Critical Argument Injection Flaw in AI Agents Enables Remote Code Execution

AI-powered agents are increasingly utilized to perform tasks such as code analysis, file management, and workflow automation. However, a recently identified vulnerability, known as argument injection, demonstrates how these capabilities can be exploited for remote code execution (RCE), even when certain safeguards are in place.

CVE ID Product Vulnerability

CVE-2025-54795 Claude Code Command injection in CLI agents

AI agents commonly use pre-approved system tools like find , grep , and git for efficiency and reliability. These tools are considered secure and can operate with minimal oversight, thereby enhancing performance and stability. However, this design introduces a critical risk: argument injection. If user-controlled input is passed directly as a command argument without thorough validation, attackers can inject malicious flags, transforming secure commands into a vector for exploitation.

In several production systems, attackers have achieved RCE through sophisticated prompt injections:

Go Test Exploit: Attackers used the go test -exec flag to launch curl and bash , bypassing restrictions by leveraging the allowed go test command. Complex Chaining: By chaining git show and ripgrep (rg), attackers directed git show to drop a payload file and used rg --pre bash to execute it. Facade Pattern Bypasses: Facade handlers that append raw user input without strict separators can allow attackers to execute code, such as with fd -x=python3 .

These attacks illustrate that even sophisticated safety models, such as requiring human approval for risky commands, can fail if argument injection is not tightly controlled. This vulnerability is particularly dangerous because a single cleverly-designed prompt can achieve RCE.

Experts recommend isolating AI agent operations from the main system using sandboxes, such as containers (Docker), WebAssembly, or platform-specific sandbox tools. This approach prevents escape if an agent is compromised. If sandboxing is not feasible, developers should:

Implement facades that consistently separate user input using "--" to block flags. Permanently disable shell execution via shell=False . Maintain strict allowlists and review them against resources for potential abuse. Audit command execution paths for argument injection opportunities. Log all executions and flag suspicious sequences for review.

Users should exercise caution when granting system access to AI agents, especially in environments containing sensitive data. Utilizing containers or sandboxes, even on local machines, can limit the impact of successful attacks. Security engineers are encouraged to search for these vulnerabilities by examining agent command lists, reviewing code, and testing for unexpected flag handling.

As AI agents become more capable, securing their command execution capabilities is crucial. Argument injection remains a classic vulnerability in a modern context, emphasizing the enduring importance of input validation and isolation in next-generation technology.

Based on reporting by GBHackers.