Results for “traffic-shaping”

Compares Trailmark code graphs at two source code snapshots to surface security-relevant structural changes that text diffs miss, such as new attack paths, blast radius growth, and privilege boundary modifications.

Build network traffic baselines from NetFlow/IPFIX data using Python pandas for statistical analysis, z-score anomaly detection, and hourly/daily traffic pattern profiling.

Analyzes network traffic captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts.

Runs full Trailmark structural analysis by building a graph and computing pre-analysis passes for hotspots, taint, blast radius, privilege boundaries, and attack surface.

Exploit-phase writing — shapes raw material into an article paragraph by paragraph. Use when the user has a raw-material pile and wants the final article written.