docs/LIMITATIONS.md

Known Limitations

AppSecBench is a strong but bounded benchmark. Be aware of these limitations when interpreting results.

Coverage & realism

• Synthetic, isolated snippets. Each case demonstrates one weakness in a few lines. Real code interleaves multiple concerns; high scores here do not guarantee strength on large, messy codebases.
• Not exhaustive. 34 vulnerability classes are covered; many CWE entries and emerging weakness types (e.g. some supply-chain, post-quantum, or domain-specific issues) are not yet represented.
• Framework breadth is curated. Only the frameworks in the supported list appear; other popular stacks (e.g. Rails, Flask alternatives) are not covered in v1.0.0.
• AI/LLM cases are conceptual. Prompt-injection / RAG / MCP / agent examples are illustrative of the control (isolation, scoping, authz, sandboxing), not a full agent harness.

Tooling & checks

• Heuristic syntax checks for some languages. Rust, C#, Java, Kotlin, Swift, PHP, C/C++ are validated with delimiter-balance heuristics when their compiler is absent; a "PASS" on those is a balance check, not a guarantee of compilability. (Python/JS/TS/Go/YAML/Bash use real toolchains when installed.)
• CVSS reflects the archetype, not a specific deployment. Scores use dominant realistic exploitability/impact vectors; a given app's actual risk may differ.

Evaluation

• The reference grader is transparent but shallow. scripts/evaluate.py uses keyword/format matching. For publication-grade results, pair it with an LLM judge or human review; the rubric weights are provided for that purpose.
• Severity priors are estimates. expected_false_positive_probability / expected_false_negative_probability encode difficulty-based priors, not empirically measured rates.

Suggested improvements for v1.1+

• Grow to 1,000+ records with broader language/framework coverage (Rails, Vue, Angular, Scala).
• Add multi-file / multi-function cases and end-to-end mini-apps.
• Add an LLM-judge harness and inter-rater reliability on a labeled sample.
• Add executable test oracles (do the secure snippets actually pass a security test?).
• Expand AI/LLM coverage with full agent/MCP server fixtures.
• Add license/PII redaction checks across more ecosystems.

See CHANGELOG.md for the version plan.