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Push Security Launches New Browser Controls to Prevent Sensitive Data and Secrets Leaking Into Unsanctioned AI ToolsPush Security, the most powerful AI-native security tool in the browser, today launched a new set of browser-layer controls designed to prevent security incidents caused by sensitive data leaving the browser. The new capabilities include file upload and download telemetry, with configurable monitor, warn, and block modes; visibility and control over clipboard actions; and automated app and domain categorization. Together these features give security teams real-time visibility and enforcement when intellectual property, source code, customer records, and other sensitive data move to unsanctioned AI tools, personal cloud accounts, and other high-risk destinations. "The most common form of sensitive data exposure in the modern enterprise isn't a stolen laptop or misconfigured storage containers in the cloud," said Jacques Louw, chief research officer at Push Security. "Too often it's an engineer integrating an unsanctioned AI assistant with systems that contain source code and secrets, or a customer service agent dragging an exported customer list into a third-party AI tool. "Each is a security incident in the making, yet none would generate a useful signal in endpoint DLP, CASB, or secure web gateway tooling, because the activity is happening entirely inside the browser session," Louw added.
The scale of the exposure is significant
"The first wave of AI risk was abstract - boards asking CISOs whether employees were using ChatGPT," said Adam Bateman, CEO of Push Security. "This new wave is more concrete. Sensitive data is flowing into AI tools through personal accounts with weak passwords, that often have no MFA, and little to no security oversight. This means they are one phishing attack away from compromise, and that's a security problem, not a governance problem."
New Push browser controls
Investigation telemetry, not just policy alerts
Push collects telemetry for permitted events too, not just the ones that triggered a block, and forwards it as structured, context-enriched data to Microsoft Sentinel, Splunk Cloud, Datadog, Panther, Cribl Cloud, or any SIEM reachable by webhook. "When a developer uploads a production dataset for testing, or a manager uploads a performance report, the security incident is happening inside the browser tab," said Louw. "Network tools see the destination. Endpoint tools see disk writes. Neither sees what was typed, uploaded, or pasted in the session."
Complementing the security stack you already have
Category-level controls give security teams a durable policy surface. Block, warn, or monitor responses can be applied to entire categories of apps and domains scoped by user groups, letting engineers use approved generative AI tools while restricting access for other populations, without managing per-URL rules. These capabilities also run on Push's existing privacy-preserving architecture. Personal browsing is not monitored by default, plaintext credentials are never collected, and sensitive clipboard data can be redacted.
AI visibility and control is a feature, not a separate investment
A standalone AI governance tool monitors the AI apps you already know about and tells you whether someone violated a usage policy. But it has no visibility into the unsanctioned tools, personal accounts, and shadow identities where the actual risk concentrates, and it cannot tell you which identity was used, whether that account has MFA, or whether the data just landed in an account the security team has no ability to protect. That is the gap a browser security platform closes. "AI visibility and control is a feature of the right browser security platform, not a separate solution," said Bateman. "The activity is already happening in the browser. The telemetry to see it, and the controls to act on it, belong there too."
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About Push Security
View source version on businesswire.com: https://www.businesswire.com/news/home/20260602072519/en/ |

