ntfs-forensic is designed to parse untrusted NTFS images — including disk images acquired from compromised or actively hostile systems. Hostile input is the expected case, not an edge case. Robustness against crafted structures is a core design goal, and we take reports of crashes, hangs, or memory-safety issues seriously.

Security fixes are released against the latest published 0.1.x line.

Do not open a public GitHub issue for a security vulnerability.

Report privately, by either:

• GitHub Security Advisories — open a private advisory on the ntfs-forensic repository, or
• Email — albert@securityronin.com.

Please include:

• the affected version and target triple,
• a minimal reproducing NTFS image or byte buffer (a fuzz corpus entry is ideal),
• the observed behaviour (panic, hang, excessive allocation, mis-parse) and the expected behaviour.

We aim to acknowledge a report within a few business days and to coordinate disclosure once a fix is available.

ntfs-forensic is hardened against adversarial input by construction:

• #![forbid(unsafe_code)] across the whole crate — no unsafe, anywhere.
• No panics on malicious input — every length and offset is validated against both the structure's declared size and the actual buffer; arithmetic is checked or saturating.
• Bounded allocations — try_reserve_exact and explicit ceilings refuse allocation bombs (e.g. a crafted runlist or LZNT1 stream).
• Loop caps — attribute chains, runlists, and index entries are bounded against non-terminating walks.
• Fixup verification — torn writes and update-sequence-array tampering surface as a typed FixupMismatch error rather than silently-wrong output.
• Partition isolation — OffsetReader makes reading past the volume boundary structurally impossible.

Continuous fuzzing with cargo-fuzz backs the hardening above. Seven targets cover the parsers that consume attacker-controlled bytes:

The crates' panics found by fuzzing (e.g. an LZNT1 chunk-size overflow) are fixed and pinned as regression tests.

For how to run the targets yourself, see CONTRIBUTING.md.