Python
CVE-2026-1777
HIGH
Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessObtain HMAC signing key from DescribeTrainingJob response
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DeliveryGain access to Training Jobs S3 output location
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ExploitUpload malicious artifacts to S3
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ExecutionTrigger next Training Job execution
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ImpactExecute arbitrary code
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A04:2025 - Cryptographic Failures
ASVS 5.0
V12 - Secure Communication Transport encryption
|
| Exploitation Conditions | Attacker requires high-privilege AWS IAM permissions to call DescribeTrainingJob API AND write permissions to the specific S3 bucket designated as Training Jobs output location. Amazon SageMaker Python SDK versions before v3.2.0 and v2.256.0 must be in use with ModelBuilder feature enabled. |
| Impact | CVSS 7.2 (HIGH). Attack vector: Network. Complexity: Low. Privileges required: High. User interaction: None. |
| Exploit ScenarioDerived | An attacker could exploit this vulnerability to compromise the affected system. |
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Alert meAnalysisAIv1 – Mar 12, 2026
Amazon SageMaker Python SDK versions before 3.2.0 and 2.256.0 expose the ModelBuilder HMAC signing key in cleartext API responses, allowing authenticated users with S3 bucket write access to inject malicious artifacts into training jobs that execute with elevated privileges. An attacker with dual permissions to call the DescribeTrainingJob API and modify the training output S3 location can achieve arbitrary code execution when the compromised job runs. No patch is currently available for this vulnerability.
Earlier versions of this analysis (1)
The Amazon SageMaker Python SDK before v3.2.0 and v2.256.0 includes the ModelBuilder HMAC signing key in the cleartext response elements of the DescribeTrainingJob function. [CVSS 7.2 HIGH]
RemediationAI
Monitor vendor advisories for a patch. Restrict network access to the affected service where possible.
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in pypi
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
Classified as CWE-319 (Cleartext Transmission of Sensitive Information). The Amazon SageMaker Python SDK before v3.2.0 and v2.256.0 includes the ModelBuilder HMAC signing key in the cleartext response elements of the DescribeTrainingJob function. A third party with permissions to both call this API and permissions to modify objects in the Training Jobs S3 output location may have the ability to upload arbitrary artifacts which are executed the next time the Training Job is invoked.
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Severity by source
AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H
Primary rating from NVD · only source for this CVE.
CVSS VectorNVD
Lifecycle Timeline
2DescriptionCVE.org
The Amazon SageMaker Python SDK before v3.2.0 and v2.256.0 includes the ModelBuilder HMAC signing key in the cleartext response elements of the DescribeTrainingJob function. A third party with permissions to both call this API and permissions to modify objects in the Training Jobs S3 output location may have the ability to upload arbitrary artifacts which are executed the next time the Training Job is invoked.
Executive ViewAI
Amazon SageMaker deployments using affected SDK versions are exposing sensitive ModelBuilder HMAC signing keys in plaintext through API responses, creating a critical authentication bypass risk. Organizations using SageMaker for model training and deployment need immediate assessment and remediation to prevent unauthorized access to machine learning pipelines and potential data exfiltration.
Implement restrictive IAM policies limiting DescribeTrainingJob API access to authorized users only; enable VPC endpoints for SageMaker API calls to prevent external API exposure; rotate ModelBuilder HMAC keys immediately and monitor for unauthorized usage patterns; consider disabling ModelBuilder feature until patch deployment if business operations allow; enable CloudTrail logging and set alerts for DescribeTrainingJob API invocations; implement network segmentation to limit lateral movement from compromised credentials.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
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GHSA-rjrp-m2jw-pv9c
NVD
CVE.org
EPSS
Exploit-DB