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:Draft:Zombie Dependency

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{{AFC comment|1=Medium blog is not a source. more sources needed Old-AgedKid (talk) 15:38, 16 April 2025 (UTC)}}

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{{Short description|Cybersecurity attack}}

{{Draft topics|software|computing|technology}}

{{AfC topic|other}}

Zombie Dependency{{Cite web |title=Rising from the Dead: Zombie Dependencies |url=https://ossprey.com/blog/zombie-dependency-nextjs/ |access-date=2025-04-17 |website=ossprey.com}} is a term used in cybersecurity and software development to describe a software package that remains referenced in codebases or dependency graphs despite being abandoned, orphaned, empty, or otherwise unmaintained. These dependencies often pose a supply chain security risk, as their dormant status makes them attractive targets for malicious actors seeking to hijack or republish them with malicious payloads.

Definition and Characteristics

A zombie dependency is typically characterized by one or more of the following traits:

  • No active maintainer or project owner
  • Stale repository activity, often with no commits or updates for extended periods
  • Empty or minimal content, sometimes including only placeholder files
  • No official release, or an initial version published and never updated
  • Still referenced in public or private codebases, build pipelines, or documentation

Unlike deprecated or archived projects that are marked intentionally as such, zombie dependencies often remain in a state of ambiguity—neither active nor officially retired.

Risks and Attack Surface

Zombie dependencies introduce multiple types of risks:

  • Hijacking or takeover: An attacker can claim or re-register abandoned packages on repositories like npm, PyPI, or RubyGems and insert malicious code a method similar to typosquatting or package namespace confusion {{Cite web |date=2021-09-13 |title=Detect and prevent dependency confusion attacks on npm to maintain supply chain security |url=https://snyk.io/blog/detect-prevent-dependency-confusion-attacks-npm-supply-chain-security/ |access-date=2025-04-16 |website=Snyk |language=en-US}}.
  • AI hallucinations: As noted in a Bleeping Computer article (2025){{Cite web |title=AI-hallucinated code dependencies become new supply chain risk |url=https://www.bleepingcomputer.com/news/security/ai-hallucinated-code-dependencies-become-new-supply-chain-risk/ |access-date=2025-04-16 |website=BleepingComputer |language=en-us}} and a Cornell University research paper (2025){{Citation |last1=Spracklen |first1=Joseph |title=We Have a Package for You! A Comprehensive Analysis of Package Hallucinations by Code Generating LLMs |date=2025-03-02 |arxiv=2406.10279 |last2=Wijewickrama |first2=Raveen |last3=Sakib |first3=A. H. M. Nazmus |last4=Maiti |first4=Anindya |last5=Viswanath |first5=Bimal |last6=Jadliwala |first6=Murtuza}}, generative AI models may suggest non-existent or zombie packages, leading developers to unknowingly include them in projects.
  • Silent failures: Zombie packages may contain outdated, vulnerable code, or fail quietly when APIs and integrations change.

Mitigation Strategies

Security-conscious organizations and developers are encouraged to:

  • Audit and regularly review third-party dependencies
  • Use dependency monitoring tools (e.g., Dependabot, Snyk, Ossprey)
  • Prefer well-maintained packages with active communities
  • Lock dependency versions and verify package integrity with cryptographic hashes
  • Isolate and test third-party packages in sandboxed environments before use

See also

References

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