new·The score now tells you which way it movedA brain's exam only ever grows: its own material writes questions, and so does every question a real caller asked and did not get answered. The score is a percentage over that growing set, so a brain that learned more could post a smaller number — and this week three did. One of them answered two MORE questions than the week before and showed eighteen points less. Printed as a single percentage, that reads as decline to a reader and as punishment to anyone who contributes material.all news →
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OWASP Cheat Sheets · all subjects

attack-surface/measurement

4 notes, read out of this brain and free to use. Each one was extracted from a source and is re-checked against its exam.

Relative Attack Surface Quotient (RSQ) measurement method

The Relative Attack Surface Quotient (RSQ) is a method developed by Michael Howard at Microsoft for measuring an application's Attack Surface and tracking changes over time. It calculates an overall attack surface score for a system and measures this score as changes are made to the system and its deployment.

Attack Surface Metric calculation approach

Carnegie Mellon researchers developed a formal Attack Surface Metric by calculating the sum of all entry and exit points, channels (different ways clients or external systems connect including TCP/UDP ports, RPC endpoints, named pipes), and untrusted data elements. They then apply a damage potential/effort ratio to these elements to identify high-risk areas.

Network-level fingerprinting signals

JA3/JA4 is a TLS ClientHello fingerprint; headless tooling often produces uncommon JA3 values. HTTP/2 fingerprint (Akamai method) analyzes frame ordering, settings, and priorities. Sec-CH-UA-* Client Hints are declared by the browser but can be verified against TLS fingerprint. These passive network-level signals require no client cooperation and should be used before resorting to browser-side fingerprinting.

Browser-side fingerprinting signals (last resort)

WebGL renderer string, canvas hash, font list, and audio context are strong fingerprinting signals but invasive. Page-level behavioral telemetry such as mouse paths, scroll behavior, and focus events should be collected only on sensitive flows. Browser-side fingerprinting should be a last resort after passive network signals.

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