Security readout for executives and security teams
Plain-English summary
picklescan is meant to identify dangerous Python pickle files. This flaw lets a malicious pickle evade detection by using a specific PyTorch-related function path. If someone later loads that file, attacker-controlled code could run. The practical risk is highest in AI, ML, and model-sharing workflows that process untrusted pickle artifacts.
Executive priority
Treat this as a high-priority AI supply-chain issue where pickle files enter business workflows. It is not listed as actively exploited in the provided sources, but successful abuse could run attacker code after a false-negative scan.
Technical view
CVE-2025-71366 is a CWE-502 unsafe deserialization detection bypass in picklescan before 0.0.28. Malicious pickle files can hide calls to torch.utils.bottleneck.__main__.run_cprofile, bypassing picklescan checks and enabling arbitrary code execution when a victim loads the pickle. CVSS is 8.1, network-adjacent delivery with required user interaction.
Likely exposure
Organizations using picklescan below 0.0.28 to vet pickle files, ML models, or shared artifacts are most exposed, especially where files come from external users, partners, public repositories, or automated pipelines.
Exploitation context
The bundle does not report active exploitation and KEV is false. Exploitation depends on a victim or workflow accepting a malicious pickle, picklescan missing it, and the file later being loaded by Python tooling.
Researcher notes
The key security boundary is misplaced trust in picklescan results. Focus review on pickle ingestion, model artifact provenance, dependency versions, and whether downstream systems load files automatically after scanning. Evidence provided does not include exploit telemetry or broader affected products.
Mitigation direction
- Upgrade picklescan deployments using versions before 0.0.28.
- Review vendor advisory guidance before relying on scan results.
- Block or quarantine untrusted pickle files where practical.
- Require safer model formats when external artifact exchange is possible.
- Add approval gates before loading externally supplied pickle files.
Validation and detection
- Inventory picklescan versions in dependency manifests and runtime images.
- Identify workflows that scan or load pickle files from untrusted sources.
- Confirm whether any environment uses picklescan before 0.0.28.
- Review artifact intake logs for externally supplied pickle files.
- Verify updated scanners are deployed in CI and production pipelines.
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-2025-71366 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-4r9r-ch6f-vxmx)CVE reference, VulnCheck · vendor-advisory
- VulnCheck Advisory: picklescan - Arbitrary Code Execution via torch.utils.bottleneck.__main__.run_cprofileCVE 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.