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Threat actors can take advantage of Amazon Web Services Security Token Service (AWS STS) as a way to infiltrate cloud accounts and conduct follow-on attacks. The service enables threat actors to impersonate user identities and roles in cloud environments, Red Canary researchers Thomas Gardner and Cody Betsworth  said  in a Tuesday analysis. AWS STS is a  web service  that enables users to request temporary, limited-privilege credentials for users to access AWS resources without needing to create an AWS identity. These STS tokens can be valid  anywhere from 15 minutes to 36 hours . Threat actors can steal long-term IAM tokens through a variety of methods like malware infections, publicly exposed credentials, and phishing emails, subsequently using them to determine roles and privileges associated with those tokens via API calls. "Depending on the token's permission level, adversaries may also be able to use it to create additional IAM users with long-term A...

In today's digital landscape, around  60%  of corporate data now resides in the cloud, with Amazon S3 standing as the backbone of data storage for many major corporations.  Despite S3 being a secure service from a reputable provider, its pivotal role in handling vast amounts of sensitive data (customer personal information, financial data, intellectual property, etc.), provides a juicy target for threat actors. It remains susceptible to ransomware attacks which are often initiated using leaked access keys that have accidentally been exposed by human error and have access to the organization's buckets. To effectively combat these evolving threats, it is vital to ensure that your organization has visibility into your S3 environment, that you are aware of how threat actors can compromise data for ransom and most importantly, best practices for minimizing the risk of cyber criminals successfully executing such an attack. Ensuring Visibility: CloudTrail and Server Access L...

In recent years, artificial intelligence (AI) has begun revolutionizing Identity Access Management (IAM), reshaping how cybersecurity is approached in this crucial field. Leveraging AI in IAM is about tapping into its analytical capabilities to monitor access patterns and identify anomalies that could signal a potential security breach. The focus has expanded beyond merely managing human identities — now, autonomous systems, APIs, and connected devices also fall within the realm of AI-driven IAM, creating a dynamic security ecosystem that adapts and evolves in response to sophisticated cyber threats. The Role of AI and Machine Learning in IAM AI and machine learning (ML) are creating a more robust, proactive IAM system that continuously learns from the environment to enhance security. Let's explore how AI impacts key IAM components: Intelligent Monitoring and Anomaly Detection AI enables continuous monitoring of both human and non-human identities , including APIs, service acc...