Google Workspace is a popular productivity suite, and its broad collection of apps (such as Gmail, Drive, Calendar, and Docs) can give attackers a central point of entry for accessing sensitive and valuable data if they compromise an account. Learning how to identify malicious activity in your Workspace environment enables you to stop threats before they become more serious. In this post, we’ll look at a few ways attackers gain access to and take advantage of Google Workspace.

A primary goal for security teams is identifying specific threats to their environment, but they often face the daunting task of reviewing vast amounts of log data and alerts. Even with well-crafted detection rules, sifting through irrelevant data to pinpoint essential details for an investigation can be a significant challenge. This not only prolongs investigation times but also increases the risk of overlooking critical information.

Confluent Cloud is a Kafka–as-a-service solution that simplifies the deployment, scaling, and operation of Kafka clusters. A popular feature is its Apache Kafka connectors, which make it easy to connect your Kafka clusters to any of 120+ third-party streaming data sources and destinations.

The use of version control systems, continuous integration (CI), container services, and other tools in software development have enabled developers to ship code more quickly and efficiently. However, as organizations expand their build and packaging ecosystems, they also increase the number of entry points for malicious code injections that can ultimately make their way to production environments.

According to our most recent cloud security report, most cloud security incidents are the result of compromised credentials for either human or non-human identities. Once an attacker successfully controls an identity, such as a highly privileged user account, they can quickly move to other areas of an environment, including prevalent targets like sensitive data stores. This pattern of behavior is similar across all cloud platforms and services.

AWS Identity and Access Management (IAM) enables organizations to set up permissions policies for users and workloads that need access to cloud services and resources. But as your cloud environment scales, it can be challenging to create and audit IAM policies that work effectively without compromising security.

As developers increasingly adopt chain-based and agentic LLM application architectures, the threat of critical sensitive data exposures grows. LLMs are often highly privileged within their applications and related infrastructure, with access to critical data and resources, making them an alluring target for exploitation at the client side by attackers. In particular, LLM applications can be compromised to expose sensitive data via prompt injection attacks.

When engineering teams move their workloads to the cloud, it’s often possible that sensitive data—such as credit card numbers, login credentials, and personally identifiable information (PII)—unintentionally moves to the cloud with them. To secure this data, avoid costly breaches, and meet GRC requirements, these teams often catalog where this data is stored and establish the right controls to limit access.

Cisco Umbrella is a platform for monitoring and maintaining the DNS-layer security across your network. It monitors network activity and detects behavior like DNS hijacking, spoofing, and other attacks. It can then reroute or block potentially malicious requests before they reach endpoints. However, while Umbrella’s DNS-layer security blocks malicious domains, the sheer volume of DNS and proxy logs it generates can overwhelm security teams.