AI-native vulnerability research for mobile computing environments — mapping trust relationships, discovering systemic weakness conditions, preserving evidence lineage, predicting related variants, and supporting controlled exploit development and validation on owned or explicitly authorized research targets.
OBSIDIAN treats the underlying security condition — not merely the individual finding — as the unit of research. Its Exploit Intelligence Graph connects components, trust boundaries, observations, evidence, hypotheses, primitive candidates, variants, analyst decisions, and controlled validation results into a persistent, auditable research lineage.
Normalizes authorized software and system metadata, maps security-control and trust relationships, and surfaces evidence-backed observations for expert review.
Reasons over selected hypotheses and the evidence graph, generating constrained research proposals with explicit confidence, provenance, and falsification criteria.
Preserves machine-to-machine and human research lineage from component and observation through hypothesis, primitive candidate, variant, and validation decision.
Designed to turn analyst-approved research hypotheses into controlled reproducers, exploitability proofs, regression artifacts, and variant-validation packages for isolated, authorized environments.
Validates candidate conditions and mitigations in controlled environments, records what succeeded or failed, and feeds those results back into the graph for future prediction.
OBSIDIAN is an active research platform. Machine-generated observations and hypotheses remain research signals until supported by evidence and human validation. Controlled exploit work is scoped to owned, public research, historical, synthetic, or explicitly authorized targets.