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.
AI Supply Chain Security Audit: manual, exploit-led coverage — web, API, cloud, network and AI-agent security.
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 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 this engagement
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 RMFMITRE ATLASSLSA supply-chain frameworkOWASP 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
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:
MCP Server & Tool-Chain Security Testing — MCP server security testing — tool schema tampering, confused-deputy paths, credential-scope leakage and abuse of Model…
AI Agent Penetration Testing — Penetration testing for autonomous AI agents — tool-use abuse, goal hijacking, privilege escalation and sandbox escape…
LLM Application Penetration Testing — LLM application penetration testing — the full stack around your model: prompts, plugins, APIs, output handling…
Related product from AgentOffense
Our offensive research feeds products you can run yourself — tools that complement ai supply chain security audit:
How much does AI Supply Chain Security Audit cost?
Every ai supply chain security audit is scoped and priced individually, so you pay for exactly the coverage you need — with no hidden extras. After a short, no-obligation scoping call we send a fixed-price quote, usually within one business day, with clear deliverables, a firm timeline and a complimentary retest included. The price of your ai supply chain security audit depends on the size and complexity of the target and the depth of testing required, so you always know the cost up front before any work begins.
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.
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