Common Weakness Enumeration

CWE-1427

Allowed

Improper Neutralization of Input Used for LLM Prompting

Abstraction: Base · Status: Incomplete

API response cwe.mitre.org

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.

21 vulnerabilities reference this CWE, most recent first.

CVE-2026-114107 (GCVE-0-2026-114107)

Vulnerability from cvelistv5 – Published: 2026-10-21 00:37 – Updated: 2026-10-22 16:04
VLAI
Title
HKUDS Vibe-Trading 0.1.0 before 0.1.7 Indirect Prompt Injection RCE via BashTool and BackgroundRunTool
Summary
HKUDS Vibe-Trading from 0.1.0 before 0.1.7 contains an indirect prompt injection vulnerability that allows remote attackers to execute shell commands as root by planting instructions in documents or web pages the agent processes. BashTool and BackgroundRunTool pass model-emitted commands to subprocess.run with shell=True and no allow-list or approval step, and read_url fetches arbitrary URLs, enabling command execution and server-side request forgery.
Severity
8.7 (High)
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
8.8 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-22 16:04 UTC
CWE
  • CWE-1427 - Improper Neutralization of Input Used for LLM Prompting
Assigner
VulnCheck CNA under the mitre root
CNA scorecard B 84/100 over 6843 records in the last 180 days details
References
Impacted products
Vendor Product Version
HKUDS Vibe-Trading Affected: 0.1.0 , < 0.1.7 (semver)
Unaffected: 0.1.7 (semver)
Create a notification for this product.
Date Public
2026-07-29 00:00
Credits
lemi9090
Show details on NVD website
To clipboard 

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CVE-2026-109440 (GCVE-0-2026-109440)

Vulnerability from cvelistv5 – Published: 2026-10-20 00:46 – Updated: 2026-10-22 21:16
VLAI
Title
LangAlpha through 2026.09.07 Indirect Prompt Injection RCE via Bash and ExecuteCode
Summary
LangAlpha through 2026.09.07 contains an indirect prompt injection vulnerability that allows remote attackers to execute shell commands or Python by planting instructions in web content retrieved by the agent. Because Bash and ExecuteCode lack an allow-list and human-in-the-loop approval, attackers can run code in the workspace sandbox and exfiltrate vault secrets from _internal/.vault_secrets.json.
Severity
8.7 (High)
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
8.8 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
SSVC
Exploitation: poc Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-22 21:16 UTC
CWE
  • CWE-1427 - Improper Neutralization of Input Used for LLM Prompting
Assigner
VulnCheck CNA under the mitre root
CNA scorecard B 84/100 over 6843 records in the last 180 days details
References
Impacted products
Vendor Product Version
ginlix-ai LangAlpha Affected: 0 , ≤ 2026.09.07 (custom)
Create a notification for this product.
Date Public
2026-10-15 00:00
Credits
Noy Pearl Michael Sromin Ophir Dror
Show details on NVD website
To clipboard 

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CVE-2026-96893 (GCVE-0-2026-96893)

Vulnerability from cvelistv5 – Published: 2026-10-13 01:05 – Updated: 2026-10-14 10:51
VLAI
Title
Improper Neutralization of Input Used for LLM Prompting in GitLab
Summary
GitLab has remediated an issue in GitLab EE affecting all versions from 19.1 before 19.2.8, 19.3 before 19.3.5, and 19.4 before 19.4.2 that, under certain conditions, could have allowed an authenticated user to inject specially crafted content into AI agent instructions, potentially causing unintended command execution attributed to other users, due to improper neutralization of special elements in AI conversation context construction.
Severity
7.3 (High)
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:N
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-14 03:59 UTC
CWE
  • CWE-1427 - Improper Neutralization of Input Used for LLM Prompting
Assigner
GitLab CNA under the mitre root
CNA scorecard B 75/100 over 301 records in the last 180 days details
References
Impacted products
Vendor Product Version
GitLab GitLab Affected: 19.1 , < 19.2.8 (semver)
Affected: 19.3 , < 19.3.5 (semver)
Affected: 19.4 , < 19.4.2 (semver)
    cpe:2.3:a:gitlab:gitlab:*:*:*:*:*:*:*:*
Create a notification for this product.
Credits
This vulnerability has been discovered internally by GitLab team member Mert Coskuner.
Show details on NVD website
To clipboard 

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CVE-2026-78379 (GCVE-0-2026-78379)

Vulnerability from cvelistv5 – Published: 2026-08-25 19:05 – Updated: 2026-08-25 19:20
VLAI
Title
Consent bypass in python_repl tool via batch kwargs forwarding in Amazon Strands Agents Tools
Summary
Improper neutralization of input used for LLM prompting in the python_repl tool in Amazon Strands Agents Tools before 0.8.5 might allow remote actors to execute arbitrary Python code on the agent's host by bypassing the human consent gate, via a crafted prompt that forwards non_interactive_mode as a keyword argument through the batch tool. To remediate this issue, users should upgrade to version 0.8.5 or later.
Severity
9.2 (Critical)
CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
8.1 (High)
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-25 19:19 UTC
CWE
  • CWE-1427 - Improper Neutralization of Input Used for LLM Prompting
Assigner
AMZN CNA under the mitre root
CNA scorecard A 94/100 over 139 records in the last 180 days details
References
Impacted products
Vendor Product Version
Amazon strands-agents-tools Affected: 0 , < 0.8.5 (custom)
    cpe:2.3:a:amazon:strands-agents-tools:*:*:*:*:*:*:*:*
Create a notification for this product.
Show details on NVD website
To clipboard 

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CVE-2026-77931 (GCVE-0-2026-77931)

Vulnerability from cvelistv5 – Published: 2026-10-15 01:24 – Updated: 2026-10-26 15:25 X_Open Source
VLAI
Title
MoviePilot 3.1.5 Command Injection via ExecuteCommandTool
Summary
MoviePilot through 3.1.5 contains a command injection vulnerability that allows attackers to execute arbitrary OS commands by embedding malicious instructions in untrusted content processed through tools like browse_webpage, search_web, and torrent metadata parsers, which then get passed to the unrestricted ExecuteCommandTool via asyncio.create_subprocess_shell. Attackers can craft content that instructs the model to invoke execute_command with confirm_dangerous set to true, bypassing the validate_command_safety denylist and exploiting the admin session's is_admin context to achieve remote code execution on the host.
Severity
8.7 (High)
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
8.8 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-10-26 15:23 UTC
CWE
  • CWE-1427 - Improper Neutralization of Input Used for LLM Prompting
  • CWE-77 - Improper Neutralization of Special Elements used in a Command ('Command Injection')
Assigner
VulnCheck CNA under the mitre root
CNA scorecard B 84/100 over 6843 records in the last 180 days details
References
Impacted products
Vendor Product Version
jxxghp MoviePilot Affected: 0 , ≤ 3.1.5 (semver)
Create a notification for this product.
Date Public
2026-10-12 00:00
Credits
Noy Pearl Michael Sromin Ophir Dror
Show details on NVD website
To clipboard 

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CVE-2026-75130 (GCVE-0-2026-75130)

Vulnerability from cvelistv5 – Published: 2026-08-18 18:02 – Updated: 2026-08-19 15:14
VLAI
Title
Context7 2.1.2 Prompt Injection via Custom AI Instructions
Summary
Context7 through 2.1.2 contains a prompt injection vulnerability that allows attackers to execute malicious instructions in connected AI coding agents by injecting unsanitized content through the Custom AI Instructions feature served via the MCP server. Attackers can poison the custom instructions to exfiltrate credentials from environment files to an attacker-controlled service and perform destructive file deletion on the victim's machine when the agent makes a routine library documentation request.
Severity
6.4 (Medium)
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:P/VC:N/VI:N/VA:N/SC:H/SI:H/SA:H
9 (Critical)
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-19 15:14 UTC
CWE
  • CWE-1427 - Improper Neutralization of Input Used for LLM Prompting
Assigner
VulnCheck CNA under the mitre root
CNA scorecard B 84/100 over 6843 records in the last 180 days details
References
Impacted products
Vendor Product Version
Uptash Context7 Affected: 0 , ≤ 2.1.2 (semver)
Create a notification for this product.
Date Public
2026-03-05 00:00
Credits
Eli Ainhorn - Senior AI Vulnerability Researcher @ Noma Security
Show details on NVD website
To clipboard 

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CVE-2026-70331 (GCVE-0-2026-70331)

Vulnerability from cvelistv5 – Published: 2026-08-28 17:41 – Updated: 2026-10-26 23:11
VLAI
Title
Microsoft Edge for iOS Spoofing Vulnerability
Summary
Improper neutralization of input used for llm prompting in Microsoft Edge for iOS allows an unauthorized attacker to perform spoofing over a network.
Severity
5.4 (Medium)
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:N/E:U/RL:O/RC:C
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-31 15:21 UTC
CWE
  • CWE-1427 - Improper Neutralization of Input Used for LLM Prompting
Assigner
microsoft CNA under the mitre root
CNA scorecard B 82/100 over 3954 records in the last 180 days details
References
Impacted products
Vendor Product Version
Microsoft Microsoft Edge (Chromium-based) Affected: 1.0.0.0 , < 150.0.4078.50 (custom)
Create a notification for this product.
Microsoft Microsoft Edge for iOS Affected: 1.0.0.0 , < 150.0.4078.50 (custom)
Create a notification for this product.
Date Public
2026-08-28 14:00
Show details on NVD website
To clipboard 

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CVE-2026-46580 (GCVE-0-2026-46580)

Vulnerability from cvelistv5 – Published: 2026-06-18 14:26 – Updated: 2026-06-19 03:55
VLAI
Summary
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.
Severity
8.4 (High)
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-18 00:00 UTC
CWE
  • CWE-829 - Inclusion of Functionality from Untrusted Control Sphere
  • CWE-1427 - Improper Neutralization of Input Used for LLM Prompting
Assigner
eclipse CNA under the mitre root
CNA scorecard C 64/100 over 186 records in the last 180 days details
References
Impacted products
Vendor Product Version
Eclipse Foundation Eclipse Theia Affected: 0 , < 1.71.0 (semver)
Create a notification for this product.
Credits
Piotr Ryciak (https://gitlab.eclipse.org/void01)
Show details on NVD website
To clipboard 

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CVE-2026-44717 (GCVE-0-2026-44717)

Vulnerability from cvelistv5 – Published: 2026-05-15 16:58 – Updated: 2026-05-15 17:25
VLAI
Title
MCP Calculate Server: Prompt Injection to RCE
Summary
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.
Severity
9.8 (Critical)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
SSVC
Exploitation: none Automatable: yes Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-05-15 17:24 UTC
CWE
  • CWE-94 - Improper Control of Generation of Code ('Code Injection')
  • CWE-1427
Assigner
GitHub_M CNA under the mitre root
CNA scorecard C 72/100 over 7797 records in the last 180 days details
References
Impacted products
Show details on NVD website
To clipboard 

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CVE-2026-44688 (GCVE-0-2026-44688)

Vulnerability from cvelistv5 – Published: 2026-06-18 14:22 – Updated: 2026-06-19 03:55
VLAI
Summary
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.
Severity
8.4 (High)
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-18 00:00 UTC
CWE
  • CWE-1427 - Improper neutralization of input used for LLM prompting
  • CWE-829 - Inclusion of functionality from untrusted control sphere
Assigner
eclipse CNA under the mitre root
CNA scorecard C 64/100 over 186 records in the last 180 days details
References
Impacted products
Vendor Product Version
Eclipse Foundation Eclipse Theia Affected: 0 , < 1.71.0 (semver)
Create a notification for this product.
Credits
Piotr Ryciak (https://gitlab.eclipse.org/void01)
Show details on NVD website
To clipboard 

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Mitigation
Architecture and Design

LLM-enabled applications should be designed to ensure proper sanitization of user-controllable input, ensuring that no intentionally misleading or dangerous characters can be included. Additionally, they should be designed in a way that ensures that user-controllable input is identified as untrusted and potentially dangerous.

Mitigation
Implementation

LLM prompts should be constructed in a way that effectively differentiates between user-supplied input and developer-constructed system prompting to reduce the chance of model confusion at inference-time.

Mitigation
Architecture and Design

LLM-enabled applications should be designed to ensure proper sanitization of user-controllable input, ensuring that no intentionally misleading or dangerous characters can be included. Additionally, they should be designed in a way that ensures that user-controllable input is identified as untrusted and potentially dangerous.

Mitigation
Implementation

Ensure that model training includes training examples that avoid leaking secrets and disregard malicious inputs. Train the model to recognize secrets, and label training data appropriately. Note that due to the non-deterministic nature of prompting LLMs, it is necessary to perform testing of the same test case several times in order to ensure that troublesome behavior is not possible. Additionally, testing should be performed each time a new model is used or a model's weights are updated.

Mitigation
Installation Operation

During deployment/operation, use components that operate externally to the system to monitor the output and act as a moderator. These components are called different terms, such as supervisors or guardrails.

Mitigation
System Configuration

During system configuration, the model could be fine-tuned to better control and neutralize potentially dangerous inputs.

No CAPEC attack patterns related to this CWE.

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