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CVE-2025-58367VulnerabilityPublished Updated

CVE-2025-58367: seperman deepdiff · Mass Assignment

Affects seperman deepdiffSource CVE Database V5

0

Not known to be exploited · CVSS 10.0 Critical · fixed in 8.6.1 : patch seperman deepdiff as a priority.

Data as of 26 Oct 2026, 06:26 UTC

CVSS 4.0 base score
10.0Critical
How severe the flaw is on the 0–10 CVSS scale.
EPSS
1.1% chance of exploitation in 30 days – higher than 67% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 8.6.1
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 5 Sep 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-26.

What to do

AI-suggested

European organizations should immediately audit their software dependencies to identify any usage of DeepDiff versions between 5.0.0 and 8.6.0. The primary mitigation is to upgrade to DeepDiff version 8.6.1 or later, where the vulnerability has been fixed. For environments where immediate upgrade is not feasible, organizations should implement strict input validation and sanitization on any user-controlled data passed to the Delta class or related DeepDiff functionalities. Employ application-level sandboxing or runtime restrictions to limit the impact of potential code execution. Monitoring and logging of deserialization activities can help detect exploitation attempts. Additionally, organizations should review their software supply chain and third-party applications to identify indirect usage of vulnerable DeepDiff versions. Employing Web Application Firewalls (WAFs) or Intrusion Detection Systems (IDS) with signatures targeting this vulnerability can provide temporary protection. Finally, organizations should ensure that their incident response teams are prepared to handle potential exploitation scenarios involving Python deserialization vulnerabilities.

Description

DeepDiff is a project focused on Deep Difference and search of any Python data. Versions 5.0.0 through 8.6.0 are vulnerable to class pollution via the Delta class constructor, and when combined with a gadget available in DeltaDiff, it can lead to Denial of Service and Remote Code Execution (via insecure Pickle deserialization) exploitation. The gadget available in DeepDiff allows `deepdiff.serialization.SAFE_TO_IMPORT` to be modified to allow dangerous classes such as posix.system, and then perform insecure Pickle deserialization via the Delta class. This potentially allows any Python code to be executed, given that the input to Delta is user-controlled. Depending on the application where DeepDiff is used, this can also lead to other vulnerabilities. This is fixed in version 8.6.1.

References

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