Loading story…
AWS is rolling out a simplified sign-up experience that lets customers use Google, GitHub, or Apple identities to create a preconfigured project with Free Tier credits and configurable monthly spending limits. The environment is implemented as a restricted three-account AWS Organization sandbox—comprising a user-facing member account plus hidden management and identity accounts—and can pause projects or apply controls that prevent new workload creation after a budget threshold is reached. AWS also automates service permissions through console workflows, coding agents, and IAM Role Manager, reducing the need to create IAM users, trust policies, or service permissions manually.
Security researchers found the sandbox is designed for onboarding and cost control rather than a complete security baseline. It does not enable CloudTrail and blocks GuardDuty, Security Hub, Detective, Inspector, Macie, and IAM Access Analyzer; it can also allow IAM access keys, public S3 buckets after protections are disabled, and EC2 instances using IMDSv1. Generated roles remain visible and modifiable, but may receive broad permissions such as PowerUserAccess where AWS cannot infer required access, requiring review and least-privilege refinement. Organizations needing centralized governance, multiple Regions, or full security-service coverage must enable advanced features and review inherited automated access rules and restrictive sandbox policies.
Map this exposure pattern across your cloud, code, and identities.
3 events from the most recent confirmed update back to the earliest known activity.
Wiz reported that the new AWS sign-up experience provisions a three-account AWS Organization with hidden management and identity accounts and applies SCPs and RCPs to the accessible member account. Its analysis found no configured CloudTrail, blocked access to several security services, and permitted potentially risky configurations such as IAM access keys, public S3 buckets after disabling blocking, and EC2 IMDSv1 after changing defaults.
AWS began a gradual rollout of a simplified onboarding model in which new customers can use Google, GitHub, or Apple identities and receive an automatically created project. The model provides Free Tier credits, configurable spending limits that pause projects when reached, email-based project sharing, and automatic permission configuration through supported workflows and coding agents.
AWS described IAM Role Manager, which can create and attach IAM roles from managed templates during supported service-console workflows. For user-written Lambda code, the feature may attach the broad PowerUserAccess policy and AWS recommends later least-privilege refinement using IAM Access Analyzer.
Vulnerabilities, threat actors, malware, products, organizations, and breaches Mallory has linked to this story.
See where this exposure pattern shows up across your cloud, code, supply chain, and non-human identities.
4 references tracked. Mallory keeps watching after this page renders.
wiz.io
Open sourcehelpnetsecurity.com
Open sourceaws.amazon.com
Open sourceaws.amazon.com
Open sourceMap indicators from this story to your assets and identify affected systems in minutes.
Every observed campaign, victim, and pivot linked to actors named in this story.
Malware, exploits, and IOCs connected to the activity described here.
YARA, Sigma, and Snort rules deployed to your SIEM as soon as they’re published.
Get matching new stories delivered to your team as they break — not the next morning.
Ask questions about this story and take action on the answers.
Other stories Mallory is tracking that overlap on entities, sources, or topic labels.
AWS announced a gradual rollout of a redesigned sign-in and sign-up experience that changes how some customers access AWS accounts. The update introduces a unified email entry point for **root users** and certain newly created accounts, refreshed session-selection pages, and support for signing in with supported identity providers for eligible accounts. AWS said existing customers will keep using their current credentials and sign-in methods, and the changes are being introduced to a limited set of users first. AWS said organizations using **IAM Identity Center** or federation should continue to use their existing organizational access portals or federation URLs, while customers authenticating with traditional **IAM users** and **root user** credentials should review the updated flow. The company also warned that teams relying on browser automation or scripted sign-in workflows may need to validate compatibility with the new interface as the rollout expands.
Aug 17, 2026
Amazon has introduced new security features and best practices for its Bedrock platform, focusing on both API key management and the protection of generative AI applications. The release of Amazon Bedrock API keys provides developers with new options for accessing the Bedrock API, but also introduces potential security risks if not managed properly. AWS recommends using temporary security credentials from AWS Security Token Service (STS) as the preferred authentication method, as these credentials are short-lived and reduce the risk of long-term exposure. In cases where API keys must be used, AWS advises choosing short-term API keys over long-term ones, as they have built-in expiration mechanisms that limit the window of vulnerability if a key is compromised. For scenarios requiring long-term API keys, such as with certain third-party software, AWS suggests implementing strict controls and monitoring to mitigate risks. Service control policies (SCPs) can be used to restrict the creation and use of API keys, further reducing the attack surface. In addition to credential management, AWS has launched Amazon Bedrock Guardrails, a suite of configurable safeguards designed to protect generative AI applications from sophisticated attacks, including encoding-based threats. These guardrails provide six key protections: content filters, denied topics, word filters, sensitive information filters, contextual grounding checks, and automated reasoning checks. Encoding-based attacks, where malicious actors encode harmful content to bypass detection, are a growing concern for organizations deploying generative AI. Bedrock Guardrails address this by implementing a defense-in-depth strategy that detects and blocks encoded threats, such as base64 or hexadecimal representations of forbidden words. The safeguards are designed to work across multiple foundation models, including those hosted outside of Amazon Bedrock, ensuring broad applicability. AWS provides detailed guidance on implementing these protections, emphasizing the importance of balancing robust security with usability to avoid friction for legitimate users. Monitoring and auditing of API key usage, as well as regular review of guardrail configurations, are recommended to maintain a strong security posture. The combination of secure API key management and advanced guardrails positions Amazon Bedrock as a platform capable of supporting secure, scalable, and responsible generative AI deployments. Organizations are encouraged to adopt these best practices to protect sensitive data and maintain compliance with internal and external security standards. By leveraging these new features, enterprises can mitigate the risks associated with both credential exposure and advanced AI-specific attack vectors. The comprehensive approach outlined by AWS reflects the evolving threat landscape and the need for proactive, layered defenses in modern cloud environments. Security teams should stay informed about updates to Bedrock's security capabilities and continuously adapt their strategies to address emerging threats. The integration of these controls into development and operational workflows is essential for safeguarding AI-driven applications and maintaining trust in automated systems.
Jun 29, 2026
AWS published a reference architecture for **Amazon Bedrock AgentCore** that limits AI agents to the requesting user’s permissions by propagating end-user authorization context to downstream services instead of enforcing access control in agent code. In the design, users authenticate through **Amazon Cognito**, custom claims such as department are added to JWTs, and **AgentCore Runtime** validates those claims before the agent runs. AWS said this approach reduces the risk of unauthorized data exposure from prompt injection or application bugs because the agent acts as an orchestrator rather than a trusted gatekeeper. The architecture demonstrates three enforcement patterns across common enterprise data sources: user-scoped temporary AWS credentials for **Amazon DynamoDB** using `STS AssumeRoleWithWebIdentity` and session tags, metadata-based filtering for **Amazon Bedrock Knowledge Bases**, and OAuth 2.0 on-behalf-of token exchange for **Salesforce** through AgentCore Identity. In the example CRM workflow, Sales and Finance employees can use the same agent while only receiving records allowed by their own roles, with AWS also recommending stronger isolation such as separate knowledge bases and IAM policies where stricter separation is required.
Aug 20, 2026