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CVE-2026-22612VulnerabilityPublished Updated

CVE-2026-22612: trailofbits fickling · Deserialization of Untrusted Data

Affects trailofbits ficklingSource CVE Database V5

0

Not known to be exploited · CVSS 8.9 High : upgrade to 0.1.7 soon.

Data as of 26 Oct 2026, 06:26 UTC

CVSS 4.0 base score
8.9High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.3% chance of exploitation in 30 days – higher than 24% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 0.1.7
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:P

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 10 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 2026-10-26.

What to do

Upgrade trailofbits fickling to 0.1.7.

Affected software

ProductAffectedFixed in
trailofbitsficklingAffected
  • <0.1.7
Fixed in
  • 0.1.7
PyPIficklingpkg:pypi/ficklingOther threatsAffected
  • <0.1.7
Fixed in
  • 0.1.7

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

AI-suggested

1. Immediately upgrade all instances of Fickling to version 0.1.7 or later to apply the patch that fixes the detection bypass. 2. Conduct a thorough audit of all deserialization processes within your environment, especially those involving Python pickle data, to identify and remediate any similar weaknesses. 3. Implement strict input validation and sanitization for any data deserialized by internal tools or applications to prevent untrusted data from being processed. 4. Employ runtime monitoring and anomaly detection to identify unusual behaviors indicative of deserialization attacks. 5. Restrict network access to systems running Fickling or related analysis tools to trusted users and networks only. 6. Educate development and security teams about the risks of unsafe deserialization and the importance of using secure coding practices. 7. Review and update incident response plans to include scenarios involving deserialization vulnerabilities. 8. Consider using alternative or additional static analysis tools that have robust protections against deserialization bypasses as a defense-in-depth measure.

Description

Fickling is a Python pickling decompiler and static analyzer. Prior to version 0.1.7, Fickling is vulnerable to detection bypass due to "builtins" blindness. This issue has been patched in version 0.1.7.

References

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