CVE-2025-0508

Executive Summary

CVE-2025-0508 is a medium-severity vulnerability in the AWS SageMaker Python SDK, specifically within the SageMaker Workflow component. The flaw arises from the use of MD5 hashing to identify and deduplicate workflow configurations. Due to the well-known collision resistance weakness of MD5, an attacker can craft two different workflow configurations that produce the same MD5 hash. This can cause the SageMaker pipeline to incorrectly reuse cached results from a different configuration, leading to integrity violations and erroneous processing outcomes. The vulnerability affects all versions of the SDK, and no official patch has been released at the time of analysis. The EPSS score is 0.0%, indicating low exploitation likelihood in the wild, but the risk to pipeline integrity is significant for organizations relying on SageMaker for ML workflows.

Supply Chain & Package Security

This vulnerability resides in the aws/sagemaker-python-sdk package, which is distributed via PyPI. Organizations using this SDK in their CI/CD or ML pipelines should treat this as a supply chain risk. The lack of a patch means that any version of the package is potentially vulnerable. Teams must implement compensating controls, such as input validation and workflow integrity checks, until an official fix is released.

CVSS Breakdown & Threat Level

• CVSS Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:L
• Base Score: 5.9 (Medium)
• Attack Vector: Network
• Attack Complexity: Low
• Privileges Required: None
• User Interaction: None
• Scope: Unchanged
• Confidentiality Impact: None
• Integrity Impact: Low
• Availability Impact: Low

The threat level is medium due to the low complexity and network-based attack vector, but the impact is limited to integrity and availability of pipeline results, not direct data breach.

Deep Dive & Mechanics

The SageMaker Workflow component uses MD5 hashing to generate unique identifiers for workflow configurations. When a workflow is executed, the SDK computes an MD5 hash of the configuration parameters and uses it to check if a previous run with the same hash exists. If a match is found, the SDK reuses the cached results instead of re-executing the workflow.

The vulnerability exploits the fact that MD5 is cryptographically broken and collision attacks are practical. An attacker can craft two different workflow configurations (e.g., different hyperparameters, data sources, or processing steps) that produce the same MD5 hash. When the second configuration is submitted, the SDK incorrectly identifies it as a duplicate and returns the results from the first configuration. This leads to:

• Integrity violation: The pipeline produces results that do not correspond to the intended configuration.
• Erroneous processing: Downstream systems may act on incorrect outputs, leading to flawed ML models or business decisions.

The attack does not require authentication if the workflow submission endpoint is exposed, but in practice, AWS IAM controls may limit exposure.

Vulnerable vs. Patched Code

Since no patch is available, we compare the vulnerable approach with a recommended secure alternative.

Vulnerable Code (MD5-based deduplication):

import hashlib
import json

def get_workflow_id(config):
    config_str = json.dumps(config, sort_keys=True)
    return hashlib.md5(config_str.encode()).hexdigest()

Patched Code (SHA-256 based deduplication):

import hashlib
import json

def get_workflow_id(config):
    config_str = json.dumps(config, sort_keys=True)
    return hashlib.sha256(config_str.encode()).hexdigest()

The patched version uses SHA-256, which is collision-resistant and currently considered secure for this purpose. Additionally, a salt or nonce should be included to prevent precomputation attacks.

Exploitation & Lab Setup

Red Team

Objective: Exploit MD5 collision to replace a legitimate workflow with a malicious one.

Prerequisites:

• Access to the SageMaker SDK (e.g., via AWS credentials or a compromised CI/CD pipeline).
• Ability to submit workflow configurations.

Steps:

1. Identify a target workflow configuration config_A that produces a known MD5 hash.
2. Use a collision generation tool (e.g., md5collision or hashclash) to create a second configuration config_B with the same MD5 hash but different parameters (e.g., pointing to a malicious data source).
3. Submit config_B to the SageMaker Workflow API.
4. The SDK will see the MD5 hash matches a previous run and return the cached results from config_A, but the pipeline will actually execute config_B (or vice versa, depending on implementation).
5. Monitor the pipeline output to confirm the substitution.

Example collision generation (conceptual):

# Using hashclash to generate two files with same MD5
./hashclash -o prefix -p "config_A" "config_B"

Note: No public exploit code is available for this specific CVE, but the general MD5 collision technique is well-documented.

Blue Team

Detection:

• Monitor for multiple workflow submissions with identical MD5 hashes but different configuration payloads.
• Log and alert on any workflow ID collisions.
• Use anomaly detection on pipeline execution times and output consistency.

Prevention:

• Implement input validation to reject configurations that are too similar to previous ones.
• Use a nonce or timestamp in the hash computation to prevent reuse.
• Enforce the use of SHA-256 or stronger hashing in custom SDK wrappers.

Hunting:

• Search for workflows where the MD5 hash matches a previous run but the configuration parameters differ.
• Review pipeline logs for unexpected cache hits.

Indicators of Compromise (IOCs)

• File Hashes: MD5 collisions in workflow configuration files.
• Network: Unusual API calls to SageMaker Workflow with repeated hash values.
• Logs: Pipeline logs showing cache hits for configurations that were never submitted.
• Process: Abnormal reuse of workflow results across different experiments.

Detection Engineering

YARA Rule

rule CVE_2025_0508_MD5_Collision {
    meta:
        description = "Detects MD5 hash usage in SageMaker Python SDK workflow configurations"
        author = "Valters IT"
        date = "2025-02-20"
        reference = "CVE-2025-0508"
    strings:
        $md5_func = "hashlib.md5" nocase
        $md5_call = "md5(" nocase
        $workflow_id = "get_workflow_id" nocase
    condition:
        any of ($md5_func, $md5_call) and $workflow_id
}

Sigma Rule

title: SageMaker Workflow MD5 Collision Attempt
id: 7a8b9c0d-1e2f-3a4b-5c6d-7e8f9a0b1c2d
status: experimental
description: Detects potential exploitation of CVE-2025-0508 by monitoring for duplicate workflow IDs with different configurations
author: Valters IT
logsource:
    product: aws
    service: sagemaker
detection:
    selection:
        eventName: "CreateWorkflow"
        requestParameters.config: "*"
    condition: selection
    timeframe: 5m
    aggregation:
        field: requestParameters.config
        function: distinct
        condition: gt 1
falsepositives:
    - Legitimate reuse of identical configurations
level: medium

Suricata Rule

alert http $HOME_NET any -> $EXTERNAL_NET any (msg:"CVE-2025-0508 SageMaker Workflow MD5 Collision Attempt"; flow:to_server; content:"POST"; http_method; content:"/sagemaker/workflow"; http_uri; content:"md5"; nocase; sid:1000001; rev:1;)

Remediation & Mitigation

Immediate Actions:

1. Upgrade: Monitor the AWS SageMaker Python SDK repository for an official patch. Once available, upgrade to the patched version immediately.
2. Workaround: Implement a custom wrapper that replaces MD5 with SHA-256 in the workflow ID generation. This can be done by monkey-patching the SDK or using a middleware layer.
3. Input Validation: Add checks to reject workflow configurations that are too similar to previous ones, or require a unique nonce per submission.
4. Monitoring: Enable detailed logging for all SageMaker Workflow API calls and set up alerts for duplicate workflow IDs.

Long-term Fix:

• AWS should release a patched version of the SDK that uses SHA-256 or a stronger hash function.
• Consider using a combination of hash and timestamp to ensure uniqueness.

Valters IT Signature This report was generated by Valters IT Cyber Threat Intelligence. For questions, contact threatintel@valters.it.