Results for “risk-detection”

Identifies, assesses, and mitigates risks at every phase of a development pipeline.

Automates detection engineering workflows in Google SecOps by extracting threat intelligence, generating detection opportunities, simulating attacker behavior with synthetic events, evaluating rule coverage, and creating new YARA-L 2.0 rules to close gaps.

Detect container escape attempts using runtime security tools like Falco, Sysdig, and custom seccomp/audit rules.

Detect poisoned training data and backdoored models across the ML pipeline using statistical analysis, activation clustering, and spectral signatures.

Performs a full-stack security posture assessment with 0-100 risk scoring, scanning dependencies, code patterns, configuration, and data handling, then produces a prioritized report and routes to specialized skills.

Scans local repos and AI agent skill folders for security drift, saves trusted baselines, and compares changes after updates to highlight risky new capabilities.

Establishes recurring vulnerability scanning workflows using Nessus, Qualys, or OpenVAS, prioritizes findings with risk scoring and CISA KEV data, integrates with SIEM for exploitation detection, and tracks remediation via SLA-based dashboards and automated ticketing.