trailofbits fickling up to 0.1.6 ctypes/pydoc incomplete blacklist
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 7.4 | $0-$5k | 0.00 |
Summary
A vulnerability marked as critical has been reported in trailofbits fickling up to 0.1.6. The affected element is an unknown function of the component ctypes/pydoc. The manipulation leads to incomplete blacklist. This vulnerability is traded as CVE-2026-22608. It is possible to initiate the attack remotely. There is no exploit available. It is suggested to upgrade the affected component.
Details
A vulnerability was found in trailofbits fickling up to 0.1.6. It has been rated as critical. This issue affects an unknown code of the component ctypes/pydoc. The manipulation with an unknown input leads to a incomplete blacklist vulnerability. Using CWE to declare the problem leads to CWE-184. The product implements a protection mechanism that relies on a list of inputs (or properties of inputs) that are not allowed by policy or otherwise require other action to neutralize before additional processing takes place, but the list is incomplete, leading to resultant weaknesses. Impacted is confidentiality, integrity, and availability. The summary by CVE is:
Fickling is a Python pickling decompiler and static analyzer. Prior to version 0.1.7, both ctypes and pydoc modules aren't explicitly blocked. Even other existing pickle scanning tools (like picklescan) do not block pydoc.locate. Chaining these two together can achieve RCE while the scanner still reports the file as LIKELY_SAFE. This issue has been patched in version 0.1.7.
It is possible to read the advisory at github.com. The identification of this vulnerability is CVE-2026-22608 since 01/07/2026. The exploitation is known to be easy. The attack may be initiated remotely. No form of authentication is needed for a successful exploitation. The technical details are unknown and an exploit is not publicly available. The attack technique deployed by this issue is T1562.006 according to MITRE ATT&CK.
Upgrading to version 0.1.7 eliminates this vulnerability. The upgrade is hosted for download at github.com. Applying the patch b793563e60a5e039c5837b09d7f4f6b92e6040d1 is able to eliminate this problem. The bugfix is ready for download at github.com. The best possible mitigation is suggested to be upgrading to the latest version.
The vulnerability is also documented in the vulnerability database at EUVD (EUVD-2026-1686). Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
Product
Type
Vendor
Name
Version
License
Website
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒
CVSSv3
VulDB Meta Base Score: 7.5VulDB Meta Temp Score: 7.4
VulDB Base Score: 7.3
VulDB Temp Score: 7.0
VulDB Vector: 🔒
VulDB Reliability: 🔍
NVD Base Score: 7.8
NVD Vector: 🔒
CVSSv2
| AV | AC | Au | C | I | A |
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| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: Incomplete blacklistCWE: CWE-184 / CWE-183 / CWE-20
CAPEC: 🔒
ATT&CK: 🔒
Physical: Partially
Local: Yes
Remote: Yes
Availability: 🔒
Status: Not defined
EPSS Score: 🔒
EPSS Percentile: 🔒
Price Prediction: 🔍
Current Price Estimation: 🔒
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: UpgradeStatus: 🔍
0-Day Time: 🔒
Upgrade: fickling 0.1.7
Patch: b793563e60a5e039c5837b09d7f4f6b92e6040d1
Timeline
01/07/2026 CVE reserved01/10/2026 Advisory disclosed
01/10/2026 VulDB entry created
01/17/2026 VulDB entry last update
Sources
Product: github.comAdvisory: GHSA-5hvc-6wx8-mvv4
Status: Confirmed
CVE: CVE-2026-22608 (🔒)
GCVE (CVE): GCVE-0-2026-22608
GCVE (VulDB): GCVE-100-340379
EUVD: 🔒
Entry
Created: 01/10/2026 10:15Updated: 01/17/2026 05:46
Changes: 01/10/2026 10:15 (72), 01/10/2026 10:27 (1), 01/10/2026 11:15 (1), 01/17/2026 05:46 (11)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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