CVE-2026-30304
AI Code Command Injection Vulnerability
Description
In its design for automatic terminal command execution, AI Code offers two options: Execute safe commands and execute all commands. The description for the former states that commands determined by the model to be safe will be automatically executed, whereas if the model judges a command to be potentially destructive, it still requires user approval. However, this design is highly susceptible to prompt injection attacks. An attacker can employ a generic template to wrap any malicious command and mislead the model into misclassifying it as a 'safe' command, thereby bypassing the user approval requirement and resulting in arbitrary command execution.
INFO
Published Date :
March 27, 2026, 3:16 p.m.
Last Modified :
March 27, 2026, 3:16 p.m.
Remotely Exploit :
No
Source :
[email protected]
Affected Products
The following products are affected by CVE-2026-30304
vulnerability.
Even if cvefeed.io is aware of the exact versions of the
products
that
are
affected, the information is not represented in the table below.
No affected product recoded yet
Solution
- Only execute commands confirmed safe by the model.
- Require user approval for all commands.
- Implement strict input validation for commands.
- Update AI model to detect malicious prompts.
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2026-30304.
| URL | Resource |
|---|---|
| https://github.com/Secsys-FDU/LLM-Tool-Calling-CVEs/issues/2 | |
| https://marketplace.visualstudio.com/items?itemName=tianguaduizhang.claude-dev-china |
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2026-30304 is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2026-30304
weaknesses.
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2026-30304 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2026-30304 vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
-
New CVE Received by [email protected]
Mar. 27, 2026
Action Type Old Value New Value Added Description In its design for automatic terminal command execution, AI Code offers two options: Execute safe commands and execute all commands. The description for the former states that commands determined by the model to be safe will be automatically executed, whereas if the model judges a command to be potentially destructive, it still requires user approval. However, this design is highly susceptible to prompt injection attacks. An attacker can employ a generic template to wrap any malicious command and mislead the model into misclassifying it as a 'safe' command, thereby bypassing the user approval requirement and resulting in arbitrary command execution. Added Reference https://github.com/Secsys-FDU/LLM-Tool-Calling-CVEs/issues/2 Added Reference https://marketplace.visualstudio.com/items?itemName=tianguaduizhang.claude-dev-china