CrewAI Security Vulnerabilities

CrewAI fails to validate Docker runtime availability during execution and silently reverts to an insecure sandbox mode, enabling remote code execution. Affected versions prior to the patch rely on Docker for isolation; when Docker becomes unavailable or is misconfigured, the fallback mechanism does not enforce adequate sandboxing constraints, allowing attackers to execute arbitrary commands within the application context. No CVSS score or official CVE details are available at this time, though the vulnerability has been reported to CERT and carries high practical risk due to the automatic unsafe fallback behavior.

Server-side request forgery in CrewAI's RAG search tools allows remote attackers to access internal and cloud services by injecting malicious URLs at runtime without proper validation. The vulnerability affects CrewAI's content acquisition mechanisms, enabling unauthorized data exfiltration from internal networks and cloud-hosted resources. No CVSS score, active exploitation status, or patch information is currently available in public sources.

Remote code execution in CrewAI's CodeInterpreter tool occurs when Docker connectivity fails and the system falls back to SandboxPython, allowing unauthenticated remote attackers to execute arbitrary C functions and achieve code execution. The vulnerability affects systems relying on CrewAI's code execution capabilities where Docker is unavailable or unreachable, creating a dangerous fallback condition that bypasses intended sandboxing protections.

CrewAI's JSON loader tool fails to validate file paths before reading, allowing arbitrary local file access that exposes sensitive server files to attackers with network access to the application. The vulnerability enables information disclosure without authentication, affecting all versions of CrewAI that include the vulnerable JSON loader component. No active exploitation has been confirmed, but the straightforward nature of the attack (unsanitized file path input) makes this a practical concern for production deployments.