EUVD-2026-51231Severity by source
AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
Untrusted template input is network-reachable and unauthenticated in the intended threat model, low complexity; pure arbitrary-file-read gives C:H with no integrity or availability impact.
Primary rating from Vendor (GitHub_M).
CVSS VectorVendor: GitHub_M
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
Lifecycle Timeline
3DescriptionCVE.org
Banks generates meaningful LLM prompts using a simple template language. In versions prior to 2.4.4, all four media filters (image, audio, video, document) in banks accept untrusted user input as file paths via Path(value) and pass them directly to open(file_path, "rb") without any path sanitization, canonicalization, or directory restriction. An attacker who controls template variables passed to a banks Prompt can use path traversal (../) to read arbitrary files accessible to the Python process-including .env files, SSH keys, cloud credentials, source code, /etc/passwd, and /etc/shadow-with the content returned base64-encoded in the rendered prompt output, making exfiltration trivial. This is particularly dangerous for applications that use banks to process user-provided template variables before sending prompts to an LLM. This issue has been fixed in version 2.4.4.
Articles & Coverage 1
AnalysisAI
Arbitrary file disclosure in the Banks Python prompt-templating library (masci/banks) before 2.4.4 lets attackers who control template variables read any file the Python process can access. All four media filters (image, audio, video, document) wrap untrusted input in Path(value) and feed it straight to open(file_path, "rb") with no sanitization, so path traversal (../) reads files like .env, SSH keys, cloud credentials, source, /etc/passwd and /etc/shadow, returning them base64-encoded in the rendered prompt for trivial exfiltration. …
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Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata
Vulnerability AssessmentAI
| Exploitation | Exploitation requires that the embedding application passes attacker-influenced data into a Banks Prompt template variable that is consumed by one of the four media filters (image, audio, video, or document), and that the rendered prompt output (or the resulting LLM response) is observable to the attacker so the base64-encoded file contents can be retrieved. … Additional conditions and limiting factors are described in the full assessment. |
| Risk Assessment | The CVSS 3.1 vector CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N scores 7.5 and models pure confidentiality loss via network-reachable, unauthenticated, low-complexity access - consistent with arbitrary file read. … Full risk analysis with EPSS, KEV, and SSVC signal comparison available after sign-in. |
| Exploit Scenario | An application uses Banks to render prompts and passes a user-supplied field (e.g., a filename or attachment path) into a template that applies the document filter. The attacker sets that variable to '../../../../etc/shadow' or '../../.env'; Banks opens the file and embeds its base64-encoded contents in the rendered prompt, which the attacker then reads back from the LLM interaction or response. … |
| Remediation | Vendor-released patch: upgrade Banks to version 2.4.4, which fixes all four media filters (pin banks>=2.4.4 in requirements/pyproject and rebuild). … Detailed patch versions, workarounds, and compensating controls in full report. |
Recommended ActionAI
Within 24 hours, identify all production and development systems using masci/banks, determine their versions, and assess whether untrusted users or external systems can supply template variable values through APIs or other interfaces. …
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External POC / Exploit Code
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