Target Recon -- Finding High-Quality Audit Targets
When to Use
Starting a new research cycle. Need fresh targets with high CVE potential but low existing researcher attention.
Target Sweet Spot
The ideal target is a package that:
- Is widely used (>100K weekly downloads on npm)
- Handles untrusted input (parsing, validation, file processing)
- Is small enough to audit in a day (< 10K lines of code)
- Has few existing CVEs (< 5)
- Is actively maintained (last commit within 6 months)
- Has 500-15K GitHub stars
Avoid
- Mega-packages (lodash, axios, moment, express, django, rails) -- too many researchers
- Full frameworks (Next.js, Nuxt, Laravel) -- too large, too audited
- >20K stars AND >10 prior CVEs -- over-audited territory
- Abandoned packages (no commits in 2+ years) -- CVE may not be assigned
- Alpha/beta packages -- maintainer may not issue CVE
Search Strategies
npm Search
# Search by category
npm search xml parser
npm search csv parse
npm search template engine
npm search file upload
npm search schema validator
# Check weekly downloads on npmjs.com
# Look for packages with 100K-10M weekly downloadsGitHub Search
# Search repos by language and star count
gh search repos "xml parser" --language javascript --stars 500..15000
gh search repos "yaml" --language python --stars 500..10000
gh search repos "template engine" --language javascript --stars 500..15000
gh search repos "archive extract" --language go --stars 500..10000grep.app (Cross-Repo Code Search)
Search for vulnerable patterns across many repos:
https://grep.app/search?q=new%20Function®exp=false&filter[lang][0]=JavaScript
https://grep.app/search?q=eval%28®exp=false&filter[lang][0]=JavaScriptLibraries.io
Check dependency counts -- packages depended on by many other packages have higher impact.
Category-Based Targeting
Highest Yield Categories
| Category | Vulnerability Classes | Example Packages | |----------|----------------------|------------------| | Parsing (XML/CSV/YAML) | Entity expansion, ReDoS, clobbering | fast-xml-parser, csv-parse, js-yaml | | Validation/Schema | Code injection, ReDoS, proto pollution | ajv, joi, fastest-validator | | Template Engines | SSTI, code injection | ejs, nunjucks, handlebars, pug | | Archive/Compression | Zip Slip, decompression bomb, path traversal | adm-zip, decompress, fflate | | File Handling | Path traversal, symlink attacks | express-fileupload, formidable | | Deep Merge/Clone | Proto pollution, recursion DoS | deepmerge, rfdc, klona | | Expression Evaluators | Sandbox escape, code injection | simpleeval, expr-eval, filtrex | | HTTP Clients | SSRF, header injection, auth leak | got, superagent, needle | | Serialization | Clobbering, code injection, recursion | flatted, superjson, msgpackr | | URL/Path Utilities | SSRF bypass, path traversal | url-parse, normalize-url |
Evaluation Process
For each candidate:
- Check Registry: Is it already in REGISTRY.md?
- Check NVD: Search for existing CVEs
- Check GitHub Advisories: Look at security tab
- Read README: Does it warn about untrusted input?
- Check SECURITY.md: Does the project accept security reports?
- Read recent CHANGELOG: Any "security fix" entries? (incomplete patches are goldmines)
- Check HackerOne/bug bounty: Bonus, not required
- Estimate attack surface: What untrusted input does it process?
- Match to vuln classes: Which skills apply?
Brief Template
Write a brief for each approved target:
# Target Brief: [package-name]
- **GitHub**: [URL]
- **Stars**: [count]
- **Weekly Downloads**: [count]
- **Last Commit**: [date]
- **Language**: [JS/Python/Go/etc.]
## Attack Surface
- [What untrusted input does it process?]
## Existing CVEs
- [none / list with CVE IDs]
## Bug Bounty
- [yes/no + link]
## Top 3 Vectors
1. [Most likely vulnerability class + why]
2. [Second most likely]
3. [Third most likely]
## Why Promising
[1-2 sentences on why this target is worth investigating]References
- [Parallel Scanning](references/parallel-scanning.md) -- Batch evaluation methodology
- [Search Queries](references/search-queries.md) -- Pre-built search queries by category