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Treat every package name suggested by an AI coding assistant as untrusted until it has been verified against the intended registry and reviewed. A name that is absent today can be registered by an attacker tomorrow; if an agent or developer installs it, package code may run in a build environment with access to credentials or release artifacts. A registry lookup can catch a name that remains unavailable, but it cannot establish that an existing package is legitimate.
How package hallucinations become a supply-chain risk
A package hallucination is a dependency name that a code-generating model emits even though it is not a real package in the relevant registry, or a package identity that does not match the intended dependency. The security risk escalates if an attacker registers a plausible hallucinated name and publishes malicious code under it. This variant is known as slopsquatting. OWASP illustrates the idea with the hypothetical contrast between node-fetch-promise and the real node-fetch; that example is not a claim that the illustrative name is malicious. See the OWASP NPM Security Cheat Sheet.
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- An AI assistant suggests a plausible dependency name.
- An attacker predicts or observes names likely to be generated and registers one with malicious content.
- Generated code or an autonomous agent requests the package.
- The package manager downloads it; installation may execute lifecycle scripts.
- Malicious code can then reach the developer machine, CI worker, credentials, or downstream release process.
The critical distinction is that absence and legitimacy are different questions. A 404 from the intended registry means the name was not available there at the time checked. A successful lookup says only that a package record exists. The USENIX Security 2025 study notes that an attacker may have already published a hallucinated name, so cross-referencing a generated name against a list of known packages can miss the attack. Open-source availability is not proof that hosted code is trustworthy.
This threat overlaps with, but is not identical to, other package risks:
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- Typosquatting: an attacker targets a person who mistypes a known package name.
- Dependency confusion: a public package competes with a package intended to resolve privately; private scopes and internal-only routing are relevant defenses.
- Maintainer compromise: an attacker changes a package that was previously legitimate.
All meet at the package-manager boundary, but no single control addresses every cause. OWASP discusses dependency-chain controls in its CI/CD dependency-chain guidance; npm also describes registry threats in Threats and Mitigations.
What the published prevalence figures do—and do not—show
The Cloud Security Alliance’s 2026 summary of the USENIX Security 2025 study reports that 440,445 of 2.23 million generated samples (19.7%) contained at least one hallucinated package name. The researchers generated samples using 16 code-generating models across Python and JavaScript. The summary reports cohort averages of 21.7% for the open-source models and 5.2% for commercial models studied. These are results for the tested model versions, prompts, and evaluation setup—not current prevalence estimates for all AI coding tools or today’s model versions. See the Cloud Security Alliance Lab Space summary and the USENIX Security 2025 paper.
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The paper’s released Python and JavaScript datasets contain 19,500 coding prompts and 586,000 generated coding samples. Those public-dataset counts are distinct from the 2.23 million samples in the CSA summary’s study-wide figure, so they should not be treated as the same denominator. Neither figure establishes how often current developers encounter hallucinated dependencies in production projects.
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Require explicit approval or an allowlist
Do not let an AI agent install arbitrary packages autonomously. Require human approval for each proposed dependency or restrict additions to an organization-maintained allowlist. Before approval, check that the package is in the exact ecosystem and registry the project uses, and that its documented purpose and implementation match the task. An allowlist reduces surprise additions, but it needs an exception process and a clear owner for updates. OWASP’s Secure Coding with AI guidance covers validation and approval controls for AI-assisted dependencies.
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Review identity and history, not just whether the name exists
Inspect the registry record, publisher or maintainer identity, creation date, release and maintainer history, source repository, code, and package behavior. Check whether the package actually fits the intended function. OWASP flags signals such as a very recent creation date, low download count, or a single maintainer with little history; these warrant scrutiny but are not proof of malice. A name-exists check alone cannot distinguish an attacker’s package from a legitimate one.
Make dependency resolution controlled and reproducible
Lock and review the resolved dependency set
- Commit the package manager’s lockfile and configure CI to install in its frozen or locked mode.
- Require code review for changes to dependency manifests and lockfiles.
- Prefer vetted, explicitly approved versions over floating to the latest release.
- Use package-manager integrity data or explicit hashes where supported by the ecosystem and workflow.
These measures make resolution more repeatable and unexpected artifact changes easier to detect. They do not establish that a dependency was appropriate or benign when it was first approved, and they cannot guarantee that future releases or transitive dependencies will remain safe.
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Route downloads through a controlled registry path
Configure developers and CI to obtain third-party packages through an internal proxy or curated repository that can enforce policy and log requests. Route private scoped packages exclusively to the internal registry to reduce dependency-confusion exposure. Where appropriate, commit repository-local package-manager configuration so a machine-level setting cannot silently change resolution. Do not publish internal package names to public registries. These measures centralize resolution; they do not make every package served by a proxy safe without review and policy.
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Package installation can execute lifecycle scripts, so treat dependency installation as code execution rather than a passive download. Run install and build steps in isolated, disposable environments. Withhold signing keys, deployment tokens, and unrelated secrets from dependency-install stages; restrict network egress and job permissions to what is required. If you suspect a package or build step exposed credentials, rotate the affected credentials and assess what they could access. OWASP’s CI/CD guidance and the UK National Cyber Security Centre’s dependency-management guidance cover supply-chain exposure and containment principles.
Monitor changes and prepare a response path
- Review dependency diffs, especially unexpected new package names and changes to lockfiles or registry configuration.
- Monitor CI activity, network traffic, and credential use for behavior that does not fit the job.
- Use dependency scanning or software composition analysis to flag known vulnerable or malicious components.
- Maintain a way to quarantine a package or version, rebuild from a known-good lockfile, and rotate exposed secrets.
Scanners can only flag issues represented in their data or detection logic. A newly registered malicious package may not yet have a signature, so scanning complements—not replaces—approval, identity review, controlled resolution, and isolation.
Match each control to the risk it actually reduces
| Control | What it helps with | What it does not prove |
|---|---|---|
| Registry existence lookup | Catches names still absent from the intended registry | That a registered package is legitimate or safe |
| Publisher, history, and code review | Surfaces suspicious identity, recency, or mismatch signals | That future releases or transitive dependencies will remain benign |
| Human approval or allowlist | Prevents an agent from silently adding arbitrary names | That every approved dependency is uncompromised |
| Lockfile and integrity check | Makes resolution reproducible and can detect unexpected artifact changes | That the selected dependency was appropriate or non-malicious when approved |
| Internal proxy and scoped routing | Centralizes policy and reduces unsafe resolution paths, including some dependency-confusion exposure | That every package served by the proxy is safe without review and policy |
| Isolation and least privilege | Reduces the secrets and systems reachable by install-time code | That malicious code cannot run or cause harm |
| Vulnerability or malware scanning | Flags issues represented in the scanner’s data or detection logic | That a newly published or previously unknown package is clean |
Think of the controls as layers at different points: approval checks the proposed name and purpose before installation; registry policy governs where resolution can go; lockfiles constrain version selection; isolation limits impact if a gate fails; and monitoring helps detect activity afterward. A hash can verify that an artifact matches an expected value, but it cannot decide whether the dependency should have been approved in the first place.
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