Please report security issues privately to g@abejar.net.

Do not file public GitHub issues for vulnerabilities. Include the affected component (detector / static deobfuscator / LLM deobfuscator / IoC extractor / classifier / sandbox comparator) and a reproducer. We aim to acknowledge reports within 72 hours.

• Sample execution: this project must NEVER execute the analysed sample. If you find a code path that calls eval, exec, subprocess.run on attacker-controlled bytes, that's a critical bug.
• Path-traversal / file-write outside the user's CWD via the CLI's --output flag.
• LLM analyst escalating a benign sample to ransomware / wiper / credential_stealer without any heuristic capability evidence (anti-hallucination guard bypass).
• IoC extractor mis-classifying a domain in a way that lets an attacker smuggle a malicious URL past defang().
• Static deobfuscator infinite loop (the max_layers cap exists for this reason; if you can defeat it, that's a bug).
• Pickle / yaml / unsafe deserialisation in any code path.

• Static-analysis false positives or false negatives. The classifier is intentionally precision-leaning; tune _CAP_PATTERNS for your set.
• LLM rationale prose quality (we strip / truncate; we don't fact-check).
• ImageNet-style adversarial inputs that confuse the heuristic — these are interesting but not security bugs.

This project ships only synthetic, defanged samples in fixtures/ — all URLs use RFC 2606 example domains. We do not bundle, fetch, or distribute real malware. If you submit your own samples, ensure you have legal authority to do so and that they are stored on a compromised- data-handling-approved system.