Results for “data-exposure”

Design clear, accessible data visualizations with appropriate chart selection and styling.

Big Data Based Analysis Skill

Collects publicly available information about a target organization to identify attack surfaces, social engineering targets, technology stacks, and credential exposures for authorized security testing.

Time-Series Data

Use to fulfil a subject access request from support data — finding everything about the person, and deciding what must be redacted before disclosure. Trigger for "handle this SAR", "subject access request", "customer wants all their data", DSAR fulfilment from support systems, "a customer asked for their call recordings", or an employee requesting their own QA records.

Configure and manage data quality tests, profiling, alerts, and incidents in OpenMetadata. Use when setting up quality tests, configuring profiler workflows, creating observability alerts, or triaging data quality incidents.

Detect data staging activity before exfiltration by monitoring for archive creation with 7-Zip/RAR, unusual temp folder access, large file consolidation, and staging directory patterns via EDR and process telemetry.

Persists app data on Android using Room, SQLite, SharedPreferences, DataStore, and encryption.

Use to build PNAS's Data Availability Statement and deposition plan — mandatory deposition of data in an approved repository at submission, accession numbers/DOIs, public + archived code, and materials sharing. "Available on request" is not sufficient for primary data.

Test web applications for XML injection vulnerabilities including XXE, XPath injection, and XML entity attacks to identify data exposure and server-side request forgery risks.

Use to build Cell's data and code deposition plan and the Data and Code Availability statement that lives inside STAR Methods Resource Availability — approved repositories, accessions/DOIs at submission, and Cell's three-bullet availability format with Mendeley Data as Elsevier's default.

Apache Spark, Hadoop, distributed computing, and large-scale data processing for petabyte-scale workloads

Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.

California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA) compliance advisor — business threshold analysis, consumer rights fulfillment (access, delete, correct, opt-out of sale/sharing, limit SPI), privacy notice drafting, service provider vs. contractor vs. third-party classification, sensitive personal information (SPI) handling, data minimization, opt-out mechanisms, CPPA enforcement, penalty exposure, GDPR comparison, and gap assessments for businesses operating in or targeting California residents.

Analyse experiment results, run validity checks (SRM, exposure parity, data integrity, novelty/primacy), interpret causally, make a ship/iterate/kill decision against the pre-declared rule, and append to cumulative learnings. Forces honest readouts — strips significance claims from underpowered or peek-violating tests; never lets directional results masquerade as causal wins. Load when results exist, or when the user says "read out this experiment", "analyse the test", "did the test win", "interpret the results", "what did we learn", "ship or kill", or when the experimentation orchestrator routes here.