CVE-2026-1778: 
Python vulnerability analysis and mitigation

CVE-2026-1778 is an insecure TLS configuration vulnerability in the Amazon SageMaker Python SDK that disables SSL/TLS certificate verification globally when a Triton Python model is imported. This misconfiguration allows HTTPS connections with invalid or self-signed certificates to succeed, opening the door to man-in-the-middle (MITM) attacks. Affected versions include SageMaker Python SDK v3 before v3.1.1 and v2 before v2.256.0. The vulnerability was disclosed on February 2, 2026, via the AWS Security Bulletin and GitHub Advisory Database. It carries a CVSS v3.1 base score of 5.9 (Medium) and a CVSS v4.0 base score of 8.2 (High) (GitHub Advisory, AWS Bulletin).

The root cause is classified as CWE-295 (Improper Certificate Validation) and CWE-599 (Missing Validation of OpenSSL Certificate). SSL certificate verification was globally disabled in the Triton Python backend as a workaround for SSL errors encountered during model downloads from public sources such as TorchVision, inadvertently affecting all HTTPS connections made during Triton Python model imports. An attacker positioned on the network path (e.g., via ARP spoofing or DNS hijacking) can intercept these unverified HTTPS connections and substitute malicious models or dependencies without detection. No authentication or user interaction is required to position for the attack, though network adjacency or routing control is a prerequisite (GitHub Advisory, AWS Bulletin).

Successful exploitation enables an attacker to perform MITM attacks against HTTPS connections during Triton Python model imports, allowing them to serve malicious models or tampered dependencies to the SageMaker environment. This can lead to arbitrary code execution within the Triton container, compromising the integrity of machine learning models deployed to SageMaker. The primary impact is on integrity (unauthorized model/code substitution), with potential for further lateral movement or data exfiltration depending on the permissions of the compromised container (GitHub Advisory, AWS Bulletin).

There is no public proof-of-concept exploit code and no evidence of in-the-wild exploitation at this time. The EPSS score is approximately 0.006% (1st percentile), indicating a very low probability of exploitation in the near term. The vulnerability is not listed in the CISA Known Exploited Vulnerabilities (KEV) catalog. Exploitation requires the attacker to be in a network position to intercept HTTPS traffic (e.g., via MITM), which raises the practical bar for exploitation (GitHub Advisory, Feedly).

1. Reconnaissance: Identify target environments running Amazon SageMaker Python SDK versions v3 < v3.1.1 or v2 < v2.256.0 that use Triton Python model imports.
2. Network Positioning: Gain a MITM position on the network path between the SageMaker environment and the model/dependency download source (e.g., via ARP spoofing, DNS hijacking, or rogue Wi-Fi/proxy).
3. TLS Interception: Present a self-signed or otherwise invalid TLS certificate to the SageMaker SDK during an HTTPS model download. Because certificate verification is globally disabled in the Triton Python backend, the connection proceeds without error.
4. Payload Delivery: Serve a malicious model file or tampered dependency in place of the legitimate one. The SDK accepts the response without validating the server's identity.
5. Code Execution: The malicious model or dependency is loaded into the Triton container, potentially achieving remote code execution within the container's context (GitHub Advisory, AWS Bulletin).

• Network: Unexpected TLS certificate mismatches or self-signed certificate warnings in network monitoring tools during SageMaker model import operations; unusual outbound HTTPS connections from SageMaker training/inference instances to unexpected IP addresses or domains.
• Logs: SSL/TLS warning suppression or absence of certificate validation errors in SageMaker SDK logs during Triton model imports where errors would normally be expected; unexpected model download sources in application logs.
• File System: Presence of unexpected or unsigned model files in the Triton container's model repository directory; newly introduced files with unusual checksums compared to known-good model artifacts.
• Process: Unexpected child processes or network connections spawned from within the Triton container following a model import operation.

Upgrade the Amazon SageMaker Python SDK to v3.1.1 (v3.x branch) or v2.256.0 (v2.x branch) or later, which re-enable proper TLS certificate verification. For environments where immediate patching is not feasible, customers using self-signed certificates for internal model downloads should add their private CA certificate to the container image rather than relying on the SDK's previous insecure configuration. Additionally, restrict network access to trusted model repositories and monitor for suspicious certificate-related activity during model imports (AWS Bulletin, GitHub Advisory).

AWS published an official security bulletin (2026-004-AWS) on February 2, 2026, disclosing this vulnerability alongside a related HMAC exposure issue (CVE-2026-1778), and recommended immediate upgrade to patched versions. The advisory was also published to the GitHub Advisory Database and reviewed the same day. No significant independent researcher commentary or broad social media discussion has been identified beyond the official disclosure channels (AWS Bulletin, GitHub Advisory).