# AI and cybersecurity

Published articles for AI and cybersecurity.

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## 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.

## Announcing early access to Chainguard's CUDA Optimized Images

DevFeed: [Announcing early access to Chainguard's CUDA Optimized Images](<https://devfeed.tech/articles/announcing-early-access-to-chainguard-s-cuda-optimized-images-12885.md>)

Original publisher: [Read original article](<https://www.chainguard.dev/unchained/announcing-early-access-to-chainguards-cuda-optimized-images>)

Published: 2024-04-25T00:00:00Z

Content type: news

Language: en

Sources: [Chainguard: Unchained](<https://devfeed.tech/sources/chainguard-unchained.md>)

Topics: [CUDA](<https://devfeed.tech/topics/cuda.md>), [container images](<https://devfeed.tech/topics/container-images.md>), [Containers](<https://devfeed.tech/topics/containers.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [PyTorch](<https://devfeed.tech/topics/pytorch.md>), [Security](<https://devfeed.tech/topics/security.md>), [Vulnerabilities](<https://devfeed.tech/topics/vulnerabilities.md>), [model-deployment](<https://devfeed.tech/topics/model-deployment.md>), [AI Development](<https://devfeed.tech/topics/ai-development.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-and-cybersecurity](<https://devfeed.tech/tags/ai-and-cybersecurity.md>), [ai-development](<https://devfeed.tech/tags/ai-development.md>), [ai-software-supply-chain](<https://devfeed.tech/tags/ai-software-supply-chain.md>), [ai-software-supply-chain-security](<https://devfeed.tech/tags/ai-software-supply-chain-security.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [chainguard](<https://devfeed.tech/tags/chainguard.md>), [chainguard-images](<https://devfeed.tech/tags/chainguard-images.md>), [chainguard-pytorch-image](<https://devfeed.tech/tags/chainguard-pytorch-image.md>), [container-images](<https://devfeed.tech/tags/container-images.md>), [containers](<https://devfeed.tech/tags/containers.md>), [cuda](<https://devfeed.tech/tags/cuda.md>), [cves](<https://devfeed.tech/tags/cves.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [image-cves](<https://devfeed.tech/tags/image-cves.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [ml](<https://devfeed.tech/tags/ml.md>), [ml-and-cybersecurity](<https://devfeed.tech/tags/ml-and-cybersecurity.md>), [ml-software-supply-chain](<https://devfeed.tech/tags/ml-software-supply-chain.md>), [ml-software-supply-chain-security](<https://devfeed.tech/tags/ml-software-supply-chain-security.md>), [model-deployment](<https://devfeed.tech/tags/model-deployment.md>), [nemo](<https://devfeed.tech/tags/nemo.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [pytorch](<https://devfeed.tech/tags/pytorch.md>), [security](<https://devfeed.tech/tags/security.md>)

### AI overview

Chainguard announces early access to CUDA Optimized Images, designed to secure and simplify the deployment and management of NVIDIA accelerated AI applications in containers. The images target model deployment tampering, container vulnerabilities, large image sizes, driver and CUDA compatibility issues, dependency mismatches, and GPU debugging challenges.

### Source excerpt

Accelerate AI development with Chainguard's CUDA Optimized Images. Secure, streamlined NVIDIA deployments -- join our Early Access Program!

## Five Threat Model Diagrams for Machine Learning

DevFeed: [Five Threat Model Diagrams for Machine Learning](<https://devfeed.tech/articles/five-threat-model-diagrams-for-machine-learning-36796.md>)

Original publisher: [Read original article](<https://shostack.org/blog/five-threat-model-diagrams-for-ml/>)

Author: Adam

Published: 2023-04-13T00:00:00Z

Content type: opinion

Language: en

Sources: [Shostack & Friends Blog](<https://devfeed.tech/sources/shostack-friends-blog.md>)

Topics: [Machine Learning, Security Attacks](<https://devfeed.tech/topics/machine-learning-security-attacks.md>), [Machine Learning & Artificial Intelligence](<https://devfeed.tech/topics/machine-learning-artificial-intelligence.md>), [Training AI Models](<https://devfeed.tech/topics/training-ai-models.md>), [Data Quality](<https://devfeed.tech/topics/data-quality.md>), [data](<https://devfeed.tech/topics/data.md>)

Tags: [ai-and-cybersecurity](<https://devfeed.tech/tags/ai-and-cybersecurity.md>), [cybersecurity](<https://devfeed.tech/tags/cybersecurity.md>), [data-quality](<https://devfeed.tech/tags/data-quality.md>), [diagram](<https://devfeed.tech/tags/diagram.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [training-data](<https://devfeed.tech/tags/training-data.md>)

### AI overview

This article presents five threat-model diagrams for machine learning systems. The diagrams distinguish threats to and from ML systems, illustrate data flows and responses, and examine how training-data sources and system-design decisions can create risks. The author emphasizes that the diagrams are illustrative rather than complete and notes uncertainty about the model of how Twitter content reached Microsoft's Tay.

### Source excerpt

Some diagrams to help clarify machine learning threats