CVE-2026-50775 in DataHub
Summary
by MITRE • 08/17/2026
A blind SSRF attack in DataHub v.1.5.0.1 allows a remote attacker to execute arbitrary code via the server retrieving an image from a crafted URL, and it fails to return the content or any errors directly.
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Analysis
by VulDB Data Team • 08/17/2026
The vulnerability identified in Apache DataHub version 1.5.0.1 represents a critical security flaw classified as Server-Side Request Forgery (SSRF), specifically manifesting through an image processing mechanism that lacks adequate input validation and network access controls. This particular implementation of SSRF is characterized by its blind nature, meaning the attacker cannot directly observe the response from the internal or external server they are forcing DataHub to contact. Instead, the vulnerability relies on out-of-band interactions or side-channel effects to confirm exploitation, as the application fails to return any content or error messages related to the fetched resource. This obscurity makes detection and debugging significantly more challenging for security teams while allowing attackers to probe internal network infrastructure with a lower risk of immediate discovery through standard HTTP response analysis.
From a technical perspective, the flaw resides in how DataHub handles image URLs provided by users during ingestion or metadata updates. When an attacker supplies a maliciously crafted URL pointing to an internal service, such as a cloud metadata endpoint like http://169.254.169.254/latest/meta-data/iam/security-credentials/, the server initiates an HTTP request on behalf of the user. Because the application does not restrict which IP ranges or domains can be accessed, it effectively acts as a proxy for arbitrary network requests. The critical aspect of this blind SSRF is that the server attempts to fetch and potentially process the image data but silently discards the result if it cannot parse it correctly or if the connection fails in a specific way. This behavior prevents the attacker from seeing the direct output, forcing them to rely on timing differences, DNS callbacks, or other indirect methods to verify successful access to internal resources.
The operational impact of this vulnerability is severe, particularly within enterprise environments where DataHub is integrated with various backend systems and cloud providers. An authenticated remote attacker can leverage this flaw to perform network reconnaissance against the local area network, identifying live hosts, open ports, and running services that are not exposed to the public internet. More critically, in modern cloud-native deployments, attackers often target instance metadata service endpoints to steal temporary security credentials for AWS IAM roles or Azure managed identities. Possession of these credentials can lead to full compromise of associated cloud resources, including storage buckets, compute instances, and database clusters. Furthermore, if internal services are vulnerable to other attacks such as server-side template injection or command execution via specific file formats, the SSRF vector serves as a powerful entry point to trigger those secondary vulnerabilities within trusted network boundaries that would otherwise be inaccessible from outside.
This vulnerability aligns with CWE-918, which defines Server-Side Request Forgery (SSRF) flaws where the server makes requests based on user-supplied input without proper validation of the destination address or protocol. In terms of offensive security frameworks, this attack vector maps to MITRE ATT&CK technique T1571, specifically Subversion of Trusty Web Services, and potentially T1046 for Network Service Discovery if used for scanning internal networks. The blind nature of the exploit also correlates with techniques involving out-of-band data exfiltration or interaction, where the attacker infers success through indirect means rather than direct response parsing.
Mitigation strategies must focus on implementing strict allow-listing for outbound network connections initiated by DataHub services. Organizations should configure firewalls and proxy settings to block access to known internal IP ranges, such as RFC 1918 private addresses, link-local addresses like 169.254.0.0/16, and cloud metadata endpoints. Additionally, input validation on image URL fields is essential; developers should enforce strict regex patterns that only permit well-known public domains or specific internal whitelisted hosts if such functionality is required for business operations. Upgrading to a patched version of DataHub where these restrictions are enforced by default is the primary remediation step. For environments unable to upgrade immediately, network-level segmentation and egress filtering provide necessary compensating controls to prevent the application from reaching sensitive internal resources.