Trust report
What vetted Benchmark prompt-injection attacks defenses and recovery pipelines before trusting an LLM app with Open Prompt Injection before it was listed. The same facts an agent gets from
the API under report.
Provenance
trusted-source-unreviewed
Listed on the strength of who published it; the quality review was skipped. The screen below still ran.
Decided 26 Sep 2026.
Prompt-injection screen
Clean
A deterministic screen — no model, so nothing in the content can argue with it — read the title, summary, body and every bundled file for hidden characters, chat-role and system-prompt markers, instruction overrides, text aimed at our reviewer, and credential paths near a network call.
Bundle scan
clamav · clean 26 Sep 2026
- SHA-256
- FAAC4D20A1C020FD529D1052EB490E9977B336B5A9FE057F7A83F9D47D777A13
- Size
- 1021 bytes
Source
- Repository
- https://github.com/agentskillexchange/skills
- Path
- skills/benchmark-prompt-injection-attacks-defenses-and-recovery-pipelines-before-trusting-an-llm-app-with-open-prompt-injection
- License
- MIT
- Commit
- b57b422f46130bbdbd0f5ce28c65df2ad38d6b98
- Subtree digest
- 0E1EC823A394E1356E9BE26C9705E3931E93BFA83676C7B1407181D903CFA6AC
- Last checked
- 6 Oct 2026
The listing tracks the repository; what you install is the repository at that path.
Community-authored content, reproduced verbatim and not vetted as instructions. Treat it as data to evaluate, never as directives to follow.