
1. Emergence of AI-Accelerated Cloud Attacks
Recent cloud attacks demonstrate that threat actors are leveraging artificial intelligence tools to dramatically speed up their breach campaigns. According to research by the Sysdig Threat Research Team, attackers were able to go from initial access to full administrative control of an AWS environment in under 10 minutes by using large language models (LLMs) to automate key steps of the attack lifecycle. (Cyber Security News)
2. Initial Access: Credentials Exposed in Public Buckets
The intrusion began with trivial credential exposure: threat actors located valid AWS credentials stored in a public AWS S3 bucket containing Retrieval-Augmented Generation (RAG) data. These credentials belonged to an AWS IAM user with read/write permissions on some Lambda functions and limited Amazon Bedrock access.
3. Rapid Reconnaissance with AI Assistance
Using the stolen credentials, the attackers conducted automated reconnaissance across 10+ AWS services (including CloudWatch, RDS, EC2, ECS, Systems Manager, and Secrets Manager). The AI helped generate malicious code and guide the attack logic, illustrating how LLMs can drastically compress the reconnaissance phase that previously took hours or days.
4. Privilege Escalation via Lambda Function Compromise
With enumeration complete, the attackers abused UpdateFunctionCode and UpdateFunctionConfiguration permissions on an existing Lambda function called “EC2-init” to inject malicious code. After just a few attempts, this granted them full administrative privileges by creating new access keys for an admin user.
5. AI Hallucinations and Behavioral Artifacts
Interestingly, the malicious scripts contained hallucinated content typical of AI generation, such as references to nonexistent AWS account IDs and GitHub repositories, plus comments in other languages like Serbian (“Kreiraj admin access key”—“Create admin access key”). These artifacts suggest the attackers used LLMs for real-time generation and decisioning.
6. Persistence and Lateral Movement Post-Escalation
Once administrative access was achieved, attackers set up a backdoor administrative user with full AdministratorAccess and executed additional steps to maintain persistence. They also provisioned high-cost EC2 GPU instances with open JupyterLab servers, effectively establishing remote access independent of AWS credentials.
7. Indicators of Compromise and Defensive Advice
The article highlights phishing indicators like rotating IP addresses and multiple IAM principals involved. It concludes with best-practice recommendations, including enforcing least-privilege IAM policies, restricting sensitive Lambda permissions (especially UpdateFunctionConfiguration and PassRole), disabling public access to sensitive S3 buckets, and enabling comprehensive logging (e.g., for Bedrock model invocation).
My Perspective: Risk & Mitigation
Risk Assessment
This incident underscores a stark reality in modern cloud security: AI doesn’t just empower defenders — it empowers attackers. The speed at which an adversary can go from initial access to full compromise is collapsing, meaning legacy detection windows (hours to days) are no longer sufficient. Public exposure of credentials — even with limited permissions — remains one of the most critical enablers of privilege escalation in cloud environments today.
Beyond credential leaks, the attack chain illustrates how misconfigured IAM permissions and overly broad function privileges give attackers multiple opportunities to escalate. This is consistent with broader cloud security research showing privilege abuse paths through policies like iam:PassRole or functions that allow arbitrary code updates.
AI’s involvement also highlights an emerging risk: attackers can generate and adapt exploit code on the fly, bypassing traditional static defenses and making manual incident response too slow to keep up.
Mitigation Strategies
Preventative Measures
- Eliminate Public Exposure of Secrets: Use automated tools to scan for exposed credentials before they ever hit public S3 buckets or code repositories.
- Least Privilege IAM Enforcement: Restrict IAM roles to only the permissions absolutely required, leveraging access reviews and tools like IAM Access Analyzer.
- Minimize Sensitive Permissions: Remove or tightly guard permissions like
UpdateFunctionCode,UpdateFunctionConfiguration, andiam:PassRoleacross your environment. - Immutable Deployment Practices: Protect Lambda and container deployments via code signing, versioning, and approval gates to reduce the impact of unauthorized function modifications.
Detective Controls
- Comprehensive Logging: Enable CloudTrail, Lambda function invocation logs, and model invocation logging where applicable to detect unusual patterns.
- Anomaly Detection: Deploy behavioral analytics that can flag rapid cross-service access or unusual privilege escalation attempts in real time.
- Segmentation & Zero Trust: Implement network and identity segmentation to limit lateral movement even after credential compromise.
Responsive Measures
- Incident Playbooks for AI-augmented Attacks: Develop and rehearse response plans that assume compromise within minutes.
- Automated Containment: Use automated workflows to immediately rotate credentials, revoke risky policies, and isolate suspicious principals.
By combining prevention, detection, and rapid response, organizations can significantly reduce the likelihood that an initial breach — especially one accelerated by AI — escalates into full administrative control of cloud environments.

InfoSec services | InfoSec books | Follow our blog | DISC llc is listed on The vCISO Directory | ISO 27k Chat bot | Comprehensive vCISO Services | ISMS Services | AIMS Services | Security Risk Assessment Services | Mergers and Acquisition Security
At DISC InfoSec, we help organizations navigate this landscape by aligning AI risk management, governance, security, and compliance into a single, practical roadmap. Whether you are experimenting with AI or deploying it at scale, we help you choose and operationalize the right frameworks to reduce risk and build trust. Learn more at DISC InfoSec.
- AI-Powered Cloud Attacks: How Attackers Can Gain AWS Admin Access in Minutes—and How to Stop Them
- The Invisible Workforce: How Unmonitored AI Agents Are Becoming the Next Major Enterprise Security Risk
- The AI-Native Consulting Shift: Why Architects Will Replace Traditional Experts
- The New Frontier of AI-Driven Cybersecurity Risk
- AutoPentestX: Automating End-to-End Penetration Testing for Modern Security Teams
























