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VulnerabilityPublished Updated

CVE-2026-33155: seperman deepdiff · Uncontrolled Resource Consumption

Affects seperman deepdiffSource CVE Database V5

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Not known to be exploited · CVSS 8.7 High : upgrade to 8.6.2 soon.

Data as of 1 Nov 2026, 11:02 UTC

CVSS 4.0 base score
8.7High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.4% chance of exploitation in 30 days – higher than 39% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 8.6.2
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 20 Mar 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponized: 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 1 Nov 2026.

What to do

Upgrade seperman deepdiff to 8.6.2.

Affected software

ProductAffectedFixed in
sepermandeepdiffAffected
  • >=5.0.0 <8.6.2
Fixed in
  • 8.6.2
PyPIdeepdiffpkg:pypi/deepdiffOther threatsAffected
  • >=5.0.0 <8.6.2
Fixed in
  • 8.6.2

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

  1. Upgrade immediately to deepdiff version 8.6.2 or later, where this vulnerability is patched.
  2. Avoid unpickling data from untrusted or unauthenticated sources; treat all pickle data as potentially malicious.
  3. Implement strict input validation and sanitization for any data that will be unpickled, including size and content checks.
  4. Consider replacing pickle-based data interchange with safer serialization formats such as JSON or protobuf that do not allow arbitrary code execution or resource exhaustion.
  5. Use application-level resource limits (e.g., memory quotas, container limits) to mitigate impact if untrusted pickle data must be processed.
  6. Monitor application logs and system metrics for unusual memory usage spikes that could indicate exploitation attempts.
  7. Employ runtime protections such as sandboxing or process isolation to limit the blast radius of a potential DoS attack.
  8. Educate developers and DevOps teams about the risks of untrusted pickle data and enforce secure coding practices around deserialization.
  9. Review and audit all code paths that invoke deepdiff’s pickle_load or similar unpickling functions to ensure they do not process untrusted input.
  10. If upgrading is not immediately possible, consider patching or monkey-patching the _RestrictedUnpickler to validate constructor arguments or limit memory allocation.

Description

DeepDiff is a project focused on Deep Difference and search of any Python data. From version 5.0.0 to before version 8.6.2, the pickle unpickler _RestrictedUnpickler validates which classes can be loaded but does not limit their constructor arguments. A few of the types in SAFE_TO_IMPORT have constructors that allocate memory proportional to their input (builtins.bytes, builtins.list, builtins.range). A 40-byte pickle payload can force 10+ GB of memory, which crashes applications that load delta objects or call pickle_load with untrusted data. This issue has been patched in version 8.6.2.

References

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