CVE-2026-22612: trailofbits fickling · Deserialization of Untrusted Data
Affects trailofbits ficklingSource CVE Database V5
Not known to be exploited · CVSS 8.9 High : upgrade to 0.1.7 soon.
Data as of 26 Oct 2026, 06:26 UTC
- 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:PExploitation evidence
Disclosed: evidence found.
CVE published 10 Jan 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by 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
| Product | Affected | Fixed in |
|---|---|---|
| trailofbitsfickling | Affected
| Fixed in
|
PyPIficklingpkg:pypi/ficklingOther threats | Affected
| 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 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.