今日已更新 133 条资讯 | 累计 37382 条内容
关于我们

标签:#app

找到 1024 篇相关文章

AI 资讯

How to Measure Time to Revoke for Exposed Credentials

This is a follow-up to an article we published in The Hacker News introducing time to revoke as a critical CISO metric. This version provides a practical guide for measuring it across exposed secrets and non-human identities. 👉 TL;DR: Time to revoke is a security metric that measures how long an exposed credential remains usable after it has been confirmed valid. Measuring it requires teams to record when a credential is validated and when its invalidation is confirmed. From that baseline, CISOs can track median and P90 time to revoke, the percentage of exposed secrets revoked within SLA, owner coverage, the percentage that remain valid after detection, and the incidents that require manual escalation. Detection is not the same as credential revocation Detection tells you when a credential was found. A remediation ticket tells you when work was assigned or closed. Neither tells you whether the exposed access was fully neutralized. For leaked credentials, "Did we find it?" is the first question. "How long did it remain valid?" is just as important, if not more so. If a leaked API key, cloud credential, service account token, OAuth secret, private key, or database connection string is still valid, it is a point of ingress. Until it is revoked, rotated, or otherwise invalidated, it remains a path an attacker can use. Credential rotation only counts when the exposed credential is disabled, expired, or otherwise rendered unusable. That makes time to revoke a critical CISO metric. It connects detection to business risk by measuring the exposure window security teams need to close. What is time to revoke in secrets remediation? Time to revoke measures how long an exposed credential remains usable after it has been confirmed valid. Time to revoke = confirmed invalidation timestamp − validation timestamp The clock starts when the organization verifies that the credential works and stops when it confirms that the credential can no longer be used. Closing a ticket, deleting a

2026-08-26 原文 →
AI 资讯

Your App Works. But Is It Actually Solving Your Users’ Problems?

A technically perfect app can still fail. It can have clean code, modern architecture, powerful APIs, and impressive features—and still leave users uninstalling it, abandoning transactions, or switching to a competitor. Because users don't experience your code.They experience the product. That is why developers and businesses need to look beyond functionality and ask a more important question: “Does this software make the user’s life easier?” The Real Cost of a Poor Digital Experience Customer expectations are rising quickly. According to PwC’s 2025 Customer Experience Survey, 70% of executives say customer expectations are evolving faster than their companies can adapt. Even more importantly, 29% of consumers said they stopped using or buying from a brand because of poor customer experience. That means a frustrating digital experience isn't simply a UX problem. It can become a business problem . A confusing checkout flow, slow screen, unnecessary registration step, broken search function, or poorly designed notification can turn a potential customer into a lost customer. And users rarely tell you exactly what went wrong. They simply leave. More Features Don't Always Mean More Value One of the biggest mistakes in software development is assuming that adding more features automatically makes a product better. It doesn't. Imagine an app with: 30+ features AI integration Multiple dashboards Complex personalization Advanced analytics …but users struggle to complete the one task they downloaded the app for. That's not innovation. That's friction. A better development approach starts with identifying the core user problem and then building around it. Before adding a feature, ask: What problem does this solve? If the answer isn't clear, the feature may not belong in the product. Performance Is Part of User Experience Developers often separate performance from UX. Users don't. To them, a slow API, delayed screen, frozen button, or failed transaction is simply a bad experien

2026-08-26 原文 →
AI 资讯

AI models flub these intelligence tests. Can you fare any better?

Puzzles and games have been central to AI development since the very beginning. Just as we humans like to test our smarts with crosswords or logic puzzles, developers can test how far models have advanced with a gaming gauntlet. The term “machine learning” was popularized in a 1959 article by the IBM computer scientist Arthur…

2026-08-26 原文 →
AI 资讯

Raised on AI

When my oldest child was born, I immediately set up Gmail and Twitter accounts in her name. I broadly announced her birth online and proceeded to plaster her photo across all sorts of platforms. In short, I began creating her digital footprint long before she could stand on her own two feet. Fast-forward a couple…

2026-08-26 原文 →