Security readout for executives and security teams
Plain-English summary
CVE-2025-71367 affects picklescan, a tool intended to detect unsafe Python pickle content. Older versions may miss a malicious pattern, so a file that appears to pass scanning could still run attacker-controlled code when later loaded by Python pickle processing.
Executive priority
Treat as high priority if the organization handles third-party pickle or model files. The business risk is code execution through a trusted scanning workflow, but urgency depends on whether untrusted artifacts are loaded.
Technical view
picklescan before 0.0.34 reportedly fails to detect _operator.attrgetter calls in pickle payload reduce methods. This detection bypass is classified as CWE-502 and can lead to arbitrary code execution when a crafted pickle is processed with pickle.load(). CVSS 3.1 score is 8.1 high.
Likely exposure
Exposure is most likely where picklescan is used to screen pickle or model artifacts from users, partners, public repositories, CI pipelines, or automated ingestion before those files are loaded by application code or tooling.
Exploitation context
The source bundle does not report KEV listing or confirmed active exploitation. Exploitation requires a victim workflow that accepts a crafted pickle file and later loads it after relying on vulnerable picklescan results.
Researcher notes
Evidence is limited to the provided CVE, GitHub advisory, and VulnCheck advisory metadata. No exploit-in-the-wild claim is provided. Focus review on trust boundaries where picklescan output gates subsequent pickle deserialization.
Mitigation direction
- Upgrade picklescan according to the GitHub advisory, prioritizing versions before 0.0.34.
- Avoid loading untrusted pickle files, even after scanning.
- Add provenance controls for model and pickle artifacts.
- Quarantine externally supplied pickle files pending vendor-guided remediation.
- Use additional sandboxing around workflows that must process pickle content.
Validation and detection
- Inventory applications, CI jobs, and notebooks that use picklescan.
- Identify deployed picklescan versions and flag versions before 0.0.34.
- Trace whether scanned pickle files are later processed with pickle.load().
- Review artifact sources for external or unauthenticated submissions.
- Confirm compensating controls do not rely solely on picklescan detection.
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-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 lookupExecution behavior lookup
The CVE wording references code or command execution, so execution technique review may help defensive triage. This is a Glexia inferred lookup path, not an official MITRE, ATT&CK, or CVE Program mapping.
Open ATT&CK lookupCVE-2025-71367 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
- 8.1 (3.1)
- Known Exploited
- No
- Published
Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N
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.
SSVC decision data
CVSS vector scores
2 official scoresWe 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:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N2.85.2VulnCheckCVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N——VulnCheckVulnerability scoring details
Base CVSS 4.0 score
7.6HighVector: CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N
Base CVSS 3.1 score
8.1HighVector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:N
Vulnerability timeline
Timeline events are normalized from CVE metadata, CNA source timelines, ADP timelines, and KEV metadata when present.
- CVE reservedCVE Program
The CVE ID was reserved by the assigning CNA.
- CVE publishedCVE Program
The CVE record was published.
- CVE updatedCVE Program
The CVE record metadata indicates this as the latest update time.
ADP provider summaries
Source materials
- CVE List V5 sourceCVE List V5
- GitHub Security Advisory (GHSA-46h3-79wf-xr6c)CVE reference, VulnCheck · vendor-advisory
- VulnCheck Advisory: picklescan - Remote Code Execution via _operator.attrgetter Detection BypassCVE reference, VulnCheck · third-party-advisory
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.
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.