
IOCX v0.7.0 — deterministic heuristics + adversarial PE samples
IOCX v0.7.0 is out. It’s a static IOC extraction and PE‑analysis engine built for DFIR and malware‑analysis workflows focused on deterministic behaviour. This release adds a deterministic heuristic engine, new adversarial PE samples, and a contract‑testing framework to keep output stable across runs.
Key changes in v0.7.0:
Deterministic heuristic engine (new)
Snapshot‑tested heuristics for:
- anti‑debug API usage
- TLS callback anomalies
- packer‑like section layouts + entropy
- RWX sections
- import‑table anomalies
- signature anomalies
Runs under analysis_level = full and is designed to avoid false‑positive reconstruction.
Adversarial PE samples (new)
Three intentionally hostile binaries covering:
- rich/atypical imports
- high‑entropy + malformed Rich Headers
- split/reversed/null‑interspersed strings
Useful to validate deterministic heuristics and literal-only IOC extraction.
Rich Header crash fix
Malformed Rich Headers with non‑UTF8 bytes could break JSON serialization. v0.7.0 adds a deep sanitiser that hex‑encodes nested byte structures for deterministic, JSON‑safe output.
Snapshot‑driven contract testing
Each sample has a byte‑for‑byte JSON snapshot. Output must match exactly — same file, same output, every time.
Performance
Remains ~28 MB/s on typical PE samples.
Links
GitHub: https://github.com/iocx-dev/iocx
PyPI: https://pypi.org/project/iocx/
Example
pip install iocx
iocx suspicious.exe -a full
Happy to hear feedback from anyone working with obfuscated or adversarial PE samples.