Your AI stack is only as trustworthy as the models, plugins and datasets it depends on. Our AI supply chain security audit reviews the provenance and integrity of every component — third-party models, extensions, training data and pipelines — for the trust risks that traditional AppSec overlooks.
We surface where untrusted or tampered components could compromise your AI system before it ever reaches users.
Our AI supply-chain audit reviews every component your AI system depends on: base and fine-tuned models, their provenance and integrity, training and fine-tuning datasets, plugins and extensions, and the pipelines and registries that build and serve them. We assess open-source, commercial and in-house models, hunting for backdoored artifacts, poisoned data, malicious plugins and integrity gaps that could compromise your application invisibly — the AI equivalent of a software supply-chain attack.
Why it matters
Your AI system is only as trustworthy as the models, datasets, plugins and pipelines it is built from. A tampered model, poisoned dataset or malicious plugin can backdoor your application invisibly, bypassing every runtime control you have in place.
AI supply-chain assurance is now as important as software supply-chain security — and far less mature in most organizations, which is exactly why attackers are turning to it.
What we test
- Model provenance & integrity
- Plugin & extension risk review
- Dataset integrity & poisoning exposure
- Fine-tune data leakage
- Dependency & pipeline security
- Model artifact & registry access control
Common vulnerabilities we uncover
- Compromised or backdoored model artifacts
- Training and fine-tuning data poisoning
- Malicious or over-privileged plugins and extensions
- Model provenance and integrity gaps
- Fine-tune data leakage through the model
- Insecure model registries and pipelines
Our AI Supply Chain Security Audit methodology
- Scoping & rules of engagement. We agree objectives, targets and boundaries for your ai supply chain security audit, so testing is safe, authorized and focused on what matters to your business.
- Reconnaissance & mapping. We enumerate the full attack surface in scope, building a complete picture before any exploitation begins.
- Manual exploitation. Our senior testers chain vulnerabilities by hand — going far beyond automated scanners — to prove real, demonstrable impact.
- Analysis & reporting. Every finding is triaged, risk-rated with CVSS and written up with a copy-paste reproduction and clear remediation.
- Remediation support & free retest. We support your team through the fixes and retest the remediated issues to confirm they are genuinely closed.
Tools & techniques
We audit the AI supply chain using provenance analysis, artifact integrity verification, dependency and plugin review, and targeted data-poisoning and extraction tests. We inspect model artifacts and their signing, review training and fine-tuning data handling, enumerate plugin and extension permissions, and probe fine-tuned models for training-data leakage. Findings are mapped to the NIST AI RMF and MITRE ATLAS with supply-chain hardening recommendations.
When you need AI Supply Chain Security Audit
- When using open-source or third-party models and datasets
- Before deploying fine-tuned models trained on sensitive data
- For organizations building AI/ML platforms and model registries
- As part of NIST AI RMF and secure-MLOps programs
What you receive
- AI supply-chain risk map
- Component trust findings
- Provenance & integrity controls
- Prioritized remediation plan
What’s included in your report
Every ai supply chain security audit engagement concludes with a comprehensive, board-ready report and a working session to walk your team through it. Your report includes:
- An executive summary with overall risk posture for non-technical stakeholders
- Detailed technical findings, each with a step-by-step, copy-paste reproduction
- CVSS v3.1 severity ratings and business-impact context for every issue
- Prioritized, actionable remediation guidance your engineers can apply directly
- A complimentary retest to confirm fixes and update finding status
- A formal attestation letter for customers, auditors and compliance programs
Standards & frameworks
NIST AI RMF
MITRE ATLAS
SLSA supply-chain framework
OWASP LLM Top 10 (LLM05)
Outcomes you can expect
After your ai supply chain security audit, you will have clear, evidence-based visibility into your real security risk — not a scanner’s guesswork. You will know exactly which weaknesses an attacker could exploit, what the business impact would be, and the precise steps to fix them in priority order. Teams use our findings to close critical gaps, satisfy customer and regulator security requirements, and demonstrate due diligence to their board. With a complimentary retest included, you also get documented proof that the issues are genuinely resolved.
Engagement details & logistics
Every ai supply chain security audit starts with a short, no-obligation scoping call to understand your goals, environment and constraints, followed by a fixed-price proposal and a clear statement of work. Most engagements are delivered fully remotely, with on-site work arranged where it genuinely adds value. Throughout testing we maintain an agreed communication cadence and escalate any critical, high-impact finding to you immediately rather than waiting for the final report. All work is performed under a signed NDA with strict data-handling controls, using safe, non-disruptive techniques and carefully coordinated rules of engagement to protect your production systems. On completion you receive your report and a walkthrough session, followed by a complimentary retest once your fixes are in place. Typical engagements are booked one to three weeks in advance, and urgent or pre-deadline testing can often be accommodated — just ask at hi@agentoffense.com.
Why organizations choose AgentOffense for AI Supply Chain Security Audit
Our ai supply chain security audit is delivered by senior offensive-security engineers who test the way real attackers do — manually, creatively and with a relentless focus on proving genuine, demonstrable impact. Here is what sets our engagements apart:
- Manual, exploit-driven testing that chains vulnerabilities the way a real attacker would, going far beyond what automated scanners can find.
- Reproducible proof for every finding, with copy-paste reproduction steps your engineers can follow and independently verify.
- Honest severity calibration so you invest in fixing what genuinely matters and avoid wasting effort on false positives and noise.
- Clear, business-focused reporting that speaks to engineers and executives alike, tying every issue to real-world impact.
- A complimentary retest included, so you get documented proof that your fixes actually close the attack path.
- Responsible, collaborative delivery with a named point of contact and secure handling of all data throughout the engagement.
Explore related services
AI Supply Chain Security Audit is frequently scoped alongside our other offensive-security services for broader coverage. Explore related engagements that complement it:
Frequently asked questions
Why does AI supply chain security matter?
Tampered models, poisoned datasets and malicious plugins can backdoor an AI system invisibly. Supply-chain assurance is now as important as it is for traditional software.
Do you review open-source models we use?
Yes. We assess provenance, integrity and known risks of open-source and third-party models in your stack.
Can you check for training-data leakage?
Yes — we test whether fine-tuned models leak sensitive training data through crafted prompts.
Do you review open-source and third-party models?
Yes. We assess provenance, integrity and known risks of open-source, commercial and fine-tuned models across your stack.
Can you detect training-data leakage?
Yes — we test whether fine-tuned models regurgitate sensitive training data through crafted extraction prompts.
Why is AI supply-chain security a growing concern?
Tampered models, poisoned datasets and malicious plugins can backdoor an AI system in ways runtime controls cannot catch, making supply-chain assurance as critical for AI as it is for software.
Can you assess our MLOps pipeline?
Yes. We review model build, storage, signing and serving pipelines, plus registry access controls, for supply-chain integrity.
Can you check model artifact integrity and signing?
Yes. We review how models are built, signed, stored and served, and assess registry access controls for supply-chain integrity.
How long does an AI supply-chain audit take?
Usually one to three weeks depending on the number of models, datasets and pipelines in scope.