# Benchmaxxing: When the Benchmark Becomes the Target

DevFeed: [Benchmaxxing: When the Benchmark Becomes the Target](<https://devfeed.tech/articles/benchmaxxing-when-the-benchmark-becomes-the-target-8302.md>)

Original publisher: [Read original article](<https://www.crowdstrike.com/en-us/blog/benchmaxxing-when-benchmark-becomes-the-target/>)

Author: Nathan Danneman

Published: 2026-09-12T11:17:51.295154Z

Content type: article

Language: en

Sources: [Blog](<https://devfeed.tech/sources/blog.md>)

Topics: [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Cybersecurity](<https://devfeed.tech/topics/cybersecurity.md>), [Ground truth / benchmark quality](<https://devfeed.tech/topics/ground-truth-benchmark-quality.md>), [Detection engineering](<https://devfeed.tech/topics/detection-engineering.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-and-cybersecurity](<https://devfeed.tech/tags/ai-and-cybersecurity.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [benchmarking](<https://devfeed.tech/tags/benchmarking.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [blog](<https://devfeed.tech/tags/blog.md>), [cybersecurity](<https://devfeed.tech/tags/cybersecurity.md>), [leaderboards](<https://devfeed.tech/tags/leaderboards.md>), [securing-ai](<https://devfeed.tech/tags/securing-ai.md>), [security](<https://devfeed.tech/tags/security.md>), [validation](<https://devfeed.tech/tags/validation.md>)

## AI overview

The article explains how public AI and cybersecurity benchmarks can become targets for optimization, a practice it calls "benchmaxxing." It argues that gaming, ceiling effects, data leakage, binary scoring, omitted costs, and aggregate scores can make benchmark results poor proxies for real-world defensive capability. The article proposes task-coupled internal benchmarks intended to evaluate end-to-end cyber agents and support rigorous science rather than visibility-driven score optimization.

## Source excerpt

The more attention a benchmark receives, the stronger the incentive to optimize for it. In AI and cybersecurity, this can have significant consequences.