Audit an AI-generated project as if every dependency suggestion were untrusted input. Start with the manifests and lockfiles to build an inventory, verify each package in the intended registry, inspect its source and maintenance signals, run the package manager’s vulnerability audit, and review the results against current advisory databases. For projects that need an enduring record, generate a software bill of materials (SBOM) and repeat the checks whenever dependencies or vulnerability data change.
This process catches two different classes of problems: packages that never should have been installed (including hallucinated or typosquatted names), and real packages whose selected versions are vulnerable, abandoned, or unsuitable for the application. A clean scan is only a time-stamped result from a particular tool and data set, not a complete security review.
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What a dependency audit must establish
An AI coding assistant can produce plausible import statements and package names without knowing whether a package exists, whether it is the right library, or whether its proposed version is safe. An audit should answer five practical questions before the generated code is merged:
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- Does every suggested package exist under the exact name in the registry you intend to use?
- Are the selected versions affected by known vulnerabilities or withdrawn releases?
- Do the packages have enough source, release, and maintainer information to justify their use?
- Can you reproduce the inventory and detect changes or newly disclosed issues later?
Dependency scanning does not replace a review of application logic, configuration, build scripts, secrets, deployment permissions, or runtime behavior. It is one control in a broader software-supply-chain and application-security process.
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Step 1: Build the authoritative dependency inventory
Find every manifest
Search the repository for the files used by its package managers. Common examples include package.json for JavaScript, pyproject.toml or requirements.txt for Python, go.mod for Go, Cargo.toml for Rust, Maven or Gradle build files for Java, and project files for .NET. An AI-generated repository may contain more than one ecosystem, such as a JavaScript front end and a Python service, so audit each one rather than assuming the first manifest is complete.
Read the lockfiles, not just the requested ranges
A manifest expresses what the project asks for; a lockfile records the concrete versions and transitive packages selected by the resolver. Inspect the lockfiles present in the repository, such as package-lock.json, yarn.lock, pnpm-lock.yaml, Python lock files, go.sum, or Cargo.lock. Confirm that the lockfile is generated by the package manager and version expected by the project, and that it is included in the review when the project’s workflow uses one.
Record both direct dependencies (declared by the application) and transitive dependencies (pulled in by those direct packages). A vulnerability in a transitive component still matters if it is shipped, imported into a build artifact, or available to a runtime process.
Use an SBOM when the inventory must persist
An SBOM is a machine-readable record of an application’s components and versions. It gives security and operations teams a way to identify affected applications when a vulnerability is disclosed, instead of reconstructing the dependency graph from old builds. OWASP’s February 24, 2025 guidance highlights CycloneDX as an SBOM format and describes OWASP Dependency-Track as a platform that consumes SBOMs for ongoing vulnerability identification. NIST supply-chain guidance also treats SBOMs and vulnerability management as related practices.
Generate the SBOM from the resolved project or build artifact using a tool that supports the project’s ecosystem. Preserve the output with the build or release record, record when it was generated, and establish who owns follow-up for findings. An SBOM is an inventory, not a guarantee that every component is safe; its value depends on accurate component identifiers and a process that evaluates new advisories.
Step 2: Verify every AI-suggested package identity
Check the exact registry name before installation
Search the intended public registry for the exact package name, including punctuation, scope, and capitalization where the ecosystem treats those distinctions as meaningful. OWASP’s Secure Coding with AI Cheat Sheet states: “Verify every AI-suggested package exists on the public registry before installing.” This check should happen before a generated install command is run, not after the package has entered the lockfile.
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A nonexistent name may be an AI hallucination. It may also be a name that an attacker registers later to exploit developers who copy generated code. A package with a familiar-looking name can be typosquatting a legitimate project. If the registry does not contain the exact package, stop and identify the intended library from its official documentation or source repository rather than choosing the closest spelling.
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Separate identity from suitability
Finding a real package does not establish that it is appropriate. Compare the package’s documented purpose with the generated code’s need. Check whether the project is using a server-side library in a client bundle, a development-only tool at runtime, or a large framework for a narrowly scoped task. Remove suggestions that duplicate an existing capability unless the additional dependency has a clear, documented benefit.
Use maintenance signals as warning indicators
Review the registry page and source repository for release history, latest release date, maintainer continuity, issue and pull-request activity, licensing information, and download or adoption trends. A newly created package, an abrupt maintainer change, copied documentation, or no meaningful source history deserves extra scrutiny. These signals are clues, not proof of safety: a popular package can contain a vulnerability, and a small but well-maintained package can be legitimate.
Inspect the package source, build scripts, install hooks, and permissions requested by the generated application. Look for network calls, shell execution, credential access, obfuscated files, or scripts that run automatically during installation. Confirm that the source being reviewed corresponds to the exact version in the lockfile and that published artifacts are consistent with the repository where practical.
Step 3: Check versions against vulnerability data
Run the ecosystem-native audit
Use the package manager or ecosystem tool appropriate to each project component. The OWASP guidance names these examples:
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| Ecosystem | Example audit command | What to verify |
|---|---|---|
| JavaScript and npm projects | npm audit |
Run from the directory containing the relevant manifest and lockfile; review direct and transitive findings. |
| Python projects | pip audit |
Audit the environment or dependency set that the project actually resolves, not an unrelated global environment. |
| Go projects | govulncheck |
Use the project’s module graph and examine whether a reported vulnerable package is reachable by the application. |
| Rust projects | cargo audit |
Run against the checked-in Cargo.lock where the project uses one and investigate affected transitive crates. |
Commands and supported file formats change. Read the current documentation for the selected tool and verify that it supports the project’s package manager, lockfile format, and language version before treating a clean result as meaningful.
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Interpret severity and reachability
Capture the package name, affected version range, advisory identifier, severity, fix version if one exists, and the path that brings the component into the graph. Determine whether the vulnerable code is reachable in the deployed product, present only in development tooling, or included in a build artifact that users receive. Do not dismiss a finding solely because it is transitive; document the reason when reachability or deployment context reduces its practical impact.
Conversely, do not assume that a “high” label automatically tells you the business risk. Examine the advisory’s conditions, affected functionality, authentication requirements, and whether the project exposes that functionality. Record both the technical assessment and the decision owner so that a later reviewer can understand why a finding was fixed, upgraded, isolated, or accepted.
Cross-check independent advisory sources
Compare scanner results with current records from the National Vulnerability Database (NVD), the GitHub Advisory Database, and OSV. Different databases can publish at different times or use different package identifiers. Check that the advisory maps to the same ecosystem and package, that the affected version range includes the locked version, and that a proposed fix is actually available in the registry you use.
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Step 4: Remediate without breaking the generated application
Prefer the smallest controlled update
When a fixed version exists, update the direct dependency or the parent package that brings in the vulnerable transitive component. Regenerate the lockfile with the project’s normal package-manager workflow, review the resulting diff, and rerun tests and the audit. Avoid an indiscriminate “upgrade everything” operation in a fragile generated project: it can introduce unrelated breaking changes and make it difficult to identify which change resolved or created a problem.
Replace, remove, or isolate questionable packages
If a package is unmaintained, unnecessary, unverifiable, or unsuitable for the required feature, remove it or replace it with a well-documented alternative selected through an independent review. If removal cannot happen immediately, consider isolating the functionality, restricting permissions, preventing untrusted input from reaching it, or excluding it from production artifacts. Document the temporary control and a deadline for reassessment; an exception without an owner becomes permanent risk.
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Handle findings with no available fix
Some advisories have no patched release or affect a dependency that cannot be upgraded without a larger migration. Record the affected versions, exploit conditions, deployment exposure, compensating controls, and the person who accepted the residual risk. Recheck the advisory on a defined schedule because a fix, workaround, or revised impact assessment may later become available.
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Step 5: Compare scanner capabilities before standardizing
A single scanner rarely handles every repository equally well. Evaluate a tool against the project you actually operate rather than relying on a generic feature list.
| Audit axis | Questions to ask |
|---|---|
| Language and file support | Does it parse every manifest and lockfile in the repository, including the formats used by generated subprojects? |
| Graph coverage | Does it identify both direct and transitive components, and can it explain the path from an application dependency to a finding? |
| Advisory data | Which vulnerability sources does it use, how often are they updated, and how are package aliases and withdrawn releases handled? |
| SBOM exchange | Can it import and export a standard SBOM such as CycloneDX, and can the output be attached to a release record? |
| Ongoing monitoring | Can it alert when a new advisory affects an existing SBOM or lockfile, rather than scanning only when a developer remembers to run it? |
| Workflow integration | Can it run before merge, produce reviewable output, and distinguish new findings from previously accepted ones? |
OWASP dep-scan documentation describes support for numerous project types and formats, including npm lockfiles, Maven and Gradle, Python lockfiles, Go, Ruby, Rust, and .NET, and describes SBOM generation for scanning. Because support changes, confirm the current list and behavior for your repository before adopting any tool as a required gate.
Step 6: Make the audit repeatable
Run checks at the right events
Run dependency checks before merging generated code, whenever a manifest or lockfile changes, and when new vulnerability advisories are published. A scheduled scan of the default branch or released SBOM catches disclosures that occur after the original review. For applications with frequent releases or sensitive data, continuous monitoring is more useful than relying on a quarterly manual check.
Protect the lockfile and review changes
Keep versions pinned through the project’s normal package-management process and require review of lockfile diffs. A lockfile change can add a new transitive package even when the manifest appears unchanged. Check for unexpected registry hosts, altered integrity or checksum fields, sudden dependency-tree expansion, and package replacements that the generated code does not need.
Store evidence with the release
Keep the audit date, tool and version, advisory-data date when available, manifest and lockfile commit, SBOM, findings, and remediation decisions. This record lets a team answer which releases contain a component and whether a newly disclosed issue was present. It also prevents repeated investigation of the same accepted finding without context.
A practical review checklist
- List every manifest and lockfile, including nested services, examples, and build directories that ship code.
- Resolve the dependency graph and distinguish direct from transitive components.
- Verify each AI-suggested package’s exact identity in the intended public registry.
- Review source, install scripts, release history, maintainer continuity, licensing, and unusual permissions.
- Run the native audit for each ecosystem and confirm the tool parsed the intended lockfile.
- Cross-check affected versions with NVD, the GitHub Advisory Database, and OSV.
- Apply the smallest tested upgrade, remove unnecessary packages, or document compensating controls.
- Generate and retain an SBOM when the project needs durable inventory or monitoring.
- Run the checks before merge, after dependency changes, and when new advisories appear.
- Record findings, exceptions, owners, deadlines, and the exact release or commit reviewed.
Common failure modes and their fixes
“The package name came from the model, so it must be real”
AI systems can invent plausible names or select a similarly named package. Verify the exact registry identity and source before installation. If no authoritative package exists, remove the import and identify the required capability independently.
“The manifest is clean, so the project is clean”
Manifests omit the concrete transitive versions selected by the resolver. Audit the lockfile and deployed artifact, and investigate nested projects rather than scanning only the repository root.
“The scanner returned zero findings”
A zero result may mean that the tool did not support a file format, did not parse the lockfile, lacked a recent advisory, or could not model a vulnerable code path. Confirm coverage and cross-check current advisory sources before recording the result as a release decision.
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Urgency matters, but an untested upgrade can break authentication, data handling, or the build. Identify the affected path, apply the smallest viable fix, test the application, and document any residual exposure when no safe immediate upgrade exists.
“One SBOM or scan is permanent evidence”
Dependencies and vulnerability records change. Tie each inventory to a specific commit or release and schedule new scans when the graph or advisory data changes.
What this audit does not cover
Dependency auditing cannot establish that generated business logic is correct, that configuration is secure, that secrets are protected, that build pipelines are trusted, or that runtime behavior is safe. It also cannot prove that a package with healthy maintenance signals is free of malicious code. Pair the dependency process with code review, secret scanning, testing, least-privilege build and deployment permissions, and incident-response procedures appropriate to the application.
The Bottom Line
For an AI-generated project, trust the resolved dependency graph only after independently verifying package identities, checking locked versions against current vulnerability data, reviewing source and maintenance signals, and preserving an SBOM or equivalent inventory for repeatable monitoring. Treat every audit result as time-bound evidence, not a permanent security guarantee.
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