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.

Many organizations lack clear visibility into the efficiency of their security processes, making it difficult to accurately assess their security teams’ performance. Without insight into key factors like alert response speed, investigation thoroughness, and the accuracy of detection rules, teams risk operating without a clear view. This can lead to missed threats, inefficient use of resources, and an inability to improve security outcomes.

Due to their numerous components and dependencies, web applications often have multiple vulnerabilities—many of them unknown and susceptible to zero-day attacks—that can be exploited by malicious HTTP requests. Determining whether a vulnerability exists is challenging without visibility into an application’s real-time data and event flows, which isn’t possible with existing firewall-based solutions.

Compromised secrets, such as leaked API and SSH keys, credentials, and session tokens, are the leading cause of cloud security incidents. While attackers can directly compromise secrets through methods like phishing, they can also gain control by finding and taking advantage of simple misconfigurations in your environment.

There are several tactics that threat actors can use to access cloud environments, services, and data. A common example is lateral movement, which involves techniques that enable a threat actor to pivot from one host to the next within an environment. This type of activity often uses other tactics, such as initial access and privilege escalation, as part of a larger attack flow.

Windows event logs are a key source of important information about your Windows environments, including detailed records of user activities, system performance, and potential security issues. However, with the sheer volume of logs modern environments generate, it can be overwhelming for security teams to efficiently detect, triage, and respond to threats in real time.