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43
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12

demo

πŸ—ƒοΈ Polyglot Bug Patterns

🐝 Dataset Β· 🎨 Space Β· 🧠 Model Β· πŸ’» GitHub


Bro, imagine a dataset of 43 non-destructive attack payloads across 8 bug classes β€” 24 of them polyglot, meaning a single string that's simultaneously plausible HTML, JS, SQL and shell, so it escapes whatever context your app dropped it into. Plus real detector output from a full multimodal scan.

Everything here is synthesised or locally generated. No real-world traffic, no scraped data, no user data.

πŸ“¦ What's inside

Config Rows What it is
payloads 43 Every detection payload: value, bug class, CWE, OWASP, CVSS v3.1 vector+score, polyglot flag, and a destructive safety flag.
findings 36 Real findings from one full scan of the bundled demo target, with proof strings, endpoints, remediation, tags.
scans 1 Scan-level rollup: pages scanned, risk score, counts by severity, modality breakdown.
class_index 9 Per-class counts plus totals.

Each config ships JSONL and Parquet, so both of these work:

from datasets import load_dataset

ds = load_dataset("Kicaulah/polyglot-bug-patterns", "payloads")
print(ds["train"][0]["value"])
print(ds["train"].filter(lambda r: r["polyglot"])[0]["value"])

findings = load_dataset("Kicaulah/polyglot-bug-patterns", "findings")
print(len(findings["train"]), "findings from one scan")

🧬 The payload classes

Class n Examples
sqli 8 ' OR 1=1 -- , UNION SELECT NULL, MySQL error-based double-query, ORDER BY 99 column-count probe
xss 9 '"><svg/onload=alert(1)> attr breakout, </script><script> closer, JS-string escape, {{7*7}} SSTI
cmdi 6 ;MARKER;, $(echo …), backticks, %0a CRLF, ${IFS}
traversal 5 ..%2f..%2f..%2fetc%2fpasswd, ....//....//, double-double-encoded
ssrf 5 http://MARKER.oast.invalid/, 127.0.0.1, file:///, gopher://, [::1]
prompt-injection 4 "Ignore all previous instructions", </s>[INST] … [/INST] chat-template escape, markdown-fence system override
nosql-ldap 3 *(), '; return true; //, LDAP wildcard filter
redirect 3 absolute, protocol-relative, backslash open redirect

Every payload carries a unique marker (PBHX7) so reflection is unambiguous β€” that's what makes these usable as training signal for a detector or as a fixture in your own test suite.

⚠️ Safety properties

This is a defensive dataset. Concretely:

  • Every payload is non-destructive by construction. The destructive column is false for all 43 rows β€” verified by the same safety.is_forbidden_payload() gate the scanner itself uses at runtime.
  • No DROP/DELETE/UPDATE/INSERT, no system()/exec()/xp_cmdshell, no sleep()/benchmark(), no reverse shells, no persistence.
  • Time-based blind SQLi is deliberately absent β€” sleep() payloads are blocked project-wide.
  • Payloads are for systems you own or are authorized to test. Using them against someone else's production box is illegal in most jurisdictions.

πŸ§ͺ Using it

As a test fixture β€” assert your WAF/filter catches the polyglot set:

from datasets import load_dataset
ds = load_dataset("Kicaulah/polyglot-bug-patterns", "payloads")["train"]
for row in ds.filter(lambda r: r["vuln_class"] == "xss"):
    print(row["value"])   # feed each through your own escaping function

As detector training data β€” findings pairs a payload with the signal that proved it (proof), the CVSS vector, and the remediation. That's a supervised signal for "was this injection real or a reflection".

As an LLM security eval β€” prompt-injection rows are ready-made instruction overrides for testing whether your model or agent guardrails hold.

πŸ“Š Provenance

  • payloads β€” hand-authored from public documentation (OWASP WSTG, PortSwigger cheat sheets, public CVE writeups), rewritten to be non-destructive and marker-tagged.
  • findings / scans β€” actual output of Hunter.demo() against polyglot_bug_hunter.demo_target, an intentionally vulnerable app that runs on localhost inside the test process. Regenerate with python tools/build_dataset.py.

Nothing was scraped from production systems.

πŸ“ Changelog

  • v1.0.0 β€” initial release: 43 payloads / 8 classes (24 polyglot), 36 findings from one full 4-modality demo scan, JSONL + Parquet, 12 languages declared.

🀝 Contribute a pattern

Missing a class? Open an issue or PR. The bar: it must be non-destructive (the automated gate enforces it), documented with a CWE and an OWASP mapping, and tagged for what detector signal it should produce.

MIT Β· πŸ•·οΈ PolyglotBugHunter-X Β· authorized security testing only

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