Observed since 21 Oct, 10:51 UTC
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AI-Hacking Self-Audit — non-intrusive, zero-exfiltration personal security self-audit for the AI-hacking era.
A non-intrusive, zero-exfiltration personal security self-audit for macOS.
AI-automated attacks now hit individuals, not just enterprises. This tool shows your security score and exactly what to fix — without attacking anything and without sending a single byte off your machine.
pip install ai-hacking-defense
ai-hacking-defense # or: python3 scan.py → security_report.html
ai-hacking-defense feedback builds a masked, fully-previewed report draft — nothing is ever sent automatically; you submit it yourself on GitHub. Issues are collected into a backlog daily and shipped as releases with a public CHANGELOG, so your report visibly becomes the next version.
macOS: all checks verified. Windows/Linux: experimental — runs, but not yet fully verified.
Detection catches common evasions, not all. Known gaps we have not closed yet:
.ppk), may be missed.open(vault).read()), but it is best-effort, not a guarantee: a read assigned to a variable and then printed/sent, a backslash-escaped command (e.g. ca\t), or copying/sourcing the file (cp, source) can still be missed — new evasions always exist.lsof), not a continuous kernel-level stream: without root not every read is observed, encrypted exfiltration is only inferred from read->connect timing (payload never inspected), and normal backup/sync/browser access is whitelisted (a brand-new legitimate tool may false-positive). It watches only the paths you specify, never the whole disk.Three stdlib-only command-line tools:
ahd-scan (also ai-hacking-defense) — the 7-area security self-audit (incl. Wi-Fi + file-access watch) + HTML report. Zero network.ahd-agent-guard — prompt-injection detector (warn-only, no blocking). On a public prompt-injection evasion corpus it detects 29/30 (96.7%) at 0 false positives in our test. This 96.7% is the injection detector's rate on that one corpus — not an overall "defense rate" across every attack type. Zero network. echo "<text>" | ahd-agent-guardahd-threat-feed — refreshes public vulnerability feeds (OSV, CISA KEV, EPSS) to a local cache. GET-only of public databases from a fixed allowlist — none of your data is ever sent.ahd-scan and ahd-agent-guard make no network calls at all. ahd-threat-feed only downloads public vulnerability data (GET-only, allowlisted hosts) and uploads nothing. In all cases, none of your files, secrets, or data ever leave your machine — that is what zero-exfiltration means here.
This package detects and reports. It does not auto-block, run a background dashboard, or hook into your pipelines. "Warn-only" is literal — see each report card's limits.
pip install ai-hacking-defense
python3 reproduce_detection.py # prints detection % and false-positive % on a public evasion corpus
It reports 29/30 = 96.7% detection at 0 false positives on our standard prompt-injection corpus (one honest miss: full letter-spacing). Scope note: this measures the prompt-injection detector only; other attack types (credential, vault, network) are measured separately and are lower — not rolled into a single "defense rate."
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 0.1.8 | 7 Oct 2026 | 0 |
This describes our collected data; it is not a security assessment.
Shared repository data · GitHub
Public sponsor counts have not been collected. These signals belong to the repository owner.
github · 1 observations shown. Missing days are unknown.
| Date / source period | Value | Observed at |
|---|---|---|
| 2026-10-23 | 0 | 2026-10-23T07:32:15.6092400Z |
Observed since 21 Oct, 10:51 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:153c5463eb1012786427e1c7cafd3559790b33554a6b3c085adb1a4fc3583f8f