A provider-neutral systems-security framework for constraining autonomous AI agents through capability assessment, effective authority, bounded reach, exposure-path analysis, and runtime trajectory assurance.
A decision model for multi-account AWS security: trust boundaries, identity, preventive and detective controls, evidence, containment, and recovery.
A vendor-neutral threat model for AI agents that separates model behavior from authorization and maps threats to controls, evidence, tests, and residual risk.
A practical method for turning system boundaries and abuse paths into owned controls, observable evidence, and repeatable tests.
Provenance turns a security claim into a traceable record of source, transformation, review, and intended use—without pretending lineage alone guarantees truth.
NIST's current incident-response guidance integrates preparation, response, recovery, and continuous improvement across the six CSF 2.0 Functions.
OPA lets you centralize policy decisions (Rego) for authz and compliance across microservices, Kubernetes, CI, and more.
Sigma is a detection-rule format that lets you write once and translate to multiple SIEM backends (Splunk, Sentinel, etc.).
SLSA is a maturity model for build provenance and tamper resistance. The real value is disciplined build pipelines and signed attestations.
