Security readout for executives and security teams
Plain-English summary
A flaw in picklescan means malicious pickle files could pass detection and later run attacker-controlled code when deserialized. The business risk is highest where teams rely on picklescan as a gate before loading untrusted pickle artifacts.
Executive priority
Prioritize remediation where picklescan protects production, ML, or data-processing workflows that accept external pickle files. This is high severity, but current evidence does not establish active exploitation.
Technical view
picklescan before 0.0.30 fails to detect cProfile.run calls in pickle reduce methods. This is a CWE-502 unsafe deserialization issue with CVSS 8.1. The source bundle describes remote crafting of malicious pickle files, but execution occurs when a victim deserializes the file.
Likely exposure
Exposure is likely limited to environments using affected picklescan versions to inspect pickle files, especially where files come from external or semi-trusted sources and are later deserialized.
Exploitation context
The source bundle does not show KEV listing or confirmed active exploitation. The CVSS vector indicates network-reachable attack delivery, low complexity, no privileges, and required user interaction through processing or loading a malicious file.
Researcher notes
The key detection gap is cProfile.run inside pickle reduce methods. Validate affected scope against actual picklescan use, not just package presence. Do not assume broader product impact beyond picklescan based on the provided sources.
Mitigation direction
- Upgrade picklescan from versions before 0.0.30 per vendor guidance.
- Avoid deserializing pickle files from untrusted or unauthenticated sources.
- Add independent controls before loading pickle artifacts in pipelines.
- Review vendor advisory for any additional version-specific remediation.
- Treat previously accepted pickle files as untrusted until revalidated.
Validation and detection
- Inventory systems and pipelines using picklescan.
- Confirm installed picklescan versions are 0.0.30 or later.
- Identify workflows that deserialize pickle files after scanning.
- Review recent externally sourced pickle artifacts for revalidation needs.
- Check security tooling for alerts involving unsafe pickle deserialization.
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-2025-71363 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-49gj-c84q-6qm9)CVE reference, VulnCheck · vendor-advisory
- VulnCheck Advisory: picklescan - Arbitrary Code Execution via Undetected cProfile.run in Pickle DeserializationCVE 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.