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VulnerabilityPublished Updated

CVE-2025-66960: ollama · Uncontrolled Resource Consumption

Affects ollamaSource CVE Database V5

0

Not known to be exploited · CVSS 7.5 High.

Data as of 26 Oct 2026, 11:42 UTC

CVSS 3.1 base score
7.5High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.4% chance of exploitation in 30 days – higher than 36% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 21 Jan 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 26 Oct 2026.

What to do

Affected software

ProductAffectedFixed in
GitHubollama/ollamapkg:github/ollama/ollamaOther threatsAffected
  • =0.12.10
Fixed in–

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

  1. Monitor official ollama repositories and vendor communications for patches or updates addressing CVE-2025-66960 and apply them promptly once available.
  2. Implement network-level access controls to restrict exposure of services parsing GGUF metadata to trusted internal networks or VPNs only.
  3. Employ input validation and sanitization mechanisms at the application or middleware layer to detect and reject malformed GGUF metadata before processing.
  4. Use runtime application self-protection (RASP) or web application firewalls (WAF) with custom rules to detect anomalous requests targeting the vulnerable function.
  5. Conduct regular vulnerability scanning and penetration testing focused on AI/ML components and their dependencies.
  6. Establish monitoring and alerting for unusual resource consumption or application crashes related to ollama services.
  7. Educate development and security teams about the risks of improper input validation in AI/ML software to prevent similar issues in future code.
  8. Consider isolating or sandboxing the processing of untrusted GGUF metadata to limit the impact of potential exploitation.

Description

An issue in ollama v.0.12.10 allows a remote attacker to cause a denial of service via the fs/ggml/gguf.go, function readGGUFV1String reads a string length from untrusted GGUF metadata

References

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