"As software application development teams now start to embrace an increasing number of automation tools to provide AI-driven (or at least AI-assisted) coding functions in their codebases, a Newtonian equal and opposite reaction is also surfacing in the shape of governance controls and guardrails to keep AI injections in check as these technologies now surface in the software supply chain."
"Unlike legacy DLP, Nightfall's classifiers are explainable and adaptable. Each detection includes confidence scoring and justification metadata, so teams understand why a file was flagged and can fine-tune policies to balance protection with productivity," said Rohan Sathe, CEO and co-founder of Nightfall. "With prebuilt protection for common document types and custom detectors for unique business assets, organisations gain both immediate value and long-term flexibility in a single platform that works across SaaS apps, endpoints and communication channels."
Software teams increasingly adopt AI-driven and AI-assisted coding tools, prompting parallel development of governance controls and guardrails to manage AI in the software supply chain. Tools now automate detection and inventorying of internal AI models and external API gateways used to access approved or ad-hoc third-party data. Data Loss Prevention platforms target leaks of sensitive repositories and PII into unauthorised “shadow AI” tools via prompts, uploads and copy/paste. Explainable classifiers with confidence scoring and justification metadata enable policy tuning. Platforms offer prebuilt protections and custom detectors across SaaS, endpoints and communication channels, while network security services add visibility into generative AI use.
Read at Techzine Global
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