CVE-2025-71354: picklescan - Remote Code Execution via idlelib.debugobj.ObjectTreeItem.SetText
picklescan before 0.0.29 fails to detect malicious pickle files that exploit idlelib.debugobj.ObjectTreeItem.SetText function in reduce methods. Attackers can craft pickle files with embedded code that bypasses picklescan detection and executes arbitrary commands when pickle.load() is called.
Security readout for executives and security teams
Plain-English summary
CVE-2025-71354 is a high-severity detection bypass in picklescan before 0.0.29. A malicious Python pickle file can evade picklescan checks and still execute code later if an application loads it with pickle.load(). The business risk is highest where teams process externally supplied model, data, or artifact files.
Executive priority
Treat this as a high-priority supply-chain and data-ingestion risk if the organization handles pickle-based artifacts. Prioritize environments where external files are screened automatically and then loaded. If picklescan is not deployed, direct exposure to this specific scanner bypass is unlikely.
Technical view
The issue is CWE-502 unsafe deserialization exposure: picklescan missed malicious reduce-method usage involving idlelib.debugobj.ObjectTreeItem.SetText. The flaw affects picklescan versions before 0.0.29 per the provided description. The CVSS 3.1 score is 8.1, with network attack vector, low complexity, no privileges, and required user interaction.
Likely exposure
Exposure is likely in Python workflows that use picklescan to screen pickle files, then deserialize accepted files. Highest-risk paths include artifact ingestion, ML/model file handling, uploaded data bundles, CI pipelines, and internal tools that trust scan results before calling pickle.load().
Exploitation context
The provided bundle does not show CISA KEV listing or confirmed active exploitation. Exploitation requires a malicious pickle to reach a workflow where a user or system later deserializes it. The vulnerability is serious because the scanner may provide false assurance before execution occurs.
Researcher notes
The key uncertainty is operational exposure, not the bug class. The source bundle identifies the bypass primitive and affected scanner version range, but does not provide active exploitation evidence. Researchers should focus validation on scanner reliance, downstream deserialization, and whether 0.0.29 or later is consistently deployed.
Mitigation direction
Upgrade picklescan to 0.0.29 or later where used.
Do not deserialize untrusted pickle files, even after scanning.
Review vendor advisory guidance for any additional fixed-version or workaround details.
Restrict pickle ingestion to trusted sources and controlled repositories.
Add compensating controls around artifact upload and model import workflows.
Validation and detection
Inventory projects, containers, and CI jobs using picklescan.
Confirm installed picklescan versions are 0.0.29 or later.
Identify workflows that call pickle.load() after scanner approval.
Review recent pickle artifact sources for untrusted uploads or external submissions.
Add regression coverage for scanner-gated deserialization paths.
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
Potential ATT&CK relevance
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 · medium confidence lookup
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.
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.
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.
2CVSS vectors
3Timeline events
1ADP providers
3Source links
SSVC decision data
CISA-ADPCISA Coordinator
Timestamp
Version
2.0.3
Exploitation: noneAutomatable: noTechnical Impact: total
CVSS vector scores
2 official scores
We 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.
CWE links open Glexia weakness intelligence pages with official CWE context, developer remediation guidance, and related CVE mappings.
CWE-502 · source CWE mapping
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.