CrewAI sandbox

CVSS Meta Temp Score
CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.
Current Exploit Price (≈)
Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.
CTI Interest Score
Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
6.9$0-$5k1.07-

Summaryinfo

A vulnerability was found in CrewAI. It has been rated as problematic. Affected is an unknown function. Performing a manipulation results in sandbox. This vulnerability is reported as CVE-2026-37008. The attack requires a local approach. No exploit exists. To fix this issue, it is recommended to deploy a patch.

Detailsinfo

A vulnerability, which was classified as problematic, was found in CrewAI (version unknown). This affects an unknown function. The manipulation with an unknown input leads to a sandbox vulnerability. CWE is classifying the issue as CWE-265. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:

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.

It is possible to read the advisory at github.com. This vulnerability is uniquely identified as CVE-2026-37008 since 04/06/2026. The exploitability is told to be easy. Attacking locally is a requirement. The technical details are unknown and an exploit is not publicly available. The attack technique deployed by this issue is T1611 according to MITRE ATT&CK.

Applying the patch fb2323b3deb3ec62b3965526857e77a2264e4cd0 is able to eliminate this problem.

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Name

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 7.0
VulDB Meta Temp Score: 6.9

VulDB Base Score: 5.9
VulDB Temp Score: 5.7
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 8.1
CNA Vector (MITRE): 🔒

CVSSv2info

AVACAuCIA
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VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍

Exploitinginfo

Class: Sandbox
CWE: CWE-265 / CWE-264
CAPEC: 🔒
ATT&CK: 🔒

Physical: Partially
Local: Yes
Remote: No

Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: Patch
Status: 🔍

0-Day Time: 🔒

Patch: fb2323b3deb3ec62b3965526857e77a2264e4cd0

Timelineinfo

04/06/2026 CVE reserved
09/13/2026 +160 days Advisory disclosed
09/13/2026 +0 days VulDB entry created
09/13/2026 +0 days VulDB entry last update

Sourcesinfo

Advisory: github.com
Status: Confirmed

CVE: CVE-2026-37008 (🔒)
GCVE (CVE): GCVE-0-2026-37008
GCVE (VulDB): GCVE-100-403347

Entryinfo

Created: 09/13/2026 23:04
Changes: 09/13/2026 23:04 (24), 09/13/2026 23:05 (37)
Complete: 🔍
Cache ID: 216::103

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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