CrewAI before fb2323b offers a Python blocklist approach that operates at the wrong level of abstraction, a different vulnerability than CVE-2026-2275
Source GCVE Database
Mentioned vulnerabilities
Not known to be exploited · CVSS 8.1 High.
Data as of 29 Oct 2026, 10:37 UTC
- EPSS
- 0.1% chance of exploitation in 30 days – higher than 5% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:L/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:LExploitation evidence
Disclosed: evidence found.
CVE published 13 Sep 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 29 Oct 2026.
What to do
AI-suggested
Until a fix is available, users should be aware that import-time blocking is insufficient for sandboxing and consider alternative or additional runtime-level restrictions.
Description
CrewAI before fb2323b offers a Python blocklist approach that operates at the wrong level of abstraction, a different vulnerability than CVE-2026-2275. Import-time blocking of module names does not address the availability of Python's complete object graph. For example, calling ctypes.CDLL(None) loads the C library without relying in any import statements. In other words, a within-process sandbox cannot merely account for the import system and instead must account for the complete runtime of the Python interpreter.