BaitaPhish Research Intelligence analyzes published work across cybersecurity, AI and agents, machine learning, systems, privacy, and mathematics. Each analysis links to its sources and keeps methods, evaluation boundaries, and limitations visible. Source-paper findings and BaitaPhish interpretation are identified separately; evidence review does not establish independent replication.
19 matching research articles
The proposed decoding strategy reuses a preserved pre-adaptation language model to guide a speech-recognition model during inference.
2 min read
The work introduces a legally grounded hierarchy that combines free-form descriptions of disputed matters with structured legal categories.
2 min read
The proposed defense combines protected evidence selection with regulated source use to address malicious optimization across the search-to-generation pipeline.
2 min read
The work proposes a model-based deployment methodology that automates application adaptation for phased execution.
2 min read
The inquiry distinguishes repeated success, distinct coverage, accepted evidence, resource use, service capacity, and operational protection when evaluating added inference effort.
3 min read
The proposed alternative invokes skill packages through delegated agents instead of placing their instructions in the primary agent context.
3 min read
The study asks whether estimating both location and scale in time-series forecasting can improve point-estimate accuracy.
2 min read
The work systematically evaluates inference-time token merging across a multilingual speech-recognition model family and examines its interaction with parameter-efficient adaptation in lower-resource settings.
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The evaluated cost structure is amortizing because substantial deployment expenditure is paid per hired trainer only at setup, while recurring expenditure is markedly smaller and becomes diluted over the federation lifetime.
3 min read
The proposed contribution is a generalist-oriented prompting method that uses qualitative codebooks to detect cybercrime incidents in consumer narratives with pretrained language models.
2 min read
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.
