Quick answer
Direct answer
Risk scores
| CVSS metric | What it means |
|---|---|
| Attack vector (AV:N) | Network: reachable remotely |
| Attack complexity (AC:L) | Low complexity |
| Attack requirements (AT:N) | No attack requirements |
| Privileges required (PR:N) | No privileges required |
| User interaction (UI:N) | No user interaction |
| Confidentiality (VC:H) | High confidentiality impact |
| Integrity (VI:H) | High integrity impact |
| Availability (VA:H) | High availability impact |
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/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
About Trailofbits Fickling
CVE-2026-22612 affects Trailofbits Fickling, a product from Trailofbits. Before acting, confirm where Trailofbits Fickling runs in your estate, who owns it and whether it is reachable from the internet, because exposure decides real risk more than the score alone.
What the flaw is
In plain terms: 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.
The weakness class is Deserialization of Untrusted Data. The application rebuilds objects from attacker controlled data, which can run code.
Based on its CVSS vector, the flaw can be reached over the network, needs no login, and needs no user interaction. Apply the vendor fix and confirm exposure on internet facing and business critical assets first.
Affected versions and timeline
| Field | Detail |
|---|---|
| Product | Trailofbits Fickling |
| Affected versions | Fickling before 0.1.7 |
| Published | Jan 10, 2026 |
| Last modified | Jun 17, 2026 |
| Added to CISA KEV | Not listed |
| Assigning CNA | security-advisories@github.com |
How to detect it
- Inventory every instance of Trailofbits Fickling and record the running version against the affected range above.
- Check external attack surface scans for internet facing instances of the component.
- Review logs on affected systems for unusual requests, errors or new processes around the vulnerable function.
- Confirm with an authenticated vulnerability scan once your scanner has a check for this CVE.
How to fix it
- Apply the fixed version of Trailofbits Fickling named in the vendor advisory.
- If patching must wait, restrict network access to the affected service and put it behind authentication or a web application firewall rule.
- Rescan after the change to prove the exposure is gone, then close the ticket.
CTEM action plan
| CTEM stage | What to do for this CVE |
|---|---|
| Scope | Add every business service that depends on Trailofbits Fickling to the current CTEM cycle. |
| Discover | Find all instances, including shadow and cloud deployments, and record versions and exposure. |
| Prioritize | Rank using EPSS and CVSS together with asset exposure and business impact. |
| Validate | Confirm the flaw is reachable and exploitable in your environment and that compensating controls work. |
| Mobilize | Assign the fix to the asset owner with a due date matched to the priority, then verify closure. |
CWE References
- CWE-502: Deserialization of Untrusted Data More CVEs with this weakness
Technical References
Frequently asked questions
Related CVEs
In Trail of Bits fickling versions up to and including 0.1.11, the UnsafeImportsML analysis pass unconditionally calls AnalysisContext.shorten_code(node) on every import node it inspects, regardless of whether the import is flagged as unsafe. This call registers the shortened code representation in the shared AnalysisContext.reported_shortened_code set. When the MLAllowlist analysis pass subsequently runs, it calls the same shorten_code() method, receives already_reported=True for every import, and executes a continue statement that skips its allowlist check entirely. This renders MLAllowlist dead code for all imports — it never evaluates whether an import is in the ML allowlist or not. The MLAllowlist pass was designed to catch imports of modules outside the known-safe ML ecosystem (torch, numpy, transformers, etc.) that slip past the UnsafeImports denylist. With MLAllowlist inoperative, any standard library module not in the UNSAFE_IMPORTS denylist can be invoked via pickle deserialization while fickling's check_safety() returns LIKELY_SAFE. The fickling.load() API chains check_safety() into pickle.loads() as an explicit security gate, meaning a LIKELY_SAFE verdict causes the payload to be deserialized and executed. The root cause is shared mutable state between independently-correct analysis passes — UnsafeImportsML works as designed in isolation, MLAllowlist works as designed in isolation, but the shared reported_shortened_code set causes UnsafeImportsML to poison MLAllowlist's deduplication logic.
Fickling is a Python pickling decompiler and static analyzer. Prior to version 0.1.7, the unsafe_imports() method in Fickling's static analyzer fails to flag several high-risk Python modules that can be used for arbitrary code execution. Malicious pickles importing these modules will not be detected as unsafe, allowing attackers to bypass Fickling's primary static safety checks. This issue has been patched in version 0.1.7.
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.
Fickling is a Python pickling decompiler and static analyzer. Fickling versions up to and including 0.1.6 do not treat Python's cProfile module as unsafe. Because of this, a malicious pickle that uses cProfile.run() is classified as SUSPICIOUS instead of OVERTLY_MALICIOUS. If a user relies on Fickling's output to decide whether a pickle is safe to deserialize, this misclassification can lead them to execute attacker-controlled code on their system. This affects any workflow or product that uses Fickling as a security gate for pickle deserialization. This issue has been patched in version 0.1.7.
Fickling is a Python pickling decompiler and static analyzer. Fickling versions up to and including 0.1.6 do not treat Python’s runpy module as unsafe. Because of this, a malicious pickle that uses runpy.run_path() or runpy.run_module() is classified as SUSPICIOUS instead of OVERTLY_MALICIOUS. If a user relies on Fickling’s output to decide whether a pickle is safe to deserialize, this misclassification can lead them to execute attacker-controlled code on their system. This affects any workflow or product that uses Fickling as a security gate for pickle deserialization. This issue has been patched in version 0.1.7.
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