CVE-2023-47117
Published: 13 November 2023
Summary
CVE-2023-47117 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Humansignal Label Studio. Its CVSS base score is 7.5 (High).
Operationally, ranked in the top 1.3% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
Deeper analysis
Label Studio, an open-source data labeling tool, is affected by an information disclosure vulnerability in all versions prior to 1.9.2post0. The application permits unauthenticated users to supply arbitrary filter expressions when querying tasks; these expressions are passed directly to Django's ORM, enabling attackers to reference sensitive model fields such as password hashes. A second issue is the presence of a hard-coded Django secret key that can be used to sign arbitrary session tokens once the hashes have been obtained.
An unauthenticated remote attacker can chain ORM filter predicates to extract sensitive column values character-by-character across all user accounts. With the leaked password hashes and the static secret key, the attacker can forge valid session cookies for any user, achieving full account takeover without requiring prior credentials or user interaction.
The vendor addressed both issues in commit f931d9d129, included in release 1.9.2post0. The GitHub Security Advisory GHSA-6hjj-gq77-j4qw explicitly states that no workarounds exist and recommends immediate upgrade.
The associated EPSS score reached 0.7064 without a documented low-to-high trajectory after disclosure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0108
Vulnerability details
Label Studio is an open source data labeling tool. In all current versions of Label Studio prior to 1.9.2post0, the application allows users to insecurely set filters for filtering tasks. An attacker can construct a filter chain to filter tasks…
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based on sensitive fields for all user accounts on the platform by exploiting Django's Object Relational Mapper (ORM). Since the results of query can be manipulated by the ORM filter, an attacker can leak these sensitive fields character by character. In addition, Label Studio had a hard coded secret key that an attacker can use to forge a session token of any user by exploiting this ORM Leak vulnerability to leak account password hashes. This vulnerability has been addressed in commit `f931d9d129` which is included in the 1.9.2post0 release. Users are advised to upgrade. There are no known workarounds for this vulnerability.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.