The Acceptance Gap: Why AI-Generated Code Still Fails to Become Shipped Work
Learn why AI generated code often stalls before production and how earlier verification can improve acceptance, quality, and engineering ROI.
7 stories
Learn why AI generated code often stalls before production and how earlier verification can improve acceptance, quality, and engineering ROI.
Learn what Skyscanner's AI rollout reveals about independent verification, deterministic checks, and safer workflows for AI-generated code.
For most software teams, security is a race against a clock. The median time from vulnerability disclosure to weaponization has collapsed from 840 days to 1.6 days, and 80% of exploitations now occur on or before the day of disclosure. That’s bad.
Black Hat USA 2026 didn’t introduce the AI security problem, but made it clear how fast that problem is becoming operational. An independent study initiated and funded by Checkmarx helps explain why.
Now available in Early Access for SAST within Checkmarx One, Checkmarx Fusion adds a new detection layer that advances vulnerability-finding accuracy beyond what rules-based scanning or an AI model can achieve alone.
Checkmarx One for Government (CxG) has officially achieved FedRAMP Certified status at the Moderate Impact Level.
Modern applications don’t just run on code anymore. They run on models, agents, embeddings, datasets, and autonomous tools like MCP servers. Developers are pulling pre-trained LLMs from Hugging Face, integrating open-source agent frameworks, and wiring up AI pipelines faster than security teams can…
Showing 7 of 7 stories
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