CVE-2024-53260
Autolabproject Autolab ≤ 3.0.2
Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:N/A:NSummary
CVE-2024-53260 is a medium-severity Improper Neutralization of Formula Elements in a CSV File (CWE-1236) vulnerability in Autolabproject Autolab. Its CVSS base score is 6.8 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique User Execution (T1204); ranked at the 38th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SI-15 (Information Output Filtering) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-51922
Vulnerability Data
Autolab is a course management service that enables auto-graded programming assignments. A user can modify their first and or last name to include a valid excel / spreadsheet formula. When an instructor downloads their course's roster and opens, this name…
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will then be evaluated as a formula. This could lead to leakage of information of students in the course roster by sending the data to a remote endpoint. This issue has been patched in the source code repository and the fix is expected to be released in the next version. Users are advised to manually patch their systems or to wait for the next release. There are no known workarounds for this vulnerability.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.2.10
Mitigating Controls (NIST 800-53 r5) AI
Output filtering/validation directly stops unneutralized formula elements from being written into CSV files.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly require output neutralization for untrusted CSV content to block formula injection.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing in development can detect formula injection but does not itself implement the mitigation.
Secure SDLC mandates input validation and output encoding that directly prevents formula injection in CSV exports.
Application security requirements include rules for safe CSV generation and handling of untrusted data.
Secure architecture principles encourage safe data export design but do not specifically address CSV formula neutralization.
Secure coding standards explicitly require neutralization of special characters when writing CSV files.