CVE-2023-22452
Published: 02 January 2023
Summary
CVE-2023-22452 is a medium-severity Improper Input Validation (CWE-20) vulnerability in Kenny2Automate Project Kenny2Automate. Its CVSS base score is 6.5 (Medium).
Operationally, ranked at the 43.5th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-26614
Vulnerability details
kenny2automate is a Discord bot. In the web interface for server settings, form elements were generated with Discord channel IDs as part of input names. Prior to commit a947d7c, no validation was performed to ensure that the channel IDs submitted…
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actually belonged to the server being configured. Thus anyone who has access to the channel ID they wish to change settings for and the server settings panel for any server could change settings for the requested channel no matter which server it belonged to. Commit a947d7c resolves the issue and has been deployed to the official instance of the bot. The only workaround that exists is to disable the web config entirely by changing it to run on localhost. Note that a workaround is only necessary for those who run their own instance of the bot.
- 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.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Directly implements checks on information inputs to reject invalid data before processing.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.