Raw vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2026-34937 is a high-severity OS Command Injection (CWE-78) vulnerability in Praison Praisonaiagents. Its CVSS base score is 7.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); ranked at the 43th 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 SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2026-34937 is an OS command injection vulnerability (CWE-78) in PraisonAI, an open-source multi-agent teams system. The issue affects versions prior to 1.5.90 and resides in the run_python() function within the praisonai package. This function constructs a shell command by interpolating user-controlled code into a python3 -c "<code>" string and executes it via subprocess.run() with shell=True. The escaping logic only handles backslashes and double quotes, leaving command substitutions like $() and backticks unescaped, which enables arbitrary OS command execution on the host system before the Python interpreter is invoked. The vulnerability carries a CVSS v3.1 base score of 7.8 (AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H).
A local attacker with low privileges can exploit this vulnerability by supplying malicious input to the run_python() function, such as code containing shell metacharacters like $(command) or backticks. No user interaction is required beyond providing the crafted input, and exploitation is straightforward due to low attack complexity. Successful exploitation grants the attacker the ability to execute arbitrary operating system commands with the privileges of the PraisonAI process, potentially leading to high-impact confidentiality, integrity, and availability violations, including full system compromise if the process runs with elevated privileges.
The GitHub security advisory (GHSA-w37c-qqfp-c67f) confirms that the vulnerability has been patched in PraisonAI version 1.5.90. Security practitioners should upgrade to this version or later to mitigate the issue, and review any deployments of earlier versions for potential exposure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-18917
Vulnerability Data
PraisonAI is a multi-agent teams system. Prior to version 1.5.90, run_python() in praisonai constructs a shell command string by interpolating user-controlled code into python3 -c "<code>" and passing it to subprocess.run(..., shell=True). The escaping logic only handles \ and ",…
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leaving $() and backtick substitutions unescaped, allowing arbitrary OS command execution before Python is invoked. This issue has been patched in version 1.5.90.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.2.5V1.2.8V15.2.5
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect command sanitization during development.
Input validation directly neutralizes or rejects special characters that would otherwise alter OS command structure.
Least privilege reduces the permissions available to any process that could be subverted by injected commands.
Least functionality restricts available OS commands and interpreters, limiting the blast radius of injection.
Secure engineering principles require proper neutralization of untrusted input before command construction.
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.
PR.PS-06's SDLC practices directly require secure coding and input handling that blocks command-injection defects, yet the single broad outcome leaves many specific neutralization vectors and verification gaps unaddressed.
Routine patching/maintenance can remediate known command-injection CVEs in dependencies (partial forward) but does nothing to stop developers from introducing improper neutralization in custom code (none reverse).
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 and code review target insecure use of operating-system command interfaces, catching command-injection flaws introduced during development.