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CVE-2025-67485VulnerabilityPublished

CVE-2025-67485: machphy mad-proxy · Protection Mechanism Failure

Affects machphy mad-proxySource CVE Database V5

0

Not known to be exploited · CVSS 5.3 Medium.

Data as of 25 Oct 2026, 19:02 UTC

CVSS 3.1 base score
5.3Medium
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.2% chance of exploitation in 30 days – higher than 15% 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:L/I:N/A:N

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 10 Dec 2025

  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 2026-10-25.

What to do

Affected software

ProductAffectedFixed in
PyPImad-proxypkg:pypi/mad-proxyOther threatsAffected
  • <=0.3
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. Immediately assess the deployment of mad-proxy within your environment and identify all instances running version 0.3 or below. 2. Restrict mad-proxy usage to highly trusted network segments where exposure risk is minimized. 3. Implement network-level controls such as firewall rules and segmentation to limit access to mad-proxy and reduce attack surface. 4. Deploy additional monitoring solutions (e.g., IDS/IPS, network traffic analysis) to detect anomalous traffic patterns that may indicate bypass attempts. 5. Consider temporarily replacing mad-proxy with alternative, well-maintained proxy solutions that provide robust interception and filtering capabilities. 6. Enforce strict TLS inspection policies and certificate pinning where feasible to reduce the risk of unmonitored HTTPS traffic. 7. Maintain rigorous logging and audit trails for all proxy traffic to facilitate incident investigation. 8. Stay informed on vendor updates and apply patches promptly once a fix becomes available. 9. Conduct regular security assessments and penetration tests focusing on proxy infrastructure to identify potential bypasses or weaknesses. 10. Educate security teams about this vulnerability and incorporate it into threat modeling and risk management processes.

Description

mad-proxy is a Python-based HTTP/HTTPS proxy server for detection and blocking of malicious web activity using custom security policies. Versions 0.3 and below allow attackers to bypass HTTP/HTTPS traffic interception rules, potentially exposing sensitive traffic. This issue does not have a fix at the time of publication.

References

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