GenAI feature: Apply basic fuzzing or input manipulation tests to validate your tooling and processes.
  • Establish a shared vulnerability logging framework: Create a central process for logging, tagging, and prioritizing issues uncovered during testing.
  • Assign early ownership roles across teams: Identify leads for GenAI security testing within product, engineering, and security to enable faster response cycles.
To move from Experimentation to “Lifting-Off”, prioritize the following actions:
  • Complete one or more of our Deep Dive Courses: Begin exploring key concepts and best practices, including:
  • Secure AI Governance & Accountability Best Practices
  • Secure AI Risk Management Best Practices
  • Secure AI Security Controls Best Practices
  • Secure AI Prompt Injection Best Practices
  • Secure AI Sensitive Information Best Practices
  • Secure AI Supply Chain Risks Best Practices
  • Secure AI Model Poisoning Best Practices
  • Secure AI Output Handling Best Practices
  • Secure AI Excessive Agency Best Practices
  • Secure AI System Prompt Risks Best Practices
  • Secure AI Vectorization Risks Best Practices
  • Secure AI Misinformation Best Practices
  • Secure AI DDoS Prevention Best Practices
  • Nail It Before You Scale It: Assess and optimize your solution or process before adopting it at scale
  • Assess Your Proposed Solution or Process: Validate how GenAI security testing is currently performed and identify any critical gaps in test coverage or tooling.
  • Define in-scope Processes and Guardrails: Clarify which GenAI systems, models, and APIs fall under mandatory security testing and what standards must apply.
  • Close any Data or Measurement Gaps: Ensure vulnerability testing data is captured systematically and used to inform metrics, dashboards, and remediation workflows.
  • Define Your Adoption & Scaling Plan: Create a structured roadmap for how GenAI solutions will be rolled out across teams, workflows, or business units
  • Define Your Phased Implementation Plan: Prioritize testing rollout based on risk exposure, business impact, and model sensitivity.
  • Build Awareness and Finalize Enablers: Provide toolkits, documentation, and support resources to help teams independently execute testing protocols.
  • Operationalize Your Comms Plan: Clearly articulate testing expectations, responsibilities, and escalation pathways across technical and non-technical stakeholders.
To move from Lifting-Off to “Accelerating”, prioritize the following actions:
  • Formalize Your Best Practices: Document and standardize what’s working to ensure consistent, scalable success across teams and use cases
  • Publish a Security Testing Playbook: Capture approved tools, workflows, and severity classifications in a reusable format.
  • Build Testing into Dev Workflows: Integrate vulnerability scans into CI/CD pipelines and development toolchains.
  • Create Repeatable Templates and Checklists: Offer standard forms for test execution, results reporting, and remediation guidance.
  • Accelerate Your Adoption: Intensify efforts to embed GenAI across your organization by expanding use cases, increasing user engagement, and removing adoption barriers
  • Expand Testing Coverage Across Teams: Ensure that every GenAI project includes security vulnerability testing as a non-negotiable step.
  • Automate Testing Where Possible: Use AI or scripting tools to auto-trigger security checks as code is deployed or updated.
  • Upskill Teams to Self-Test: Enable engineering teams to own day-to-day testing and know when to escalate issues.
  • Celebrate Your Wins: Publicly acknowledge team accomplishments to build and sustain adoption momentum
  • Spotlight Secure-First Product Launches: Share examples where proactive testing prevented downstream risk.
  • Recognize Cross-Functional Test Collaborations: Highlight collaboration between security and product teams as a model.
  • Offer Internal Awards for Testing Impact: Acknowledge those who uncover and resolve critical vulnerabilities early.
The “Accelerating” stage represents “Target State” for many capabilities. “Breaking Away”, on the other hand, suggests that the specific Capability represents a clear competitive advantage for your business.
  • Streamline & Embed: Integrate GenAI into core workflows while eliminating friction points to make usage seamless and routine
  • Embed Testing in Standard Operating Procedures: Ensure security testing is mandatory and routine across GenAI solution delivery.
  • Simplify Team Access to Testing Tools: Provide one-click access to approved scanners, fuzzers, and logging platforms.
  • Visualize Test Coverage via Dashboards: Offer real-time dashboards to monitor testing frequency, gaps, and remediation status.
  • Leverage Automation: Use GenAI-powered tools and workflows to streamline repetitive tasks, enhance operational efficiency, and reduce manual effort
  • Automate Risk-Based Testing Triggers: Dynamically escalate or de-escalate testing based on model risk profiles or usage patterns.
  • Deploy AI-Assisted Vulnerability Detection: Use GenAI to identify patterns in logs, payloads, or prompts that indicate emerging threats.
  • Auto-Generate and Route Test Reports: Streamline documentation by generating and distributing security findings automatically.
  • Evolve & Further Accelerate: Continuously refine GenAI strategies based on insights and outcomes, while expanding into more complex or high-impact use cases
  • Refine Test Protocols Based on Threat Trends: Keep testing strategies aligned with new risks and attacker behavior.
  • Extend Testing to New GenAI Capabilities: Apply proven methods to agents, multimodal systems, and retrieval-augmented models.
  • Benchmark Testing Against Industry Leaders: Compare your practices to peer organizations and incorporate leading-edge techniques.

Key "Watchouts"

As you take action you’ll want to avoid:

  • Assuming traditional tests are sufficient: Generic testing tools often miss GenAI-specific vulnerabilities like model drift or prompt injection.
  • Overloading security teams with testing responsibilities: Without shared accountability, bottlenecks will slow adoption and increase risk exposure.
  • Failing to test across model updates and retraining: Security gaps often emerge after version changes or new data inputs.
  • Ignoring test results due to unclear remediation paths: Teams may under-prioritize issues without clarity on how to resolve or escalate.
  • Treating testing as a one-time event: GenAI systems require ongoing validation, not point-in-time audits.

Targeted Benefits

While Security Vulnerabilities Testing can be challenging, its benefits are clear and compelling, including:

  • Earlier risk detection in the GenAI lifecycle: Shift-left testing prevents issues from reaching production environments.
  • Faster incident response and resolution: Clear ownership and real-time alerts reduce remediation delays.
  • Increased trust in GenAI solutions: Frequent validation builds confidence among users, stakeholders, and regulators.
  • Improved coordination across teams: Shared testing responsibilities drive alignment between security, product, and engineering.
  • Sustained compliance posture: Ongoing validation ensures readiness for audits, certifications, and evolving regulatory requirements.

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Eddie
Accelerated Innovation

Hi, I'm Eddie 👋

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