Treat every dependency suggested by an AI coding assistant as an unverified proposal. Before you install or merge it, confirm the exact package identity in the intended registry, establish why the code needs it, inspect the complete direct and transitive dependency tree, resolve it through the expected source with a lockfile and integrity data, check current advisories, and verify publisher or build provenance when available. Then automate the repeatable checks in CI and review the manifest and lockfile diff like any other code change.
This process answers the practical question, “How do I verify dependencies introduced by AI coding assistants?” It also protects against a subtle failure: a package can exist in a public registry yet still be the wrong project, a typosquat, an abandoned library, or an unnecessarily broad addition.
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Why AI-suggested dependencies need a separate verification step
AI assistants generate plausible package names from patterns in their training data and from the wording of a prompt. They may invent a name that sounds real, confuse two projects with similar names, or select a package whose capability is much broader than the code requires. Attackers can watch for names that assistants hallucinate and register those names with malicious code. OWASP describes this as AI-assisted typosquatting: an assistant suggests a package that does not exist, then an attacker creates a package with that matching name.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsExistence and authenticity are different questions. A registry search proves only that someone published a package under that name. It does not prove that the package is maintained by the project you intended, implements the documented API, is safe to execute, or is necessary for your application.
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A USENIX Security 2025 study by Joseph Spracklen and coauthors classified 19.7% of generated package recommendations as hallucinations—440,445 out of 2.23 million generated packages in its experiments. The result covered a defined set of 16 models, Python and JavaScript, and particular prompts and methods. It is not a universal current rate for every assistant, model, language, or coding task; newer models and different prompts can behave differently.
ENISA’s March 2026 technical advisory frames the issue this way: “The use of AI-assisted development tools, particularly when most coding is delegated to AI with little or no human review (sometimes known as ‘vibe coding’), introduces new considerations in the secure use of package managers.” That warning concerns reduced review and package-management decisions, not a claim that all AI-assisted development is unsafe.
The verification standard: six questions every package must answer
- Is it the exact intended project? Confirm the spelling, namespace, registry, upstream repository, documentation, maintainers, and release history.
- Why is it needed? Identify the import or feature that requires it and check whether the standard library or an already-approved dependency is sufficient.
- What does it add? Map direct and transitive dependencies, install scripts, permissions, network behavior, and runtime scope.
- Will every developer and build get the same artifact? Resolve through the intended source, pin versions, commit the lockfile, and preserve integrity hashes where the ecosystem supports them.
- Are known issues or policy violations present? Run the ecosystem audit, consult current advisory sources, and apply your project’s severity and license policies.
- Can the artifact’s origin be checked? Validate registry signatures, publisher identity, and build provenance when available, comparing claims with the expected source revision and build process.
These checks answer different questions. A vulnerability scan cannot establish that the package is the right project. A hash cannot establish that the package is necessary or free of malicious behavior. A provenance attestation does not become trustworthy merely because it exists; its source, revision, and build claims must match your expectations.
Step 1: Inspect the AI-generated change before installing anything
Start with the proposed code and its diff, not with the package manager. Look for changes to the manifest, lockfile, import statements, shell commands, build configuration, and package-manager scripts. An assistant may have added a dependency indirectly—for example, by inserting an install command into documentation or a build script.
- Open the pull request or local diff and list every new package name, version range, source URL, and registry.
- Locate every new import or API call and record which feature it supplies.
- Ask the assistant to explain the dependency’s role, expected version, and why an existing standard-library function or approved package cannot meet the requirement.
- Verify that explanation against the code and official project documentation; treat the assistant’s explanation as a hypothesis, not evidence.
- Do not execute install or post-install commands from a new package until identity and scope checks are complete.
ENISA recommends maintaining visibility over packages selected through AI-generated code and reviewing their necessity and scope. This first pass is where you can remove an unnecessary dependency at the lowest cost.
Step 2: Verify the exact package identity in the intended registry
Search the official registry, not a copied snippet
Search the package’s exact name in the registry used by the project. Confirm the namespace, distribution name, and ecosystem because similarly named packages can exist in different registries. Compare the registry metadata with the upstream project’s documentation and repository link. The package’s README should describe the same API and purpose that appear in your code.
Check ownership and release history
Review the publisher or maintainer identity, creation date, release cadence, version history, and links to source code. Check whether the release you are about to consume belongs to the intended project and whether the repository’s tags or release artifacts correspond to that version. A very new package, a single-maintainer history, or low adoption warrants investigation, but none is proof of maliciousness. Conversely, a popular package is not automatically safe.
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Look for namespace confusion and typosquats
Compare the proposed spelling character by character with the name documented by the project. Search for near-spelling alternatives, hyphenation changes, substituted characters, and similarly named namespaces. Confirm the package manager’s source-selection rules so a private package name cannot be silently resolved from an unintended public registry, or vice versa.
OWASP recommends checking registry existence, download count, maintainer history, and creation date. Treat these as signals to investigate rather than as a mechanical trust score. Adoption numbers can be manipulated, and an old package can still be compromised or abandoned.
Step 3: Establish necessity and limit the scope
Map the requested capability to the code
Write a one-sentence reason for the dependency: for example, “This module parses a format that the current runtime does not support.” If you cannot state the reason precisely, stop and ask for a smaller change. Compare the package’s feature set with the requirement. A package that provides a complete web framework for one parsing function creates a larger attack surface and maintenance burden than a narrowly scoped library.
Check standard-library and approved alternatives
Test whether the language’s standard library, an existing first-party module, or a package already approved in the repository provides the needed function. Avoid adding a second implementation of a capability the project already has. If a new dependency is justified, document the reason in the pull request so a future maintainer does not remove it as “unused” or replace it without review.
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Inspect direct and transitive additions
A direct dependency can be reasonable while one of its indirect dependencies is unexpected. Enumerate the entire resolved graph and note packages that add native code, network clients, credential helpers, build tools, or install-time execution. SLSA’s dependency-track guidance calls for an inventory sufficient to enumerate all direct and transitive dependencies; ENISA likewise emphasizes necessity and scope.
Step 4: Resolve through the intended source and lock the result
Use the ecosystem’s standard package manager and the project’s existing lockfile format. Verify registry configuration before resolving. In organizations that use both private and public packages, source mapping is essential: NuGet package-source mapping is one example of a control that prevents a package name from being fetched from an unintended feed.
- Confirm the configured registry or package index for the project and environment.
- Resolve the exact version selected by the review, rather than allowing an unconstrained range to float during installation.
- Regenerate or update the lockfile with the normal package-manager command.
- Review the lockfile diff for every newly resolved package, version, source, and integrity field.
- Commit the lockfile with the manifest change and require review of both files.
- Reinstall from the lockfile in a clean environment to verify that the declared graph reproduces.
SLSA cites ecosystem examples: npm registry pinning with package-lock.json integrity hashes, pip’s --require-hashes, go.sum, and Cargo.lock. The exact mechanism differs by ecosystem, but the objective is the same: make the selected artifacts and their expected content explicit.
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Commands and files to use by ecosystem
| Ecosystem | Useful verification control | What to inspect |
|---|---|---|
| npm | npm audit; npm audit signatures where supported |
package.json, package-lock.json, registry configuration, integrity hashes, install scripts, signatures, and provenance attestations |
| Python | pip audit; hash-enforced requirements with --require-hashes |
Requirements or project metadata, the resolved environment, hashes, index configuration, and build or install hooks |
| Go | govulncheck |
go.mod, go.sum, module source, and the complete module graph |
| Rust | cargo audit |
Cargo.toml, Cargo.lock, crate source, build scripts, and resolved transitive crates |
| .NET | Use the project’s configured package audit and source-mapping controls | Project files, lock data where enabled, NuGet package-source mapping, package signatures, and transitive packages |
These commands identify known issues or provide integrity-related checks; they do not replace identity, necessity, or code review. Keep the npm CLI current because its signature and attestation features can change.
Step 5: Audit the complete resolved tree for known vulnerabilities
Run the ecosystem’s dependency audit after resolution and before merge. OWASP lists npm audit, pip audit, govulncheck, and cargo audit as examples. Also check current advisory sources such as the National Vulnerability Database, the GitHub Advisory Database, and OSV, according to your organization’s policy.
Configure CI to fail or require an explicit security review for the severities your project cannot accept. Record the scanner, database date, package version, and result so a later reviewer knows what was checked. Re-run the audit when the lockfile changes, not only when application code changes.
A clean audit is bounded by the advisories and dependency graph recognized at that moment. It does not prove that a package is authentic, free of malware, well maintained, or suitable for your application. An audit can miss a newly disclosed issue, malicious behavior that has no advisory, or a package resolved from an unexpected source.
Step 6: Verify integrity, publisher identity, and provenance
Integrity hashes
An integrity hash lets the package manager compare the downloaded artifact with the content recorded when the dependency was resolved. A mismatch should stop the installation and trigger investigation; do not simply regenerate the lockfile to make the error disappear. Determine whether the registry, lockfile, or cache was changed and whether the expected source is still authoritative.
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A signature can help establish that an artifact was signed by an expected publisher identity. Verify the signing identity and the trust configuration, not just the presence of a signature. A valid signature on the wrong project is still the wrong dependency.
Build provenance
Provenance describes how an artifact was built, potentially including its source repository, revision, builder, and workflow. Compare those claims with the project and version you intended to consume. An attestation is evidence to validate, not a blanket guarantee of safe code. SLSA distinguishes per-fetch integrity, publisher-signature verification, and upstream provenance verification as separate controls.
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For npm, the CLI documentation describes npm audit signatures for verifying registry signatures and provenance attestations on downloaded packages. Because the feature set can change, use a current npm CLI and document the version used in CI.
Step 7: Inspect install-time and runtime behavior
Before allowing a new package into a production build, inspect its package scripts and build hooks. Look for preinstall, install, postinstall, prepare, native compilation, downloaded binaries, shell execution, network access, and reads of environment variables or credential files. A package can pass an advisory scan and still perform risky actions during installation.
Review the source or a trusted source archive for the code paths your application will execute. Pay attention to dynamic downloads, obfuscated scripts, unexpected telemetry, broad filesystem access, and dependencies that are unrelated to the stated feature. Run unfamiliar packages in a disposable or restricted environment first, using the least privilege practical.
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Baseline for an individual project
- Review every dependency introduced by an assistant, including transitive changes.
- Commit the lockfile and use integrity verification where supported.
- Run the current ecosystem audit before merging and after dependency updates.
- Inspect install scripts and source behavior before executing a new package.
- Record the reason, expected version, source, and review decision in the change description.
Stronger controls for teams
Teams can add an approved-package allowlist, a registry proxy or ingestion platform, package-age rules, automated malware and vulnerability feeds, source mapping, and a maintained dependency inventory. CI can require a signed review for new publishers, block packages outside approved registries, and reject lockfile changes that remove integrity data.
SLSA’s Dependency Track describes progressively stronger controls: first inventory and scan results; then controlled ingestion with per-fetch integrity and publisher-signature checks when available; and finally screening such as deny-lists, malware feeds, minimum version age, and provenance verification where available. This is a framework for selecting controls, not a requirement that every project deploy one particular platform.
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|---|---|
| Ecosystem coverage | Does it understand the languages and package managers your repositories use? |
| Tree visibility | Does it enumerate direct and transitive dependencies from the lockfile? |
| Identity checks | Can it detect source or registry mismatches and suspicious name collisions? |
| Lockfile and hash awareness | Does it preserve and verify the exact resolved artifacts? |
| Registry controls | Can it enforce approved sources, proxies, or package allowlists? |
| Security signals | Does it combine vulnerability, malware, and package-health information without presenting any one signal as proof of safety? |
| Signatures and provenance | Can it validate publisher identity and build claims when the ecosystem supplies them? |
| CI policy | Can it fail builds, require exceptions, and retain an auditable decision? |
| Operational fit | Is the setup appropriate for one repository, or does it require organization-wide ingestion and administration? |
A practical review record for each AI-introduced package
Keep a short record attached to the change. It should contain the exact package name and namespace; registry and source-repository links; selected version; maintainer and release-history observations; the feature that requires it; alternatives considered; direct and transitive dependency counts or inventory; lockfile and integrity status; audit date and result; install-script findings; signature or provenance result; and the reviewer’s decision.
This record prevents a common failure mode in AI-assisted work: the code is reviewed while the package-selection rationale disappears. Future updates can then distinguish an intentional dependency from a name that was copied from an assistant response months earlier.
Failure modes and recovery steps
The package does not exist
Do not create an account, add a private registry entry, or publish the name merely to make the build pass. Ask the assistant to identify the documented project and search the intended registry manually. If no authoritative project exists, remove the import and implement the feature with an approved alternative.
The name exists, but the project is different
Stop the install, remove the dependency, and identify the intended package from official project documentation. Check whether the assistant confused a similarly named package or namespace. Record the collision so it is not reintroduced by a later automated change.
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The package is real but pulls in unexpected code
Inspect the transitive graph and install scripts. If the extra functionality is unnecessary, select a narrower package or an existing approved dependency. If the package is still justified, document the additional scope and apply the same review to each newly introduced component.
An audit reports a vulnerability
Determine whether the vulnerable code path is reachable, whether a fixed release exists, and whether the issue affects your deployment. Upgrade, constrain, replace, or isolate the dependency according to policy. Do not suppress the finding solely because the assistant selected the package.
Integrity or provenance verification fails
Do not overwrite the lockfile or accept a new artifact automatically. Compare the expected hash, source, version, and publisher with the registry release. Investigate registry, cache, mirror, or build-pipeline changes and involve the package owner or security team when the discrepancy cannot be explained.
The assistant insists the package is safe
Treat confidence, citations inside generated text, and plausible API examples as unverified claims. Require registry metadata, source history, lockfile evidence, audit output, and provenance checks from independent tools and documentation.
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| Check | It can establish | It cannot establish by itself |
|---|---|---|
| Registry and metadata review | That a name, publisher, version, and project history can be compared with the intended identity | That the code is harmless or necessary |
| Necessity and scope review | That the requested feature has a documented reason and bounded dependency graph | That the package has no vulnerabilities or malicious behavior |
| Lockfile and integrity hash | That installs resolve to the recorded artifact content | That the recorded artifact is the right or safe project |
| Vulnerability audit | That recognized advisories affect the resolved graph | That no undisclosed vulnerability or malware exists |
| Publisher signature | That an artifact was signed by a configured identity | That the signer selected the right code or that the code is secure |
| Provenance attestation | That declared source and build information can be checked | That the build process or source is suitable without validating the claims |
Final merge checklist
- The package name, namespace, registry, and upstream project match exactly.
- Maintainer identity, release history, creation date, and adoption signals have been reviewed as investigation clues.
- The dependency’s necessity and narrower alternatives are documented.
- Direct and transitive dependencies, scripts, and unusual runtime behavior are understood.
- The intended source is configured, the version is pinned, and the lockfile diff is reviewed.
- Integrity hashes are present and verified where supported.
- The current ecosystem audit and relevant advisory sources have been checked.
- Publisher signatures and provenance are validated where available.
- CI will repeat the checks for future updates.
The safest default is simple: an AI assistant may propose a dependency, but your project accepts it only after a human-verifiable chain connects the requested feature to the exact publisher, resolved artifact, dependency graph, and current security policy.
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