CVE Catalog

CVE-2026-107717

MediumCVSS 6.5
Published: Updated: Translated: NVD NIST

Exploitation Probability (EPSS)

Low risk
0.28%

19th percentile - higher than 19% of all known CVEs

Summary

Banks generates meaningful LLM prompts using a simple template language. Prior to 2.5.0, Banks Prompt.chat_messages() attempts to parse every line of rendered template output as ChatMessage JSON. When an application renders untrusted data and passes the returned ChatMessage objects to an LLM provider, attacker-controlled JSON can cross the prompt boundary and become a system, assistant, or tool message because ChatMessage.role accepts arbitrary strings. This can override application instructions, alter the intended prompt structure, or confuse downstream tool and message handling. This issue is fixed in version 2.5.0.

Risk Assessment

An attacker can manipulate the LLM prompt, potentially leading to instruction override, model behavior alteration, or data leakage.

Recommendation

Update Banks to version 2.5.0 or later. Additionally, validate and sanitize input rendered into templates and check message roles.

Other vulnerabilities in Banks

See all
Original NVD description (English source)

Banks generates meaningful LLM prompts using a simple template language. Prior to 2.5.0, Banks Prompt.chat_messages() attempts to parse every line of rendered template output as ChatMessage JSON. When an application renders untrusted data and passes the returned ChatMessage objects to an LLM provider, attacker-controlled JSON can cross the prompt boundary and become a system, assistant, or tool message because ChatMessage.role accepts arbitrary strings. This can override application instructions, alter the intended prompt structure, or confuse downstream tool and message handling. This issue is fixed in version 2.5.0.

Vulnerability data from NVD (NIST) · CISA KEV · EPSS