Security readout for executives and security teams
Plain-English summary
Fickling is meant to help identify dangerous Python pickle files. In affected versions, it can underrate malicious pickles that use Python’s runpy functions. If teams trust that rating before deserializing a pickle, attacker-controlled code could run. The vendor patched this in version 0.1.7.
Executive priority
Prioritize remediation where Fickling protects automated ingestion of untrusted pickle files, especially in ML, data science, CI, or artifact-processing workflows. Patch promptly, but urgency is lower where Fickling is not used or pickle inputs are fully trusted.
Technical view
CVE-2026-22606 affects trailofbits/fickling before 0.1.7. The analyzer does not classify runpy.run_path() or runpy.run_module() usage as overtly malicious, producing SUSPICIOUS instead. In workflows using Fickling as a security gate for pickle deserialization, this misclassification can enable unsafe deserialization and code execution. Mapped weaknesses include CWE-184 and CWE-502.
Likely exposure
Exposure is likely limited to products, pipelines, or internal tools that use Fickling versions below 0.1.7 to assess pickle safety before deserialization. General Python use is not affected unless Fickling is part of the pickle handling workflow.
Exploitation context
The source bundle does not show CISA KEV listing or cited active exploitation. The risk depends on an attacker getting a crafted pickle into a workflow where users or automation trust Fickling’s SUSPICIOUS result enough to deserialize it.
Researcher notes
This is a detection bypass, not a standalone vulnerability in Python’s pickle module. The key issue is trust boundary failure: Fickling’s classification may influence a later unsafe deserialization decision. Evidence provided confirms affected versions below 0.1.7 and patch availability in 0.1.7.
Mitigation direction
- Upgrade Fickling to version 0.1.7 or later.
- Inventory applications and pipelines that deserialize Python pickle data.
- Do not rely on Fickling below 0.1.7 as the sole deserialization gate.
- Review vendor advisory and release notes for any additional guidance.
Validation and detection
- Check installed Fickling versions in applications, virtual environments, and build images.
- Confirm dependency manifests require Fickling 0.1.7 or later.
- Identify workflows where pickle files are accepted from untrusted sources.
- Verify pickle deserialization decisions do not treat SUSPICIOUS as safe.
Public sources used
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
Conservative CVE-to-ATT&CK context
These mappings and lookup hints may be relevant to the vulnerability behavior, CWE, affected product, or exposure path. Glexia-inferred context is not an official MITRE, ATT&CK, CWE, or CVE Program mapping.
ATT&CK lookup starting points
Use these exact CWE pages and searches to review the Glexia ATT&CK library from this CVE's weakness and description context.
CWE-184: Exact CWE lookup
Use the exact CWE identifier as the starting point before reviewing related ATT&CK behavior. Open the exact CWE lookup page first, then review the ATT&CK searches from that MITRE weakness context. This is a Glexia lookup hint, not an official ATT&CK mapping.
Open ATT&CK lookupCWE-502: Code execution behavior lookup
Code execution and unsafe deserialization weaknesses often justify reviewing execution behavior and process telemetry. Open the exact CWE lookup page first, then review the ATT&CK searches from that MITRE weakness context. This is a Glexia lookup hint, not an official ATT&CK mapping.
Open ATT&CK lookupCVE-2026-22606 mapping review
Open the CVE-to-ATT&CK bridge for reviewed, inferred, or future official mappings tied to this CVE.
Open ATT&CK lookup- Severity
- High
- CVSS
- 8.9 (4.0)
- Known Exploited
- No
- Published
Vector: 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
CNA and ADP enrichment extracted from CVE v5
These fields come from the CVE record and ADP containers, not from Glexia's Take. They preserve time-varying source decisions such as CISA SSVC, KEV status, CVSS metrics, and provider references.
CVSS vector scores
1 official scoreWe collect every scored CVSS vector available in the official CNA and ADP containers. When more than one version is present, the table keeps the source vectors side by side instead of collapsing them into the highest score.
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——Primary CVE scoreVulnerability scoring details
Base CVSS 4.0 score
8.9HighVector: 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
Source materials
- CVE List V5 sourceCVE List V5
- https://github.com/trailofbits/fickling/security/advisories/GHSA-wfq2-52f7-7qvjCVE reference · x_refsource_CONFIRM
- https://github.com/trailofbits/fickling/commit/9a2b3f89bd0598b528d62c10a64c1986fcb09f66CVE reference · x_refsource_MISC
- https://github.com/trailofbits/fickling/releases/tag/v0.1.7CVE reference · x_refsource_MISC
Products and packages named in the record
CWE details
CWE links open Glexia weakness intelligence pages with official CWE context, developer remediation guidance, and related CVE mappings.
Incomplete List of Disallowed Inputs
Incomplete List of Disallowed Inputs represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.
Deserialization of Untrusted Data
Deserialization of Untrusted Data represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.