CVE-2023-53905
Projectsend r1605
Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:A/VC:N/VI:N/VA:N/SC:H/SI:H/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2023-53905 is a medium-severity Improper Neutralization of Formula Elements in a CSV File (CWE-1236) vulnerability in Projectsend Projectsend. Its CVSS base score is 6.2 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique User Execution (T1204); ranked at the 36th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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-2023-60225
Vulnerability Data
ProjectSend r1605 contains a CSV injection vulnerability that allows authenticated users to inject malicious formulas into user profile names. Attackers can craft payloads like =calc|a!z| in the name field to trigger code execution when administrators export action logs as CSV…
more
files.
- 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.