Snyk AI/LLM Penetration Testing Service Description

Overview

AI/LLM Penetration Testing service delivers an expert-driven, end-to-end security evaluation of your AI and Large Language Model-powered applications. We go beyond traditional application security testing to assess five critical layers: model behavior, LLM APIs and orchestration, integration layers (like function calling and RAG), data privacy controls, and the surrounding SDLC/infrastructure. Our methodology encompasses scoping, threat modeling, design review, custom test plan development, rigorous hands-on testing, and continuous reporting, culminating in clear remediation advice and a validation retest.

Key Benefits

• Holistic AI/LLM Security Assessment: Evaluates the entire model stack, uncovering risks beyond traditional application security.

• Threat-Led Approach: Focuses on real-world attack scenarios and potential business impact.

• Actionable Remediation Guidance: Provides clear, prioritized fixes mapped to relevant security standards.

• Reproducible Evidence: Backs findings with concrete proof-of-concept exploits and supporting data.

• Comprehensive Coverage: Assesses model behavior, APIs, integrations, data privacy, and infrastructure.

• Validation of Remediation: Includes a no-cost retest to confirm the effectiveness of implemented fixes.

• Clear Reporting for All Stakeholders: Delivers executive summaries and detailed technical reports.

AI/LLM Penetration Testing Activities

Our comprehensive methodology ensures a thorough evaluation of your AI/LLM systems:

• Scoping & Threat Modeling: Collaborative meeting to define the scope of the engagement and develop a threat model specific to your AI/LLM implementation.

• Design Review & Test Planning: Analysis of your AI/LLM architecture and the creation of a custom test plan tailored to your specific systems and identified threats.

• Fieldwork: Rigorous hands-on testing across five key layers:

  • Model Behavior: Assessing for jailbreaks, data leakage, guardrail bypass, extraction, and model-level vulnerabilities.

  • LLM APIs/Orchestration: Identifying traditional AppSec issues as well as vulnerabilities specific to agentic and LLM API interactions.

  • Integration Layers: Evaluating the security of function calling and Retrieval-Augmented Generation (RAG) pipelines.

  • Data Privacy Controls: Examining measures protecting user and training data.

  • SDLC/Infrastructure: Assessing the security of the surrounding development lifecycle and infrastructure (CI/CD, servers, cloud).

• Continuous Reporting: Regular updates on findings throughout the testing process.

• Executive & Technical Readouts: Presentation of findings with a focus on business impact for leadership and detailed technical information for security teams. Findings are mapped to standards like ISO 42001, NIST AI RMF, OWASP LLM Top 10, OWASP Agentic AI, OWASP GenAI Security, OWASP Top 10, OWASP API Top 10, and MITRE ATLAS.

• Remediation Support & Retest: Guidance on addressing identified vulnerabilities, followed by a no-cost retest to validate the effectiveness of implemented fixes and a formal attestation of the testing.

Key Deliverables

Upon completion of the engagement, you will receive:

• Executive Summary: A high-level overview of the security posture and key findings for leadership.

• Detailed Technical Report: In-depth documentation of all identified vulnerabilities, their impact, and remediation recommendations.

• Evidence Bundle: Supporting materials including logs and proof-of-concept exploits.

• Attestation Letter: Formal confirmation of the penetration testing engagement and the validation of remediated findings (post-retest).

Engagement Timeline

Typical engagement timelines for single LLM agent systems or small multi-agent systems are as follows (timelines scale with system complexity):

• ½ day kickoff

• ½ day of design review and planning

• 4 or 9 days of testing with rolling reporting

• ½ day final readout

• 1 day for retest and attestation

Key Assumptions

To ensure a successful and effective AI/LLM penetration testing engagement, we require the following from the customer:

• Access to Test Environment: Provision of a stable and representative test environment for the AI/LLM applications and related infrastructure.

• Test Credentials and Access: Provision of necessary credentials and access permissions to interact with all in-scope AI/LLM components, APIs, user interfaces, and relevant data stores.

• Detailed System Information: Provision of relevant documentation and information about the AI/LLM architecture, data flows, APIs, training data sources (if applicable and in scope), and any existing security controls.

• Clear Communication Channels: Establishment of clear and responsive communication channels with designated technical contacts.

• Availability of Technical Personnel: Availability of knowledgeable technical personnel to answer questions and assist with troubleshooting.

• Defined Scope Confirmation: Formal confirmation and agreement on the testing scope.

• Awareness of Testing Activities: Ensuring relevant internal teams are aware of the scheduled testing.

• Prompt Response to Findings: Commitment to reviewing findings and engaging in remediation discussions.