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Analyze » AWS Training & Certification » AMAAWS1770152164

Incident Score: Analysis & Impact (AMAAWS1770152164)

The details regarding individual company incidents & reports gives you full view from every side.

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-41
Company Score Before Incident808 / 1000
Company Score After Incident767 / 1000
Company LinkView AWS Training & Certification Profile
INCIDENT NUMBERAMAAWS1770152164
Type of Cyber IncidentBreach
ATTACK VECTORExposed credentials in public Amazon S3 buckets
DATA EXPOSEDTrue
INCIDENT DATE27/11/2025
STATUSAnalyzed

Key Highlights From The Incident Analysis

  • Timeline of AWS Training & Certification's Breach and lateral movement inside company's environment.
  • Overview of affected data sets, including SSNs and PHI, and why they materially increase incident severity.
  • How Rankiteo’s incident engine converts technical details into a normalized incident score.
  • How this cyber incident impacts AWS Training & Certification Rankiteo cyber scoring and cyber rating.
  • Rankiteo’s MITRE ATT&CK correlation analysis for this incident, with associated confidence level.

Full Incident Analysis Transcript

In this Rankiteo incident briefing, we review the AWS Training & Certification breach identified under incident ID AMAAWS1770152164.

The analysis begins with a detailed overview of AWS Training & Certification's information like the linkedin page: https://www.linkedin.com/company/aws-training-&-certification, the number of followers: 1449692, the industry type: IT Services and IT Consulting and the number of employees: None employees

After the initial compromise, the video explains how Rankiteo's incident engine converts technical details into a normalized incident score. The incident score before the incident was 808 and after the incident was 767 with a difference of -41 which is could be a good indicator of the severity and impact of the incident.

In the next step of the video, we will analyze in more details the incident and the impact it had on AWS Training & Certification and their customers.

On 28 November 2025, a cybersecurity incident called "AI-Powered Attack Breaches AWS Environment in Under 10 Minutes" came to light.

A threat actor exploited exposed credentials in public Amazon S3 buckets to gain initial access to an AWS environment, escalating privileges to administrative control in just eight minutes.

The disruption is felt across the environment, affecting AWS environment, Lambda functions, EC2 instances, Amazon Bedrock, and exposing True.

Formal response steps have not been shared publicly yet.

The case underscores how Analyzed, teams are taking away lessons such as AI-driven automation accelerates cyber intrusions, reducing defender response windows. Basic security lapses like exposed credentials remain a persistent risk. Runtime detection and least-privilege enforcement are critical in cloud environments, and recommending next steps like Avoid long-term IAM user credentials; use temporary roles. Monitor Lambda function modifications. Implement runtime detection and least-privilege access controls. Secure public S3 buckets and enforce strict credential hygiene.

Finally, we try to match the incident with the MITRE ATT&CK framework to see if there is any correlation between the incident and the MITRE ATT&CK framework.

The MITRE ATT&CK framework is a knowledge base of techniques and sub-techniques that are used to describe the tactics and procedures of cyber adversaries. It is a powerful tool for understanding the threat landscape and for developing effective defense strategies.

MITRE ATT&CK® Correlation Analysis

Rankiteo's analysis has identified several MITRE ATT&CK tactics and techniques associated with this incident, each with varying levels of confidence based on available evidence. Under the Initial Access tactic, the analysis identified Steal Application Access Token (T1528) with high confidence (90%), supported by evidence indicating exploited exposed credentials in public Amazon S3 buckets and Valid Accounts: Cloud Accounts (T1078.004) with high confidence (95%), supported by evidence indicating valid credentials left exposed in public S3 buckets. Under the Execution tactic, the analysis identified Serverless Execution (T1648) with high confidence (90%), supported by evidence indicating lambda function code injection to target admin user and Command and Scripting Interpreter (T1059) with moderate to high confidence (80%), supported by evidence indicating aI-assisted techniques to generate malicious code. Under the Privilege Escalation tactic, the analysis identified Abuse Elevation Control Mechanism: Bypass User Account Control (T1548.002) with moderate to high confidence (80%), supported by evidence indicating escalating privileges to administrative control in eight minutes and Valid Accounts: Cloud Accounts (T1078.004) with high confidence (90%), supported by evidence indicating targeted user frick with admin privileges. Under the Defense Evasion tactic, the analysis identified Use Alternate Authentication Material: Application Access Token (T1550.001) with moderate to high confidence (80%), supported by evidence indicating programmatic interaction with AWS Marketplace APIs and Valid Accounts: Cloud Accounts (T1078.004) with high confidence (90%), supported by evidence indicating cross-region inference profiles to distribute model invocations. Under the Credential Access tactic, the analysis identified Steal Application Access Token (T1528) with high confidence (90%), supported by evidence indicating exposed credentials in public S3 buckets and Unsecured Credentials: Credentials In Files (T1552.001) with high confidence (95%), supported by evidence indicating valid credentials left exposed in public S3 buckets. Under the Discovery tactic, the analysis identified Account Discovery: Cloud Account (T1087.004) with high confidence (90%), supported by evidence indicating enumerating account IDs to assume cross-account roles and Cloud Service Discovery (T1526) with moderate to high confidence (80%), supported by evidence indicating lateral movement across 19 AWS principals. Under the Lateral Movement tactic, the analysis identified Use Alternate Authentication Material: Application Access Token (T1550.001) with moderate to high confidence (80%), supported by evidence indicating lateral movement across 19 AWS principals and Valid Accounts: Cloud Accounts (T1078.004) with high confidence (90%), supported by evidence indicating attempts to assume cross-account roles. Under the Collection tactic, the analysis identified Data from Cloud Storage (T1530) with high confidence (90%), supported by evidence indicating exfiltration of cloud data. Under the Command and Control tactic, the analysis identified Web Service (T1102) with moderate to high confidence (70%), supported by evidence indicating programmatic interaction with AWS Marketplace APIs and Application Layer Protocol: Web Protocols (T1071.001) with moderate to high confidence (80%), supported by evidence indicating cross-region inference profiles for model invocations. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with high confidence (90%), supported by evidence indicating exfiltration of cloud data and Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), supported by evidence indicating abuse of Amazon Bedrock for data exfiltration. Under the Impact tactic, the analysis identified Resource Hijacking (T1496) with moderate to high confidence (80%), supported by evidence indicating provisioning GPU instances on EC2 for AI model development. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Sources & References