Unsafe Deserialization in picklescan (CVE-2025-71362)
Summary
Vulnerability in picklescan (CVE-2025-71362). Confidential information can be exposed externally. Exploitable via numpy.f2py.crackfortran. Mitigation: upgrade to 0.0.33 or later.
Original description
The description as published by the source.
Summary
An unsafe deserialization vulnerability allows an attacker to execute arbitrary code on the host when loading a malicious pickle payload from an untrusted source.
Details
The numpy.f2py.crackfortran module exposes many functions that call eval on arbitrary strings of values. This is the case for getlincoef and _eval_length. This list is probably not exhaustive.
According to https://numpy.org/doc/stable/reference/security.html#advice-for-using-numpy-on-untrusted-data, the whole numpy.f2py should be considered unsafe when loading a pickle.
PoC
from numpy.f2py.crackfortran import getlincoef
class EvilClass:
def __reduce__(self):
payload = "__import__('os').system('echo \"successful attack\"')"
return getlincoef, (payload, [])
Impact
Who is impacted? Any organization or individual relying on picklescan to detect malicious pickle files from untrusted sources.
What is the impact? Attackers can embed malicious code in pickle file that remains undetected but executes when the pickle file is loaded.
Supply Chain Attack: Attackers can distribute infected pickle files across ML models, APIs, or saved Python objects.
Note
The problem was originally reported to the joblib project, but this was deemed unrelated to joblib itself. However, I checked that picklescan was indeed vulnerable.
Source: NIST National Vulnerability Database NVD GitHub Advisory
Auto-generated summary
Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.
A vulnerability tracked as CVE-2025-71362 has been found in picklescan.
Attackers can target a specific entry point like numpy.f2py.crackfortran over the network to misuse the product.
Confidential information can be exposed externally. CVSS score: 8.1/10.
What to do: upgrade picklescan to 0.0.33 or later.
If unsure, ask your IT team or search "picklescan CVE-2025-71362" on the vendor's site.
CVE-2025-71362 (picklescan) — CWE-502 / CVSS v3 8.1
Attack vector: remote (network-reachable) / unauthenticated
Attack surface: numpy.f2py.crackfortran / eval / getlincoef / _eval_length
Patched: 0.0.33 — apply immediately
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.
Unsafe deserialization (CWE-502) exists in picklescan. Attackers reach the vulnerable code path via numpy.f2py.crackfortran without authentication.
Check the vendor advisory for the affected versions of picklescan. Attack surface: numpy.f2py.crackfortran / eval / getlincoef / _eval_length.
Severity: High (CVSS 8.1/10). Confidential information can be exposed externally.
Update to 0.0.33.
Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.
Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Run grep -r 'picklescan' . against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.
Response actions
Concrete steps and command examples for SOC/SRE teams to execute in order
-
1Identify exposure identify
grep -r 'picklescan' . | grep -v node_modulesリポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で
picklescanを grep し、稼働しているサービス・バージョンを把握する。 -
2Apply patch patch
Upgrade picklescan to 0.0.33ステージング環境で 0.0.33 に上げて回帰テスト → 本番反映。回帰テストはアプリの主要ハッピーパスを含めること。
-
3Post-deployment verification verify
Confirm patched version is live in productionパッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番ではアクセスログ・WAF でアラート再発が無いか継続監視。
Affected packages
References
- package github.com
- web github.com
- web disclosure@vulncheck.com
- web nvd.nist.gov
- web github.com
- web github.com
- web github.com
- web github.com