CWE-1427Base

Improper Neutralization of Input Used for LLM Prompting

Incomplete in the CWE catalog · 11 CVEs mapped

11
CVEs mapped
6.5
Median CVSS
What it is

The product uses externally-provided data to build prompts provided to

large language models (LLMs), but the way these prompts are constructed

causes the LLM to fail to distinguish between user-supplied inputs and

developer provided system directives.

Recent examples
8.4cvss
CVE-2026-46580

In Eclipse Theia versions prior to 1.71.0, files matching the pattern .prompts/*.prompttemplate in a workspace were automatically loaded and could override or…

In Eclipse Theia versions prior to 1.71.0, files matching the pattern .prompts/*.prompttemplate in a workspace were automatically loaded and could override or extend the AI agent's system prompts. An attacker could craft a malicious repository containing prompt template files that, when the workspace was opened in Theia, replaced the AI's system instructions with attacker-controlled content (indirect prompt injection). Combined with other AI chat features available in untrusted workspaces, this enabled attack chains leading to data exfiltration via Markdown image rendering or arbitrary command execution via task definitions.

HIGHno explanation yet
1%
epss
8.4cvss
CVE-2026-44688

In Eclipse Theia versions prior to 1.71.0, the AI chat agent processed workspace file and directory names as part of its prompt context without distinguishing…

In Eclipse Theia versions prior to 1.71.0, the AI chat agent processed workspace file and directory names as part of its prompt context without distinguishing them from system instructions. An attacker could craft a malicious repository with adversarial directory or file names that, when analyzed by the AI agent, would cause the agent to follow attacker-controlled instructions (indirect prompt injection). Combined with other AI chat features available in untrusted workspaces, this enabled attack chains leading to data exfiltration via Markdown image rendering or arbitrary command execution via task definitions.

HIGHno explanation yet
1%
epss
9.8cvss
CVE-2026-44717

MCP Calculate Server: Prompt Injection to RCE

MCP Calculate Server is a mathematical calculation service based on MCP protocol and SymPy library. Prior to 0.1.1, the use of eval() to evaluate mathematical expressions without proper input sanitization leads to remote code execution. This vulnerability is fixed in 0.1.1.

CRITICALno explanation yet
0%
epss
The record
Technical detail
CWE ID
CWE-1427
Abstraction
Base
Structure
Simple
Status
Incomplete
References (3)