ML Security & Adversarial Robustness
Model-level attack research and robustness evaluation for frontier or production systems, including analysis of possible defenses.
Syntony brings independent specialists into confidential, project-based adversarial evaluations when an engagement needs deeper technical, policy, or strategic expertise.
Syntony runs adversarial evaluations for frontier labs, public-sector organizations, and companies deploying AI. The Trusted Red Team Network lets us assemble specialists when an engagement requires expertise beyond the core team.
The network is project-based and confidential. We select specialists based on the engagement's needs and work they can demonstrate.
Each engagement has a specific threat model. Responsibilities and the final deliverable are agreed before work begins.
An engagement may combine technical and policy specialists when a finding needs both forms of analysis.
Findings are documented with the evidence and context needed for the client's review and control process.
Engagements run under NDA. Within those limits, methods and evidence should support independent review and reproduction.
Model-level attack research and robustness evaluation for frontier or production systems, including analysis of possible defenses.
Systematic testing for prompt injection and jailbreaks, with enough documentation to reproduce a bypass and identify the broader failure mode.
Analysis that connects a technical finding to policies, decision rights, controls, and practical remediation.
Research on how state behavior and compute supply chains shape the security consequences of AI deployment.
Analysis of how technical failures interact with organizational processes and operating conditions during deployment.
Evaluation of permissions, tool use, memory, delegation, and recovery in systems that can act on their environment.
Applications are reviewed on a rolling basis, and we respond to each submission.