Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

This is the second in a series of articles about cloud-based attack vectors. Check out our last article about admin takeovers! Inside the Cloud: Attacks & Prevention – Administrative Account Compromise Ransomware has long been associated with takeovers of endpoints. However, attackers are evolving to target cloud environments – and the effects can be devastating.

Consider the case of a malicious actor attempting to inject, scrape, harvest, or exfiltrate data via an API. Such malicious activities are often characterized by the particular order in which the actor initiates requests to API endpoints. Moreover, the malicious activity is often not readily detectable using volumetric techniques alone, because the actor may intentionally execute API requests slowly, in an attempt to thwart volumetric abuse protection.

AI guardrails are vital for ensuring the safe and responsible use of AI/large language models (LLMs). However, focusing solely on single prompt-level checks can leave organizations vulnerable to sophisticated threats. Many company policy violations and security risks can be cleverly split across multiple, seemingly innocent queries. To effectively protect against these threats, a more comprehensive approach is needed — session-level monitoring.

As businesses increasingly adopt Generative AI (Gen AI) to enhance operations, customer engagement, and innovation, the need for robust AI guardrails has never been more critical. While Gen AI offers transformative potential, it also introduces significant risks that can jeopardize your business if not properly managed. Below, we explore five critical risks associated with Gen AI and provide strategies to avoid them.

As organizations increasingly integrate artificial intelligence (AI) into their operations, the nature of data security is undergoing significant transformation. With AI’s ability to process vast amounts of data quickly, the risk of data breaches and leaks has grown exponentially. In this context, Data Loss Prevention (DLP) has (re)emerged as a critical component for IT professionals seeking to safeguard sensitive information.

GitHub Copilot and other AI coding tools have transformed how we write code and promise a leap in developer productivity. But they also introduce new security risks. If your codebase has existing security issues, AI-generated code can replicate and amplify these vulnerabilities.

Today, we’re excited to expand our recent Unified Risk Posture announcement with more information on our latest integrations with CrowdStrike. We previously shared that our CrowdStrike Falcon Next-Gen SIEM integration allows for deeper analysis and further investigations by unifying first- and third-party data, native threat intelligence, AI, and workflow automation to allow your security teams to focus on work that matters.

We’re excited to share some big news: 1Password Extended Access Management is now available on AWS Marketplace through private offers. Now it’s easier than ever to keep organizations secure while taking advantage of the AWS ecosystem.