Model integrity & adversarial testing
Overview
We assess AI/ML systems end-to-end — training data and MLOps pipelines, model artifacts, inference hardware, and deployed agent loops. We red-team deployed models, evaluate model capabilities against expert baselines, threat-model novel AI architectures, and stress-test the joins between disciplines where threat models routinely fall apart.
Our team combines ML researchers with application-security, systems, and cryptography engineers. AI failure modes live in the seams between these disciplines — a single-track review misses them.
Services & deliverables
We offer custom training solutions based on specific client needs. Our courses cover comprehensive security training for understanding and evaluating AI-based system risks, including AI failure modes, adversarial attacks, AI safety, data provenance, pipeline threats, and risk mitigation.
Our assessments address the entire AI/ML pipeline. Machine learning operations (MLOps) introduce novel attack vectors that differ from traditional software backdoors and vulnerabilities that impact ML-based systems and their operations. This service uncovers categories of vulnerabilities that can lead to ML-specific failure modes and degraded model performance or implicit and explicit access to and changes in data, model parameters, and the IP, increasing the system's overall attack surface.
Our offerings include threat modeling, applying operational design domains, and analyzing scenarios to identify functional risks. We also assess existing risk frameworks associated with AI adoption.
We help organizations measure and validate the capabilities of the AI models their systems employ (both first- and third-party). Specifically, we specialize in assessing models' offensive and defensive cyber capabilities by benchmarking their performance against experts, state-of-the-art tools, and novices using AI/ML tools.
Our services are informed by our first-hand experience assessing cybersecurity threats posed by models (AI red teaming) and building automated, AI-based systems for detecting and patching software vulnerabilities (as part of DARPA's AI Cyber Challenge). We help our customers integrate only the most effective AI tools into their internal software security processes.
Most pen-test firms hand you a PDF and walk away. Every Trail of Bits engagement ships a deliverable set your engineering team can plug into their workflow on day one and keep using long after we're gone.
| Deliverable | Trail of Bits | Status Quo |
|---|---|---|
| Written findings report Severity, difficulty, and exploit scenario for every finding. | ✓ | ✓ |
| Short- and long-term SDLC recommendations Not just bug fixes — process changes that prevent the next class of bug. | ✓ | — |
| Codebase + pipeline maturity evaluation Structured review of MLOps, data provenance, testing, and supply-chain hygiene. | ✓ | — |
| Exploit PoCs + code artifacts Runnable demonstrations for each finding so your engineers can reproduce and verify fixes. | ✓ | Sometimes |
| CI-ready Semgrep / CodeQL rules Custom static-analysis rules tuned to the model-serving and agent code we reviewed. | ✓ | — |
| Capability-evaluation + adversarial harnesses Drop-in benchmark and red-team harnesses your team keeps running after we leave. | ✓ | — |
| LLM and Claude-skill harnesses Agent skills and prompts to help your team triage findings and pre-flight the next review. | ✓ | — |
| Live walkthrough + fix-review retest We read out findings in person and re-test patches when they land. | ✓ | Sometimes |
| Open publication of generalizable findings Novel issues turn into public research so the whole industry benefits. | ✓ | — |
Comparison based on the standard published deliverables of the major application-security firms as of May 2026.
Public work
Recent public engagements
| Date | Engagement | Client / group | Effort |
|---|---|---|---|
| Oct 2023 | YOLOv7 | AI/ML Reviews | 4 wks |
| Mar 2023 | SafeTensors | AI/ML Reviews | 2 wks |
Get in touch
Book a complimentary one-hour meeting with one of our engineers to dive into a challenging technical issue, explore tooling options, and gain valuable insights directly from our experts. This session is purely technical — no sales talk, just a focused discussion that showcases our depth, talent, and capabilities.