ML Security & Adversarial Robustness
Model-level attack research, robustness evaluation, and defense analysis for frontier and production systems.
Realistic adversarial testing. Systems thinking. Geopolitical forecasting. We bring specialists into project-based engagements where independent evaluation actually changes a decision.
Syntony runs an adversarial evaluation practice for frontier labs, public sector clients, and enterprise deployments. The Trusted Red Team Network is the bench we draw from when a scope demands depth we do not keep in-house full-time.
Engagements are project-based and confidential. Specialists bring published work, demonstrable expertise, and the judgment to turn a finding into evidence a reviewer can act on.
Scoped engagements with a threat model, evidence requirements, and a clear deliverable. Not crowdsourced bug hunting.
ML security, prompt engineering, policy analysis, geopolitical forecasting, and systems thinking work side by side on the same engagement.
We do not leave reports in a drawer. Specialists see how their work flows into mitigation, control, and oversight decisions.
Client details are confidential. Engagements run under NDA and findings are scoped to be reproducible where safe to disclose.
Model-level attack research, robustness evaluation, and defense analysis for frontier and production systems.
Documented bypasses, structured probing methodologies, and the discipline to turn a one-off into a class of finding.
Translation between technical findings and the controls, escalation triggers, and oversight artifacts they imply.
Scenario analysis, compute and supply-chain dynamics, and threat modeling at the level of states and institutions.
Causal mapping, feedback analysis, and the ability to trace a finding through the operational environment around it.
Tool use, memory, autonomy, and delegation testing for systems that act on their environment.
Applications are reviewed on a rolling basis. We respond to every submission.