PatchSiren

PatchSiren cyber security CVE debrief

CVE-2026-62663 masci CVE debrief

CVE-2026-62663 is a high-severity vulnerability in the Banks library, which generates meaningful LLM prompts using a simple template language. In versions prior to 2.4.4, the library's media filters (image, audio, video, document) accept untrusted user input as file paths and pass them directly to open(file_path, 'rb') without any path sanitization, canonicalization, or directory restriction. This allows an attacker to use path traversal (../) to read arbitrary files accessible to the Python process, including sensitive files such as .env files, SSH keys, cloud credentials, source code, /etc/passwd, and /etc/shadow. The content of these files is returned base64-encoded in the rendered prompt output, making exfiltration trivial. This issue has been fixed in version 2.4.4.

Vendor
masci
Product
banks
CVSS
HIGH 7.5
CISA KEV
Not listed in stored evidence
Original CVE published
2026-07-30
Original CVE updated
2026-10-23
Advisory published
2026-07-30
Advisory updated
2026-10-23

Who should care

Defenders responsible for applications that use the Banks library to process user-provided template variables before sending prompts to an LLM should assess exposure and prioritize upgrading to version 2.4.4 or later.

Why it matters

CVE-2026-62663 is a high-severity vulnerability in the Banks library that allows path traversal attacks, enabling attackers to read arbitrary files accessible to the Python process. Defenders should prioritize upgrading to version 2.4.4 or later and validate and sanitize user-provided template variables before sending prompts to an LLM.

  • Path traversal attacks can lead to unauthorized file reads
  • Sensitive files such as .env files, SSH keys, cloud credentials, source code, /etc/passwd, and /etc/shadow can be accessed
  • Content of these files can be returned base64-encoded in the rendered prompt output, making exfiltration trivial
  • Verification of user-provided template variables is necessary to prevent path traversal attacks

Technical summary

The Banks library generates meaningful LLM prompts using a simple template language. In versions prior to 2.4.4, the library's media filters (image, audio, video, document) accept untrusted user input as file paths and pass them directly to open(file_path, 'rb') without any path sanitization, canonicalization, or directory restriction. This allows an attacker to use path traversal (../) to read arbitrary files accessible to the Python process.

Defensive priority

Defenders should prioritize upgrading to version 2.4.4 or later to prevent path traversal attacks. They should also validate and sanitize user-provided template variables before sending prompts to an LLM.

Recommended defensive actions

  • Upgrade to version 2.4.4 or later
  • Validate and sanitize user-provided template variables
  • Monitor for suspicious activity
  • Review compensating controls for exposed systems while remediation is scheduled and verified
  • Check relevant monitoring, detection, and logs for exposed assets that need extra review
  • Track exceptions, retest remediated assets, and close the item only after evidence is documented
  • Confirm whether affected product deployments exist in managed environments and assign an owner for follow-up

Evidence notes

The CVE record and NVD vulnerability detail provide information about the vulnerability, its impact, and the fixed version. However, the corpus does not establish versions, exploitation, impact, or remediation for all affected systems, requiring verification from the supplied official sources.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-62663 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-62663

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-62663 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-62663

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.