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Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection

Unit 42 clusters behavior of 40,000+ AWS identities from 125 cloud environments to map functional roles and enable lightweight SQL-based detection.

Palo Alto Unit 42 built an unsupervised behavioral clustering model using UMAP and HDBSCAN on AWS CloudTrail logs to map cloud identities to functional roles such as administrators, backup services, security tooling and DevOps. The study analyzed over 40,000 identities across 125 cloud environments over two months. The researchers show that heuristics extracted from the clustering map can be implemented in standard SQL, enabling role classification at scale without running a continuous ML pipeline. The methodology extends to audit logs from other cloud providers, SaaS and Kubernetes.

Palo Alto Unit 42 · 3d agoResearch

Attack Paths Into VMs in the Cloud

Unit 42 maps attack paths into AWS, Azure, and GCP VMs through intended features like startup scripts and SSH key pushes.

Palo Alto Unit 42 reviewed attack vectors against virtual machine services on AWS, Azure, and GCP, finding that 11% of internet-exposed cloud hosts carry Critical or High severity vulnerabilities. The attack paths rely on legitimate features such as EC2 User Data, VM custom data, EC2 Instance Connect, SSM Run Command, and serial consoles rather than vulnerabilities, and exploiting them requires attackers to first obtain control plane permissions. A compromised VM exposes not only its data but the workload identity and cloud permissions assigned to it, making identity compromise potentially more damaging than data theft. The firm places mitigation responsibility on cloud users and administrators.

Palo Alto Unit 42 · Aug 17, 2026Research1

Weak IAM affects up to 98% of cloud environments

Intruder's 2026 Cloud Security Index finds weak IAM controls affect up to 98% of cloud environments across AWS, Azure, and Google Cloud.

Intruder's 2026 Cloud Security Index report analyzed cloud misconfigurations across midmarket and enterprise environments, finding weak IAM controls and missing logging affected 80% to 98% of accounts across all three major providers. AWS recorded the highest prevalence in five of six categories, including exposed services at 76% versus 8% on Google Cloud. IAM weaknesses worsen with scale, affecting 87% of SMEs, 95% of midmarket organizations, and 98% of large enterprises, while remediation times peak at 35 days for organizations with 1,000 to 5,000 employees.

Help Net Security · Aug 14, 2026Research

Your Cloud Security Checklist Doesn't Work the Way You Think It Does

Intruder's 2026 Cloud Security Index found misconfiguration risk profiles differ sharply across AWS, Azure, and Google Cloud across 3,000 organizations.

Intruder analyzed misconfiguration data from 3,000 organizations across AWS, Azure, and Google Cloud for its 2026 Cloud Security Index. Weak IAM controls and missing logging affected 80-98% of accounts regardless of provider, while exposed services ranged from 76% on AWS to just 8% on Google Cloud. Top issues included S3 buckets without HTTPS enforcement (87% of AWS accounts), Entra ID users without MFA (55% of Azure accounts), and missing OS Login MFA (77% of Google Cloud accounts). Weak IAM prevalence rose with organization size, from 87% at SMEs to 98% at large enterprises, and midmarket organizations took the longest to remediate at 35 days on average.

The Hacker News · 9d agoResearch

The Year in Web Threats: Web Skimmers Take Advantage of Cloud Hosting and More

Unit 42 analyzed 2.24 million web threat incidents, finding web skimmers increasingly hosted on cloud infrastructure to steal payment card data.

Palo Alto Unit 42 analyzed 2,241,354 web threat incidents and 831,550 unique URLs detected via Advanced URL Filtering between October 2020 and September 2021. Threat activity peaked from October 2020 to January 2021, coinciding with the holiday shopping season, with most malicious domains geolocated to the United States, Russia, and Germany. Web skimmers ranked third among the top five threat classes and showed the most code diversity, making detection harder. Researchers observed more web skimmer families being hosted on cloud platforms to steal payment data and PII.

Palo Alto Unit 42 · Aug 17, 2026Research

From Hypervisor to Container: Cloud Security Vulnerabilities, Defense Mechanisms, and Open Challenges

Survey of 120+ cloud security papers (2008-2025) reviews hypervisor and container isolation attacks, scoring defenses with the ADPO framework and CIA impact scale.

This survey reviews over 120 security publications from 2008 to 2025 on breaches of cloud isolation boundaries via virtual machines and containers. Threats examined include VM escape, VM hopping, CPU cache side-channels, container breakouts, vulnerable container images, and DDoS attacks. The authors introduce ADPO, a 0-3 scoring framework rating defenses on accuracy, deployment ease, performance impact, and operational overhead, plus a 1-5 CIA severity mapping for attack impact.

arXiv cs.CR · 2d agoResearch

Apple Reference Image: A New Approach for Verified Photography

Apple introduces Reference Image, hardware-backed verifiable photography on iPhone 18 Pro using sensor signing and Private Cloud Compute to counter AI-generated fakes.

Apple announced Reference Image, an opt-in camera mode debuting on the main sensor of iPhone 18 Pro and iPhone 18 Pro Max that produces securely timestamped, verifiable photographs. The design splits into two phases: a secure digital negative created by cryptographically signing pixel data at the sensor immediately after capture (preventing injection or tampering), then developing that negative into a reference image. Private Cloud Compute handles processing without exposing image contents to anyone, including Apple, and fraudulent reference images can be revoked without revealing the photographer's identity. Apple positions the system as stronger than C2PA-based approaches, which sign metadata after capture, are vulnerable to editing-chain compromise, and can tie images to a device or individual.

Mapping out your unknown: A threat hunter’s guide to GitHub

Datadog Security Labs publishes a threat-hunting guide with audit-log queries to detect GitHub token theft, device code phishing, and source code exfiltration.

Datadog's threat-hunting guide covers GitHub audit log queries for detecting compromised accounts, stolen personal access tokens, and malicious OAuth app authorizations. Attackers typically obtain credentials through phishing, credential stuffing, leaked secrets, or device code phishing, then map private repositories, exfiltrate source code, and pivot into connected cloud and CI/CD environments. The guide maps detections to MITRE techniques like T1078 and T1528 and documents GitHub logging quirks affecting attribution, token metadata, and visibility fields.

Datadog Security Labs · 1d agoResearch in the wild1